Vision System for Coarsely Estimating Motion Parameters for Unknown Fast Moving Objects in Space

PubMed Central

Chen, Min; Hashimoto, Koichi

2017-01-01

Motivated by biological interests in analyzing navigation behaviors of flying animals, we attempt to build a system measuring their motion states. To do this, in this paper, we build a vision system to detect unknown fast moving objects within a given space, calculating their motion parameters represented by positions and poses. We proposed a novel method to detect reliable interest points from images of moving objects, which can be hardly detected by general purpose interest point detectors. 3D points reconstructed using these interest points are then grouped and maintained for detected objects, according to a careful schedule, considering appearance and perspective changes. In the estimation step, a method is introduced to adapt the robust estimation procedure used for dense point set to the case for sparse set, reducing the potential risk of greatly biased estimation. Experiments are conducted against real scenes, showing the capability of the system of detecting multiple unknown moving objects and estimating their positions and poses. PMID:29206189

Compressive failure modes and parameter optimization of the trabecular structure of biomimetic fully integrated honeycomb plates.

PubMed

Chen, Jinxiang; Tuo, Wanyong; Zhang, Xiaoming; He, Chenglin; Xie, Juan; Liu, Chang

2016-12-01

To develop lightweight biomimetic composite structures, the compressive failure and mechanical properties of fully integrated honeycomb plates were investigated experimentally and through the finite element method. The results indicated that: fracturing of the fully integrated honeycomb plates primarily occurred in the core layer, including the sealing edge structure. The morphological failures can be classified into two types, namely dislocations and compactions, and were caused primarily by the stress concentrations at the interfaces between the core layer and the upper and lower laminations and secondarily by the disordered short-fiber distribution in the material; although the fully integrated honeycomb plates manufactured in this experiment were imperfect, their mass-specific compressive strength was superior to that of similar biomimetic samples. Therefore, the proposed bio-inspired structure possesses good overall mechanical properties, and a range of parameters, such as the diameter of the transition arc, was defined for enhancing the design of fully integrated honeycomb plates and improving their compressive mechanical properties. Copyright © 2016 Elsevier B.V. All rights reserved.

A fully Galerkin method for the recovery of stiffness and damping parameters in Euler-Bernoulli beam models

NASA Technical Reports Server (NTRS)

Smith, R. C.; Bowers, K. L.

1991-01-01

A fully Sinc-Galerkin method for recovering the spatially varying stiffness and damping parameters in Euler-Bernoulli beam models is presented. The forward problems are discretized with a sinc basis in both the spatial and temporal domains thus yielding an approximate solution which converges exponentially and is valid on the infinite time interval. Hence the method avoids the time-stepping which is characteristic of many of the forward schemes which are used in parameter recovery algorithms. Tikhonov regularization is used to stabilize the resulting inverse problem, and the L-curve method for determining an appropriate value of the regularization parameter is briefly discussed. Numerical examples are given which demonstrate the applicability of the method for both individual and simultaneous recovery of the material parameters.

Inertial parameter identification using contact force information for an unknown object captured by a space manipulator

NASA Astrophysics Data System (ADS)

Chu, Zhongyi; Ma, Ye; Hou, Yueyang; Wang, Fengwen

2017-02-01

This paper presents a novel identification method for the intact inertial parameters of an unknown object in space captured by a manipulator in a space robotic system. With strong dynamic and kinematic coupling existing in the robotic system, the inertial parameter identification of the unknown object is essential for the ideal control strategy based on changes in the attitude and trajectory of the space robot via capturing operations. Conventional studies merely refer to the principle and theory of identification, and an error analysis process of identification is deficient for a practical scenario. To solve this issue, an analysis of the effect of errors on identification is illustrated first, and the accumulation of measurement or estimation errors causing poor identification precision is demonstrated. Meanwhile, a modified identification equation incorporating the contact force, as well as the force/torque of the end-effector, is proposed to weaken the accumulation of errors and improve the identification accuracy. Furthermore, considering a severe disturbance condition caused by various measured noises, the hybrid immune algorithm, Recursive Least Squares and Affine Projection Sign Algorithm (RLS-APSA), is employed to decode the modified identification equation to ensure a stable identification property. Finally, to verify the validity of the proposed identification method, the co-simulation of ADAMS-MATLAB is implemented by multi-degree of freedom models of a space robotic system, and the numerical results show a precise and stable identification performance, which is able to guarantee the execution of aerospace operations and prevent failed control strategies.

Dynamic Modeling from Flight Data with Unknown Time Skews

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2016-01-01

A method for estimating dynamic model parameters from flight data with unknown time skews is described and demonstrated. The method combines data reconstruction, nonlinear optimization, and equation-error parameter estimation in the frequency domain to accurately estimate both dynamic model parameters and the relative time skews in the data. Data from a nonlinear F-16 aircraft simulation with realistic noise, instrumentation errors, and arbitrary time skews were used to demonstrate the approach. The approach was further evaluated using flight data from a subscale jet transport aircraft, where the measured data were known to have relative time skews. Comparison of modeling results obtained from time-skewed and time-synchronized data showed that the method accurately estimates both dynamic model parameters and relative time skew parameters from flight data with unknown time skews.

M-MRAC Backstepping for Systems with Unknown Virtual Control Coefficients

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2015-01-01

The paper presents an over-parametrization free certainty equivalence state feedback backstepping adaptive control design method for systems of any relative degree with unmatched uncertainties and unknown virtual control coefficients. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The benefits of the approach are demonstrated in numerical simulations.

Fully 3D modeling of tokamak vertical displacement events with realistic parameters

NASA Astrophysics Data System (ADS)

Pfefferle, David; Ferraro, Nathaniel; Jardin, Stephen; Bhattacharjee, Amitava

2016-10-01

In this work, we model the complex multi-domain and highly non-linear physics of Vertical Displacement Events (VDEs), one of the most damaging off-normal events in tokamaks, with the implicit 3D extended MHD code M3D-C1. The code has recently acquired the capability to include finite thickness conducting structures within the computational domain. By exploiting the possibility of running a linear 3D calculation on top of a non-linear 2D simulation, we monitor the non-axisymmetric stability and assess the eigen-structure of kink modes as the simulation proceeds. Once a stability boundary is crossed, a fully 3D non-linear calculation is launched for the remainder of the simulation, starting from an earlier time of the 2D run. This procedure, along with adaptive zoning, greatly increases the efficiency of the calculation, and allows to perform VDE simulations with realistic parameters and high resolution. Simulations are being validated with NSTX data where both axisymmetric (toroidally averaged) and non-axisymmetric induced and conductive (halo) currents have been measured. This work is supported by US DOE Grant DE-AC02-09CH11466.

Half-blind remote sensing image restoration with partly unknown degradation

NASA Astrophysics Data System (ADS)

Xie, Meihua; Yan, Fengxia

2017-01-01

The problem of image restoration has been extensively studied for its practical importance and theoretical interest. This paper mainly discusses the problem of image restoration with partly unknown kernel. In this model, the degraded kernel function is known but its parameters are unknown. With this model, we should estimate the parameters in Gaussian kernel and the real image simultaneity. For this new problem, a total variation restoration model is put out and an intersect direction iteration algorithm is designed. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) are used to measure the performance of the method. Numerical results show that we can estimate the parameters in kernel accurately, and the new method has both much higher PSNR and much higher SSIM than the expectation maximization (EM) method in many cases. In addition, the accuracy of estimation is not sensitive to noise. Furthermore, even though the support of the kernel is unknown, we can also use this method to get accurate estimation.

A Bayesian Framework for Coupled Estimation of Key Unknown Parameters of Land Water and Energy Balance Equations

NASA Astrophysics Data System (ADS)

Farhadi, L.; Abdolghafoorian, A.

2015-12-01

The land surface is a key component of climate system. It controls the partitioning of available energy at the surface between sensible and latent heat, and partitioning of available water between evaporation and runoff. Water and energy cycle are intrinsically coupled through evaporation, which represents a heat exchange as latent heat flux. Accurate estimation of fluxes of heat and moisture are of significant importance in many fields such as hydrology, climatology and meteorology. In this study we develop and apply a Bayesian framework for estimating the key unknown parameters of terrestrial water and energy balance equations (i.e. moisture and heat diffusion) and their uncertainty in land surface models. These equations are coupled through flux of evaporation. The estimation system is based on the adjoint method for solving a least-squares optimization problem. The cost function consists of aggregated errors on state (i.e. moisture and temperature) with respect to observation and parameters estimation with respect to prior values over the entire assimilation period. This cost function is minimized with respect to parameters to identify models of sensible heat, latent heat/evaporation and drainage and runoff. Inverse of Hessian of the cost function is an approximation of the posterior uncertainty of parameter estimates. Uncertainty of estimated fluxes is estimated by propagating the uncertainty for linear and nonlinear function of key parameters through the method of First Order Second Moment (FOSM). Uncertainty analysis is used in this method to guide the formulation of a well-posed estimation problem. Accuracy of the method is assessed at point scale using surface energy and water fluxes generated by the Simultaneous Heat and Water (SHAW) model at the selected AmeriFlux stations. This method can be applied to diverse climates and land surface conditions with different spatial scales, using remotely sensed measurements of surface moisture and temperature states

Characterizing unknown systematics in large scale structure surveys

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

Agarwal, Nishant; Ho, Shirley; Myers, Adam D.

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data,more » we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.« less

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.

Adaptive fuzzy prescribed performance control for MIMO nonlinear systems with unknown control direction and unknown dead-zone inputs.

PubMed

Shi, Wuxi; Luo, Rui; Li, Baoquan

2017-01-01

In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Fully probabilistic earthquake source inversion on teleseismic scales

NASA Astrophysics Data System (ADS)

Stähler, Simon; Sigloch, Karin

2017-04-01

Seismic source inversion is a non-linear problem in seismology where not just the earthquake parameters but also estimates of their uncertainties are of great practical importance. We have developed a method of fully Bayesian inference for source parameters, based on measurements of waveform cross-correlation between broadband, teleseismic body-wave observations and their modelled counterparts. This approach yields not only depth and moment tensor estimates but also source time functions. These unknowns are parameterised efficiently by harnessing as prior knowledge solutions from a large number of non-Bayesian inversions. The source time function is expressed as a weighted sum of a small number of empirical orthogonal functions, which were derived from a catalogue of >1000 source time functions (STFs) by a principal component analysis. We use a likelihood model based on the cross-correlation misfit between observed and predicted waveforms. The resulting ensemble of solutions provides full uncertainty and covariance information for the source parameters, and permits propagating these source uncertainties into travel time estimates used for seismic tomography. The computational effort is such that routine, global estimation of earthquake mechanisms and source time functions from teleseismic broadband waveforms is feasible. A prerequisite for Bayesian inference is the proper characterisation of the noise afflicting the measurements. We show that, for realistic broadband body-wave seismograms, the systematic error due to an incomplete physical model affects waveform misfits more strongly than random, ambient background noise. In this situation, the waveform cross-correlation coefficient CC, or rather its decorrelation D = 1 - CC, performs more robustly as a misfit criterion than ℓp norms, more commonly used as sample-by-sample measures of misfit based on distances between individual time samples. From a set of over 900 user-supervised, deterministic earthquake source

Searching for 'Unknown Unknowns'

NASA Technical Reports Server (NTRS)

Parsons, Vickie S.

2005-01-01

The NASA Engineering and Safety Center (NESC) was established to improve safety through engineering excellence within NASA programs and projects. As part of this goal, methods are being investigated to enable the NESC to become proactive in identifying areas that may be precursors to future problems. The goal is to find unknown indicators of future problems, not to duplicate the program-specific trending efforts. The data that is critical for detecting these indicators exist in a plethora of dissimilar non-conformance and other databases (without a common format or taxonomy). In fact, much of the data is unstructured text. However, one common database is not required if the right standards and electronic tools are employed. Electronic data mining is a particularly promising tool for this effort into unsupervised learning of common factors. This work in progress began with a systematic evaluation of available data mining software packages, based on documented decision techniques using weighted criteria. The four packages, which were perceived to have the most promise for NASA applications, are being benchmarked and evaluated by independent contractors. Preliminary recommendations for "best practices" in data mining and trending are provided. Final results and recommendations should be available in the Fall 2005. This critical first step in identifying "unknown unknowns" before they become problems is applicable to any set of engineering or programmatic data.

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

Parameter-space metric of semicoherent searches for continuous gravitational waves

NASA Astrophysics Data System (ADS)

Pletsch, Holger J.

2010-08-01

Continuous gravitational-wave (CW) signals such as emitted by spinning neutron stars are an important target class for current detectors. However, the enormous computational demand prohibits fully coherent broadband all-sky searches for prior unknown CW sources over wide ranges of parameter space and for yearlong observation times. More efficient hierarchical “semicoherent” search strategies divide the data into segments much shorter than one year, which are analyzed coherently; then detection statistics from different segments are combined incoherently. To optimally perform the incoherent combination, understanding of the underlying parameter-space structure is requisite. This problem is addressed here by using new coordinates on the parameter space, which yield the first analytical parameter-space metric for the incoherent combination step. This semicoherent metric applies to broadband all-sky surveys (also embedding directed searches at fixed sky position) for isolated CW sources. Furthermore, the additional metric resolution attained through the combination of segments is studied. From the search parameters (sky position, frequency, and frequency derivatives), solely the metric resolution in the frequency derivatives is found to significantly increase with the number of segments.

Characterization of Acoustic Emission Parameters During Testing of Metal Liner Reinforced with Fully Resin Impregnated CNG Cylinder

NASA Astrophysics Data System (ADS)

Kenok, R.; Jomdecha, C.; Jirarungsatian, C.

The aim of this paper is to study the acoustic emission (AE) parameters obtained from CNG cylinders during pressurization. AE from flaw propagation, material integrity, and pressuring of cylinder was the main objective for characterization. CNG cylinders of ISO 11439, resin fully wrapped type and metal liner type, were employed to test by hydrostatic stressing. The pressure was step increased until 1.1 time of operating pressure. Two AE sensors, resonance frequency of 150 kHz, were mounted on the cylinder wall to detect the AE throughout the testing. From the experiment results, AE can be detected from pressuring rate, material integrity, and flaw propagation from the cylinder wall. AE parameters including Amplitude, Count, Energy (MARSE), Duration and Rise time were analyzed to distinguish the AE data. The results show that the AE of flaw propagation was different in character from that of pressurization. Especially, AE detected from flaws of resin wrapped and metal liner was significantly different. To locate the flaw position, both the AE sensors can be accurately used to locate the flaw propagation in a linear pattern. The error was less than ±5 cm.

Three-dimensional cinematography with control object of unknown shape.

PubMed

Dapena, J; Harman, E A; Miller, J A

1982-01-01

A technique for reconstruction of three-dimensional (3D) motion which involves a simple filming procedure but allows the deduction of coordinates in large object volumes was developed. Internal camera parameters are calculated from measurements of the film images of two calibrated crosses while external camera parameters are calculated from the film images of points in a control object of unknown shape but at least one known length. The control object, which includes the volume in which the activity is to take place, is formed by a series of poles placed at unknown locations, each carrying two targets. From the internal and external camera parameters, and from locations of the images of point in the films of the two cameras, 3D coordinates of the point can be calculated. Root mean square errors of the three coordinates of points in a large object volume (5m x 5m x 1.5m) were 15 mm, 13 mm, 13 mm and 6 mm, and relative errors in lengths averaged 0.5%, 0.7% and 0.5%, respectively.

Estimating unknown parameters in haemophilia using expert judgement elicitation.

PubMed

Fischer, K; Lewandowski, D; Janssen, M P

2013-09-01

The increasing attention to healthcare costs and treatment efficiency has led to an increasing demand for quantitative data concerning patient and treatment characteristics in haemophilia. However, most of these data are difficult to obtain. The aim of this study was to use expert judgement elicitation (EJE) to estimate currently unavailable key parameters for treatment models in severe haemophilia A. Using a formal expert elicitation procedure, 19 international experts provided information on (i) natural bleeding frequency according to age and onset of bleeding, (ii) treatment of bleeds, (iii) time needed to control bleeding after starting secondary prophylaxis, (iv) dose requirements for secondary prophylaxis according to onset of bleeding, and (v) life-expectancy. For each parameter experts provided their quantitative estimates (median, P10, P90), which were combined using a graphical method. In addition, information was obtained concerning key decision parameters of haemophilia treatment. There was most agreement between experts regarding bleeding frequencies for patients treated on demand with an average onset of joint bleeding (1.7 years): median 12 joint bleeds per year (95% confidence interval 0.9-36) for patients ≤ 18, and 11 (0.8-61) for adult patients. Less agreement was observed concerning estimated effective dose for secondary prophylaxis in adults: median 2000 IU every other day The majority (63%) of experts expected that a single minor joint bleed could cause irreversible damage, and would accept up to three minor joint bleeds or one trauma related joint bleed annually on prophylaxis. Expert judgement elicitation allowed structured capturing of quantitative expert estimates. It generated novel data to be used in computer modelling, clinical care, and trial design. © 2013 John Wiley & Sons Ltd.

Analysis of multinomial models with unknown index using data augmentation

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, R.M.; Link, W.A.

2007-01-01

Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.

MoCha: Molecular Characterization of Unknown Pathways.

PubMed

Lobo, Daniel; Hammelman, Jennifer; Levin, Michael

2016-04-01

Automated methods for the reverse-engineering of complex regulatory networks are paving the way for the inference of mechanistic comprehensive models directly from experimental data. These novel methods can infer not only the relations and parameters of the known molecules defined in their input datasets, but also unknown components and pathways identified as necessary by the automated algorithms. Identifying the molecular nature of these unknown components is a crucial step for making testable predictions and experimentally validating the models, yet no specific and efficient tools exist to aid in this process. To this end, we present here MoCha (Molecular Characterization), a tool optimized for the search of unknown proteins and their pathways from a given set of known interacting proteins. MoCha uses the comprehensive dataset of protein-protein interactions provided by the STRING database, which currently includes more than a billion interactions from over 2,000 organisms. MoCha is highly optimized, performing typical searches within seconds. We demonstrate the use of MoCha with the characterization of unknown components from reverse-engineered models from the literature. MoCha is useful for working on network models by hand or as a downstream step of a model inference engine workflow and represents a valuable and efficient tool for the characterization of unknown pathways using known data from thousands of organisms. MoCha and its source code are freely available online under the GPLv3 license.

On selecting a prior for the precision parameter of Dirichlet process mixture models

USGS Publications Warehouse

Dorazio, R.M.

2009-01-01

In hierarchical mixture models the Dirichlet process is used to specify latent patterns of heterogeneity, particularly when the distribution of latent parameters is thought to be clustered (multimodal). The parameters of a Dirichlet process include a precision parameter ?? and a base probability measure G0. In problems where ?? is unknown and must be estimated, inferences about the level of clustering can be sensitive to the choice of prior assumed for ??. In this paper an approach is developed for computing a prior for the precision parameter ?? that can be used in the presence or absence of prior information about the level of clustering. This approach is illustrated in an analysis of counts of stream fishes. The results of this fully Bayesian analysis are compared with an empirical Bayes analysis of the same data and with a Bayesian analysis based on an alternative commonly used prior.

Bayesian source term determination with unknown covariance of measurements

NASA Astrophysics Data System (ADS)

Belal, Alkomiet; Tichý, Ondřej; Šmídl, Václav

2017-04-01

Determination of a source term of release of a hazardous material into the atmosphere is a very important task for emergency response. We are concerned with the problem of estimation of the source term in the conventional linear inverse problem, y = Mx, where the relationship between the vector of observations y is described using the source-receptor-sensitivity (SRS) matrix M and the unknown source term x. Since the system is typically ill-conditioned, the problem is recast as an optimization problem minR,B(y - Mx)TR-1(y - Mx) + xTB-1x. The first term minimizes the error of the measurements with covariance matrix R, and the second term is a regularization of the source term. There are different types of regularization arising for different choices of matrices R and B, for example, Tikhonov regularization assumes covariance matrix B as the identity matrix multiplied by scalar parameter. In this contribution, we adopt a Bayesian approach to make inference on the unknown source term x as well as unknown R and B. We assume prior on x to be a Gaussian with zero mean and unknown diagonal covariance matrix B. The covariance matrix of the likelihood R is also unknown. We consider two potential choices of the structure of the matrix R. First is the diagonal matrix and the second is a locally correlated structure using information on topology of the measuring network. Since the inference of the model is intractable, iterative variational Bayes algorithm is used for simultaneous estimation of all model parameters. The practical usefulness of our contribution is demonstrated on an application of the resulting algorithm to real data from the European Tracer Experiment (ETEX). This research is supported by EEA/Norwegian Financial Mechanism under project MSMT-28477/2014 Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI).

PARTICLE FILTERING WITH SEQUENTIAL PARAMETER LEARNING FOR NONLINEAR BOLD fMRI SIGNALS.

PubMed

Xia, Jing; Wang, Michelle Yongmei

Analyzing the blood oxygenation level dependent (BOLD) effect in the functional magnetic resonance imaging (fMRI) is typically based on recent ground-breaking time series analysis techniques. This work represents a significant improvement over existing approaches to system identification using nonlinear hemodynamic models. It is important for three reasons. First, instead of using linearized approximations of the dynamics, we present a nonlinear filtering based on the sequential Monte Carlo method to capture the inherent nonlinearities in the physiological system. Second, we simultaneously estimate the hidden physiological states and the system parameters through particle filtering with sequential parameter learning to fully take advantage of the dynamic information of the BOLD signals. Third, during the unknown static parameter learning, we employ the low-dimensional sufficient statistics for efficiency and avoiding potential degeneration of the parameters. The performance of the proposed method is validated using both the simulated data and real BOLD fMRI data.

Parameter Estimation for GRACE-FO Geometric Ranging Errors

NASA Astrophysics Data System (ADS)

Wegener, H.; Mueller, V.; Darbeheshti, N.; Naeimi, M.; Heinzel, G.

2017-12-01

Onboard GRACE-FO, the novel Laser Ranging Instrument (LRI) serves as a technology demonstrator, but it is a fully functional instrument to provide an additional high-precision measurement of the primary mission observable: the biased range between the two spacecraft. Its (expectedly) two largest error sources are laser frequency noise and tilt-to-length (TTL) coupling. While not much can be done about laser frequency noise, the mechanics of the TTL error are widely understood. They depend, however, on unknown parameters. In order to improve the quality of the ranging data, it is hence essential to accurately estimate these parameters and remove the resulting TTL error from the data.Means to do so will be discussed. In particular, the possibility of using calibration maneuvers, the utility of the attitude information provided by the LRI via Differential Wavefront Sensing (DWS), and the benefit from combining ranging data from LRI with ranging data from the established microwave ranging, will be mentioned.

16. Photocopy of photograph (Photographer unknown, Date unknown) SUPPOSED OLDEST ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

16. Photocopy of photograph (Photographer unknown, Date unknown) SUPPOSED OLDEST VIEW OF MAIN AND EAST ELEVATIONS - Caleb Pusey House, 15 Race Street (Landingford Plantation), Upland, Delaware County, PA

Adaptive Neural Output Feedback Control for Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis and Unknown Control Directions.

PubMed

Yu, Zhaoxu; Li, Shugang; Yu, Zhaosheng; Li, Fangfei

2018-04-01

This paper investigates the problem of output feedback adaptive stabilization for a class of nonstrict-feedback stochastic nonlinear systems with both unknown backlashlike hysteresis and unknown control directions. A new linear state transformation is applied to the original system, and then, control design for the new system becomes feasible. By combining the neural network's (NN's) parameterization, variable separation technique, and Nussbaum gain function method, an input-driven observer-based adaptive NN control scheme, which involves only one parameter to be updated, is developed for such systems. All closed-loop signals are bounded in probability and the error signals remain semiglobally bounded in the fourth moment (or mean square). Finally, the effectiveness and the applicability of the proposed control design are verified by two simulation examples.

7. Photocopy of painting (Source unknown, Date unknown) EXTERIOR SOUTH ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

7. Photocopy of painting (Source unknown, Date unknown) EXTERIOR SOUTH FRONT VIEW OF MISSION AND CONVENTO AFTER 1913 - Mission San Francisco Solano de Sonoma, First & Spain Streets, Sonoma, Sonoma County, CA

6. Photocopy of photograph Photographer unknown, date unknown DETAIL OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

6. Photocopy of photograph Photographer unknown, date unknown DETAIL OF BOTTOM OF DRUM, SHOWING DECORATIVE MOLDING OF DRUM AND ARCHES: NOTE EFFECT OF BOX BEAMS CREATED BY MOLDING - University of Kentucky, Carnegie Library, Lexington, Fayette County, KY

396. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

396. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; SAN FRANCISCO - OAKLAND BAY BRIDGE; EAST BAY CROSSING; CANTILEVER STRUCTURE; DETAILS I; DRG. NO. 68 - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

393. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

393. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; SAN FRANCISCO - OAKLAND BAY BRIDGE; EAST BAY CROSSING; PIER-E3; GENERAL DETAILS; DRG. NO. 47 - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

397. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

397. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; SAN FRANCISCO - OAKLAND BAY BRIDGE; EAST BAY CROSSING; CANTILEVER STRUCTURE; DETAILS II; DRG. NO. 69 - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

398. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

398. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; SAN FRANCISCO - OAKLAND BAY BRIDGE; EAST BAY CROSSING; GENERAL PLAN; TOWER E-9; DRG. NO. 59 - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Structural control and health monitoring of building structures with unknown ground excitations: Experimental investigation

NASA Astrophysics Data System (ADS)

He, Jia; Xu, You-Lin; Zhan, Sheng; Huang, Qin

2017-03-01

When health monitoring system and vibration control system both are required for a building structure, it will be beneficial and cost-effective to integrate these two systems together for creating a smart building structure. Recently, on the basis of extended Kalman filter (EKF), a time-domain integrated approach was proposed for the identification of structural parameters of the controlled buildings with unknown ground excitations. The identified physical parameters and structural state vectors were then utilized to determine the control force for vibration suppression. In this paper, the possibility of establishing such a smart building structure with the function of simultaneous damage detection and vibration suppression was explored experimentally. A five-story shear building structure equipped with three magneto-rheological (MR) dampers was built. Four additional columns were added to the building model, and several damage scenarios were then simulated by symmetrically cutting off these columns in certain stories. Two sets of earthquakes, i.e. Kobe earthquake and Northridge earthquake, were considered as seismic input and assumed to be unknown during the tests. The structural parameters and the unknown ground excitations were identified during the tests by using the proposed identification method with the measured control forces. Based on the identified structural parameters and system states, a switching control law was employed to adjust the current applied to the MR dampers for the purpose of vibration attenuation. The experimental results show that the presented approach is capable of satisfactorily identifying structural damages and unknown excitations on one hand and significantly mitigating the structural vibration on the other hand.

400. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

400. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; SAN FRANCISCO - OAKLAND BAY BRIDGE; EAST BAY CROSSING; PIER E-6 TO E-23; TYPICAL DETAILS; DRG. NO. 52 - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

414. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

414. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; DIVISION OF SAN FRANCISCO BAY TOLL CROSSINGS; SAN FRANCISCO OAKLAND BAY BRIDGE RECONSTRUCTION; STEEL WORK - WEST BAY; TYPICAL SECTIONS; SHEET NO. 5; DRAWING NO. C-4028-5R - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

Iron overload patients with unknown etiology from national survey in Japan.

PubMed

Ikuta, Katsuya; Hatayama, Mayumi; Addo, Lynda; Toki, Yasumichi; Sasaki, Katsunori; Tatsumi, Yasuaki; Hattori, Ai; Kato, Ayako; Kato, Koichi; Hayashi, Hisao; Suzuki, Takahiro; Kobune, Masayoshi; Tsutsui, Miyuki; Gotoh, Akihiko; Aota, Yasuo; Matsuura, Motoo; Hamada, Yuzuru; Tokuda, Takahiro; Komatsu, Norio; Kohgo, Yutaka

2017-03-01

Transfusion is believed to be the main cause of iron overload in Japan. A nationwide survey on post-transfusional iron overload subsequently led to the establishment of guidelines for iron chelation therapy in this country. To date, however, detailed clinical information on the entire iron overload population in Japan has not been fully investigated. In the present study, we obtained and studied detailed clinical information on the iron overload patient population in Japan. Of 1109 iron overload cases, 93.1% were considered to have occurred post-transfusion. There were, however, 76 cases of iron overload of unknown origin, which suggest that many clinicians in Japan may encounter some difficulty in correctly diagnosing and treating iron overload. Further clinical data were obtained for 32 cases of iron overload of unknown origin; median of serum ferritin was 1860.5 ng/mL. As occurs in post-transfusional iron overload, liver dysfunction was found to be as high as 95.7% when serum ferritin levels exceeded 1000 ng/mL in these patients. Gene mutation analysis of the iron metabolism-related genes in 27 cases of iron overload with unknown etiology revealed mutations in the gene coding hemojuvelin, transferrin receptor 2, and ferroportin; this indicates that although rare, hereditary hemochromatosis does occur in Japan.

413. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

413. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; DIVISION OF SAN FRANCISCO BAY TOLL CROSSINGS; SAN FRANCISCO OAKLAND BAY BRIDGE RECONSTRUCTION; STEEL WORK - WEST BAY; CONTINUOUS SPANS - LONGITUDINAL GIRDERS; SHEET NO. 18; DRAWING NO. C-4028-18R - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

Unknown loads affect force production capacity in early phases of bench press throws.

PubMed

Hernández Davó, J L; Sabido Solana, R; Sarabia Marínm, J M; Sánchez Martos, Á; Moya Ramón, M

2015-10-01

Explosive strength training aims to improve force generation in early phases of movement due to its importance in sport performance. The present study examined the influence of lack of knowledge about the load lifted in explosive parameters during bench press throws. Thirteen healthy young men (22.8±2.0 years) participated in the study. Participants performed bench press throws with three different loads (30, 50 and 70% of 1 repetition maximum) in two different conditions (known and unknown loads). In unknown condition, loads were changed within sets in each repetition and participants did not know the load, whereas in known condition the load did not change within sets and participants had knowledge about the load lifted. Results of repeated-measures ANOVA revealed that unknown conditions involves higher power in the first 30, 50, 100 and 150 ms with the three loads, higher values of ratio of force development in those first instants, and differences in time to reach maximal rate of force development with 50 and 70% of 1 repetition maximum. This study showed that unknown conditions elicit higher values of explosive parameters in early phases of bench press throws, thereby this kind of methodology could be considered in explosive strength training.

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.

14. Photocopy of photograph (source unknown) photographer unknown pre1885 NORTH ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. Photocopy of photograph (source unknown) photographer unknown pre-1885 NORTH SIDE AND WEST FRONT (NOTE ABSENCE OF DORMER ON GAMBREL ROOF OF ELL) (Illustration #6 of Data Report included in Field Records) - Narbonne House, 71 Essex Street, Salem, Essex County, MA

415. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

415. Delineator Unknown Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; DIVISION OF SAN FRANCISCO BAY TOLL CROSSINGS; SAN FRANCISCO OAKLAND BAY BRIDGE RECONSTRUCTION; STEEL WORK - WEST BAY; Y.B. ANCHORAGE - FLOOR BEAMS YA-5 AND BENT 3; SHEET NO. 22; DRAWING NO. C-4028-22R - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

Fully automated segmentation of callus by micro-CT compared to biomechanics.

PubMed

Bissinger, Oliver; Götz, Carolin; Wolff, Klaus-Dietrich; Hapfelmeier, Alexander; Prodinger, Peter Michael; Tischer, Thomas

2017-07-11

A high percentage of closed femur fractures have slight comminution. Using micro-CT (μCT), multiple fragment segmentation is much more difficult than segmentation of unfractured or osteotomied bone. Manual or semi-automated segmentation has been performed to date. However, such segmentation is extremely laborious, time-consuming and error-prone. Our aim was to therefore apply a fully automated segmentation algorithm to determine μCT parameters and examine their association with biomechanics. The femura of 64 rats taken after randomised inhibitory or neutral medication, in terms of the effect on fracture healing, and controls were closed fractured after a Kirschner wire was inserted. After 21 days, μCT and biomechanical parameters were determined by a fully automated method and correlated (Pearson's correlation). The fully automated segmentation algorithm automatically detected bone and simultaneously separated cortical bone from callus without requiring ROI selection for each single bony structure. We found an association of structural callus parameters obtained by μCT to the biomechanical properties. However, results were only explicable by additionally considering the callus location. A large number of slightly comminuted fractures in combination with therapies that influence the callus qualitatively and/or quantitatively considerably affects the association between μCT and biomechanics. In the future, contrast-enhanced μCT imaging of the callus cartilage might provide more information to improve the non-destructive and non-invasive prediction of callus mechanical properties. As studies evaluating such important drugs increase, fully automated segmentation appears to be clinically important.

Exploring the Unknown

ERIC Educational Resources Information Center

Pallant, Amy; Pryputniewicz, Sarah; Lee, Hee-Sun

2012-01-01

Scientists, and science in general, move from the unknown to increasing levels of certainty. Teaching students about science means encouraging them to embrace and investigate the unknown, make reliable scientific claims, justify those claims with evidence, and evaluate the quality of the evidence. In all areas of science--and especially in…

Protein-like fully reversible tetramerisation and super-association of an aminocellulose

NASA Astrophysics Data System (ADS)

Nikolajski, Melanie; Adams, Gary G.; Gillis, Richard B.; Besong, David Tabot; Rowe, Arthur J.; Heinze, Thomas; Harding, Stephen E.

2014-01-01

Unusual protein-like, partially reversible associative behaviour has recently been observed in solutions of the water soluble carbohydrates known as 6-deoxy-6-(ω-aminoalkyl)aminocelluloses, which produce controllable self-assembling films for enzyme immobilisation and other biotechnological applications. Now, for the first time, we have found a fully reversible self-association (tetramerisation) within this family of polysaccharides. Remarkably these carbohydrate tetramers are then seen to associate further in a regular way into supra-molecular complexes. Fully reversible oligomerisation has been hitherto completely unknown for carbohydrates and instead resembles in some respects the assembly of polypeptides and proteins like haemoglobin and its sickle cell mutation. Our traditional perceptions as to what might be considered ``protein-like'' and what might be considered as ``carbohydrate-like'' behaviour may need to be rendered more flexible, at least as far as interaction phenomena are concerned.

Zoonotic potential of emerging paramyxoviruses: knowns and unknowns

PubMed Central

Thibault, Patricia A; Watkinson, Ruth E; Moreira-Soto, Andres; Drexler, Jan Felix; Lee, Benhur

2017-01-01

The risk of spillover of enzootic paramyxoviruses, and the susceptibility of recipient human and domestic animal populations, are defined by a broad collection of ecological and molecular factors that interact in ways that are not yet fully understood. Nipah and Hendra viruses were the first highly-lethal zoonotic paramyxoviruses discovered in modern times, but other paramyxoviruses from multiple genera are present in bats and other reservoirs that have unknown potential to spill over into humans. We outline our current understanding of paramyxovirus reservoir hosts and the ecological factors that may drive spillover, and we explore the molecular barriers to spillover that emergent paramyxoviruses may encounter. By outlining what is known about enzootic paramyxovirus receptor usage, mechanisms of innate immune evasion, and other host-specific interactions, we highlight the breadth of unexplored avenues that may be important in understanding paramyxovirus emergence. PMID:28433050

Nonlinear saturation of the slab ITG instability and zonal flow generation with fully kinetic ions

NASA Astrophysics Data System (ADS)

Miecnikowski, Matthew T.; Sturdevant, Benjamin J.; Chen, Yang; Parker, Scott E.

2018-05-01

Fully kinetic turbulence models are of interest for their potential to validate or replace gyrokinetic models in plasma regimes where the gyrokinetic expansion parameters are marginal. Here, we demonstrate fully kinetic ion capability by simulating the growth and nonlinear saturation of the ion-temperature-gradient instability in shearless slab geometry assuming adiabatic electrons and including zonal flow dynamics. The ion trajectories are integrated using the Lorentz force, and the cyclotron motion is fully resolved. Linear growth and nonlinear saturation characteristics show excellent agreement with analogous gyrokinetic simulations across a wide range of parameters. The fully kinetic simulation accurately reproduces the nonlinearly generated zonal flow. This work demonstrates nonlinear capability, resolution of weak gradient drive, and zonal flow physics, which are critical aspects of modeling plasma turbulence with full ion dynamics.

Parameter Optimization for Feature and Hit Generation in a General Unknown Screening Method-Proof of Concept Study Using a Design of Experiment Approach for a High Resolution Mass Spectrometry Procedure after Data Independent Acquisition.

PubMed

Elmiger, Marco P; Poetzsch, Michael; Steuer, Andrea E; Kraemer, Thomas

2018-03-06

High resolution mass spectrometry and modern data independent acquisition (DIA) methods enable the creation of general unknown screening (GUS) procedures. However, even when DIA is used, its potential is far from being exploited, because often, the untargeted acquisition is followed by a targeted search. Applying an actual GUS (including untargeted screening) produces an immense amount of data that must be dealt with. An optimization of the parameters regulating the feature detection and hit generation algorithms of the data processing software could significantly reduce the amount of unnecessary data and thereby the workload. Design of experiment (DoE) approaches allow a simultaneous optimization of multiple parameters. In a first step, parameters are evaluated (crucial or noncrucial). Second, crucial parameters are optimized. The aim in this study was to reduce the number of hits, without missing analytes. The obtained parameter settings from the optimization were compared to the standard settings by analyzing a test set of blood samples spiked with 22 relevant analytes as well as 62 authentic forensic cases. The optimization lead to a marked reduction of workload (12.3 to 1.1% and 3.8 to 1.1% hits for the test set and the authentic cases, respectively) while simultaneously increasing the identification rate (68.2 to 86.4% and 68.8 to 88.1%, respectively). This proof of concept study emphasizes the great potential of DoE approaches to master the data overload resulting from modern data independent acquisition methods used for general unknown screening procedures by optimizing software parameters.

Efficient uncertainty quantification in fully-integrated surface and subsurface hydrologic simulations

NASA Astrophysics Data System (ADS)

Miller, K. L.; Berg, S. J.; Davison, J. H.; Sudicky, E. A.; Forsyth, P. A.

2018-01-01

Although high performance computers and advanced numerical methods have made the application of fully-integrated surface and subsurface flow and transport models such as HydroGeoSphere common place, run times for large complex basin models can still be on the order of days to weeks, thus, limiting the usefulness of traditional workhorse algorithms for uncertainty quantification (UQ) such as Latin Hypercube simulation (LHS) or Monte Carlo simulation (MCS), which generally require thousands of simulations to achieve an acceptable level of accuracy. In this paper we investigate non-intrusive polynomial chaos for uncertainty quantification, which in contrast to random sampling methods (e.g., LHS and MCS), represents a model response of interest as a weighted sum of polynomials over the random inputs. Once a chaos expansion has been constructed, approximating the mean, covariance, probability density function, cumulative distribution function, and other common statistics as well as local and global sensitivity measures is straightforward and computationally inexpensive, thus making PCE an attractive UQ method for hydrologic models with long run times. Our polynomial chaos implementation was validated through comparison with analytical solutions as well as solutions obtained via LHS for simple numerical problems. It was then used to quantify parametric uncertainty in a series of numerical problems with increasing complexity, including a two-dimensional fully-saturated, steady flow and transient transport problem with six uncertain parameters and one quantity of interest; a one-dimensional variably-saturated column test involving transient flow and transport, four uncertain parameters, and two quantities of interest at 101 spatial locations and five different times each (1010 total); and a three-dimensional fully-integrated surface and subsurface flow and transport problem for a small test catchment involving seven uncertain parameters and three quantities of interest at

Bootstrap Standard Errors for Maximum Likelihood Ability Estimates When Item Parameters Are Unknown

ERIC Educational Resources Information Center

Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi

2014-01-01

When item parameter estimates are used to estimate the ability parameter in item response models, the standard error (SE) of the ability estimate must be corrected to reflect the error carried over from item calibration. For maximum likelihood (ML) ability estimates, a corrected asymptotic SE is available, but it requires a long test and the…

Design of a DNA chip for detection of unknown genetically modified organisms (GMOs).

PubMed

Nesvold, Håvard; Kristoffersen, Anja Bråthen; Holst-Jensen, Arne; Berdal, Knut G

2005-05-01

Unknown genetically modified organisms (GMOs) have not undergone a risk evaluation, and hence might pose a danger to health and environment. There are, today, no methods for detecting unknown GMOs. In this paper we propose a novel method intended as a first step in an approach for detecting unknown genetically modified (GM) material in a single plant. A model is designed where biological and combinatorial reduction rules are applied to a set of DNA chip probes containing all possible sequences of uniform length n, creating probes capable of detecting unknown GMOs. The model is theoretically tested for Arabidopsis thaliana Columbia, and the probabilities for detecting inserts and receiving false positives are assessed for various parameters for this organism. From a theoretical standpoint, the model looks very promising but should be tested further in the laboratory. The model and algorithms will be available upon request to the corresponding author.

Parameter identification of thermophilic anaerobic degradation of valerate.

PubMed

Flotats, Xavier; Ahring, Birgitte K; Angelidaki, Irini

2003-01-01

The considered mathematical model of the decomposition of valerate presents three unknown kinetic parameters, two unknown stoichiometric coefficients, and three unknown initial concentrations for biomass. Applying a structural identifiability study, we concluded that it is necessary to perform simultaneous batch experiments with different initial conditions for estimating these parameters. Four simultaneous batch experiments were conducted at 55 degrees C, characterized by four different initial acetate concentrations. Product inhibition of valerate degradation by acetate was considered. Practical identification was done optimizing the sum of the multiple determination coefficients for all measured state variables and for all experiments simultaneously. The estimated values of kinetic parameters and stoichiometric coefficients were characterized by the parameter correlation matrix, the confidence interval, and the student's t-test at 5% significance level with positive results except for the saturation constant, for which more experiments for improving its identifiability should be conducted. In this article, we discuss kinetic parameter estimation methods.

Allocating monitoring effort in the face of unknown unknowns

USGS Publications Warehouse

Wintle, B.A.; Runge, M.C.; Bekessy, S.A.

2010-01-01

There is a growing view that to make efficient use of resources, ecological monitoring should be hypothesis-driven and targeted to address specific management questions. 'Targeted' monitoring has been contrasted with other approaches in which a range of quantities are monitored in case they exhibit an alarming trend or provide ad hoc ecological insights. The second form of monitoring, described as surveillance, has been criticized because it does not usually aim to discern between competing hypotheses, and its benefits are harder to identify a priori. The alternative view is that the existence of surveillance data may enable rapid corroboration of emerging hypotheses or help to detect important 'unknown unknowns' that, if undetected, could lead to catastrophic outcomes or missed opportunities. We derive a model to evaluate and compare the efficiency of investments in surveillance and targeted monitoring. We find that a decision to invest in surveillance monitoring may be defensible if: (1) the surveillance design is more likely to discover or corroborate previously unknown phenomena than a targeted design and (2) the expected benefits (or avoided costs) arising from discovery are substantially higher than those arising from a well-planned targeted design. Our examination highlights the importance of being explicit about the objectives, costs and expected benefits of monitoring in a decision analytic framework. ?? 2010 Blackwell Publishing Ltd/CNRS.

Asymptotic Normality of the Maximum Pseudolikelihood Estimator for Fully Visible Boltzmann Machines.

PubMed

Nguyen, Hien D; Wood, Ian A

2016-04-01

Boltzmann machines (BMs) are a class of binary neural networks for which there have been numerous proposed methods of estimation. Recently, it has been shown that in the fully visible case of the BM, the method of maximum pseudolikelihood estimation (MPLE) results in parameter estimates, which are consistent in the probabilistic sense. In this brief, we investigate the properties of MPLE for the fully visible BMs further, and prove that MPLE also yields an asymptotically normal parameter estimator. These results can be used to construct confidence intervals and to test statistical hypotheses. These constructions provide a closed-form alternative to the current methods that require Monte Carlo simulation or resampling. We support our theoretical results by showing that the estimator behaves as expected in simulation studies.

Developing Probabilistic Safety Performance Margins for Unknown and Underappreciated Risks

NASA Technical Reports Server (NTRS)

Benjamin, Allan; Dezfuli, Homayoon; Everett, Chris

2015-01-01

Probabilistic safety requirements currently formulated or proposed for space systems, nuclear reactor systems, nuclear weapon systems, and other types of systems that have a low-probability potential for high-consequence accidents depend on showing that the probability of such accidents is below a specified safety threshold or goal. Verification of compliance depends heavily upon synthetic modeling techniques such as PRA. To determine whether or not a system meets its probabilistic requirements, it is necessary to consider whether there are significant risks that are not fully considered in the PRA either because they are not known at the time or because their importance is not fully understood. The ultimate objective is to establish a reasonable margin to account for the difference between known risks and actual risks in attempting to validate compliance with a probabilistic safety threshold or goal. In this paper, we examine data accumulated over the past 60 years from the space program, from nuclear reactor experience, from aircraft systems, and from human reliability experience to formulate guidelines for estimating probabilistic margins to account for risks that are initially unknown or underappreciated. The formulation includes a review of the safety literature to identify the principal causes of such risks.

A dynamical approach in exploring the unknown mass in the Solar system using pulsar timing arrays

NASA Astrophysics Data System (ADS)

Guo, Y. J.; Lee, K. J.; Caballero, R. N.

2018-04-01

The error in the Solar system ephemeris will lead to dipolar correlations in the residuals of pulsar timing array for widely separated pulsars. In this paper, we utilize such correlated signals, and construct a Bayesian data-analysis framework to detect the unknown mass in the Solar system and to measure the orbital parameters. The algorithm is designed to calculate the waveform of the induced pulsar-timing residuals due to the unmodelled objects following the Keplerian orbits in the Solar system. The algorithm incorporates a Bayesian-analysis suit used to simultaneously analyse the pulsar-timing data of multiple pulsars to search for coherent waveforms, evaluate the detection significance of unknown objects, and to measure their parameters. When the object is not detectable, our algorithm can be used to place upper limits on the mass. The algorithm is verified using simulated data sets, and cross-checked with analytical calculations. We also investigate the capability of future pulsar-timing-array experiments in detecting the unknown objects. We expect that the future pulsar-timing data can limit the unknown massive objects in the Solar system to be lighter than 10-11-10-12 M⊙, or measure the mass of Jovian system to a fractional precision of 10-8-10-9.

Metabolome Profiling of Partial and Fully Reprogrammed Induced Pluripotent Stem Cells.

PubMed

Park, Soon-Jung; Lee, Sang A; Prasain, Nutan; Bae, Daekyeong; Kang, Hyunsu; Ha, Taewon; Kim, Jong Soo; Hong, Ki-Sung; Mantel, Charlie; Moon, Sung-Hwan; Broxmeyer, Hal E; Lee, Man Ryul

2017-05-15

Acquisition of proper metabolomic fate is required to convert somatic cells toward fully reprogrammed pluripotent stem cells. The majority of induced pluripotent stem cells (iPSCs) are partially reprogrammed and have a transcriptome different from that of the pluripotent stem cells. The metabolomic profile and mitochondrial metabolic functions required to achieve full reprogramming of somatic cells to iPSC status have not yet been elucidated. Clarification of the metabolites underlying reprogramming mechanisms should enable further optimization to enhance the efficiency of obtaining fully reprogrammed iPSCs. In this study, we characterized the metabolites of human fully reprogrammed iPSCs, partially reprogrammed iPSCs, and embryonic stem cells (ESCs). Using capillary electrophoresis time-of-flight mass spectrometry-based metabolomics, we found that 89% of analyzed metabolites were similarly expressed in fully reprogrammed iPSCs and human ESCs (hESCs), whereas partially reprogrammed iPSCs shared only 74% similarly expressed metabolites with hESCs. Metabolomic profiling analysis suggested that converting mitochondrial respiration to glycolytic flux is critical for reprogramming of somatic cells into fully reprogrammed iPSCs. This characterization of metabolic reprogramming in iPSCs may enable the development of new reprogramming parameters for enhancing the generation of fully reprogrammed human iPSCs.

Education Through Exploration: Evaluating the Unknown

NASA Astrophysics Data System (ADS)

Anbar, A. D.

2015-12-01

Mastery of the peculiar and powerful practices of science is increasingly important for the average citizen. With the rise of the Internet, most of human knowledge is at our fingertips. As content becomes a commodity, success and survival aren't about who knows the most, but who is better able to explore the unknown, actively applying and extending knowledge through critical thinking and hypothesis-driven problem-solving. This applies to the economic livelihoods of individuals and to society at large as we grapple with climate change and other science-infused challenges. Unfortunately, science is too often taught as an encyclopedic collection of settled facts to be mastered rather than as a process of exploration that embraces curiosity, inquiry, testing, and communication to reduce uncertainty about the unknown. This problem is exacerbated by the continued prevalence of teacher-centric pedagogy, which promotes learning-from-authority and passive learning. The initial wave of massively open online courses (MOOCs) generally mimic this teaching style in virtual form. It is hypothesized that emerging digital teaching technologies can help address this challenge at Internet scale in "next generation" MOOCs and flipped classroom experiences. Interactive simulations, immersive virtual field trips, gamified elements, rapid adaptive feedback, intelligent tutoring systems, and personalized pathways, should motivate and enhance learning. Through lab-like projects and tutorials, students should be able to construct knowledge from interactive experiences, modeling the authentic practice of science while mastering complex concepts. Freed from lecturing, teaching staff should be available for direct and intense student-teacher interactions. These claims are difficult to evaluate with traditional assessment instruments, but digital technologies provide powerful new ways to evaluate student learning and learn from student behaviors. We will describe ongoing experiences with such

A learning-based semi-autonomous controller for robotic exploration of unknown disaster scenes while searching for victims.

PubMed

Doroodgar, Barzin; Liu, Yugang; Nejat, Goldie

2014-12-01

Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.

A meta-cognitive learning algorithm for a Fully Complex-valued Relaxation Network.

PubMed

Savitha, R; Suresh, S; Sundararajan, N

2012-08-01

This paper presents a meta-cognitive learning algorithm for a single hidden layer complex-valued neural network called "Meta-cognitive Fully Complex-valued Relaxation Network (McFCRN)". McFCRN has two components: a cognitive component and a meta-cognitive component. A Fully Complex-valued Relaxation Network (FCRN) with a fully complex-valued Gaussian like activation function (sech) in the hidden layer and an exponential activation function in the output layer forms the cognitive component. The meta-cognitive component contains a self-regulatory learning mechanism which controls the learning ability of FCRN by deciding what-to-learn, when-to-learn and how-to-learn from a sequence of training data. The input parameters of cognitive components are chosen randomly and the output parameters are estimated by minimizing a logarithmic error function. The problem of explicit minimization of magnitude and phase errors in the logarithmic error function is converted to system of linear equations and output parameters of FCRN are computed analytically. McFCRN starts with zero hidden neuron and builds the number of neurons required to approximate the target function. The meta-cognitive component selects the best learning strategy for FCRN to acquire the knowledge from training data and also adapts the learning strategies to implement best human learning components. Performance studies on a function approximation and real-valued classification problems show that proposed McFCRN performs better than the existing results reported in the literature. Copyright © 2012 Elsevier Ltd. All rights reserved.

A study of parameter identification

NASA Technical Reports Server (NTRS)

Herget, C. J.; Patterson, R. E., III

1978-01-01

A set of definitions for deterministic parameter identification ability were proposed. Deterministic parameter identificability properties are presented based on four system characteristics: direct parameter recoverability, properties of the system transfer function, properties of output distinguishability, and uniqueness properties of a quadratic cost functional. Stochastic parameter identifiability was defined in terms of the existence of an estimation sequence for the unknown parameters which is consistent in probability. Stochastic parameter identifiability properties are presented based on the following characteristics: convergence properties of the maximum likelihood estimate, properties of the joint probability density functions of the observations, and properties of the information matrix.

Optimization of In-Situ Shot-Peening-Assisted Cold Spraying Parameters for Full Corrosion Protection of Mg Alloy by Fully Dense Al-Based Alloy Coating

NASA Astrophysics Data System (ADS)

Wei, Ying-Kang; Luo, Xiao-Tao; Li, Cheng-Xin; Li, Chang-Jiu

2017-01-01

Magnesium-based alloys have excellent physical and mechanical properties for a lot of applications. However, due to high chemical reactivity, magnesium and its alloys are highly susceptible to corrosion. In this study, Al6061 coating was deposited on AZ31B magnesium by cold spray with a commercial Al6061 powder blended with large-sized stainless steel particles (in-situ shot-peening particles) using nitrogen gas. Microstructure and corrosion behavior of the sprayed coating was investigated as a function of shot-peening particle content in the feedstock. It is found that by introducing the in-situ tamping effect using shot-peening (SP) particles, the plastic deformation of deposited particles is significantly enhanced, thereby resulting in a fully dense Al6061 coating. SEM observations reveal that no SP particle is deposited into Al6061 coating at the optimization spraying parameters. Porosity of the coating significantly decreases from 10.7 to 0.4% as the SP particle content increases from 20 to 60 vol.%. The electrochemical corrosion experiments reveal that this novel in-situ SP-assisted cold spraying is effective to deposit fully dense Al6061 coating through which aqueous solution is not permeable and thus can provide exceptional protection of the magnesium-based materials from corrosion.

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

DOE PAGES

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.; ...

2018-01-17

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

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

Boiteau, Rene M.; Hoyt, David W.; Nicora, Carrie D.

Here, we introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS 2), and NMR in a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS 2 approach is well suited for discovery ofmore » new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.« less

Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction

PubMed Central

Hoyt, David W.; Nicora, Carrie D.; Kinmonth-Schultz, Hannah A.; Ward, Joy K.

2018-01-01

We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS2), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana. The NMR/MS2 approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases. PMID:29342073

Bonabeau model on a fully connected graph

NASA Astrophysics Data System (ADS)

Malarz, K.; Stauffer, D.; Kułakowski, K.

2006-03-01

Numerical simulations are reported on the Bonabeau model on a fully connected graph, where spatial degrees of freedom are absent. The control parameter is the memory factor f. The phase transition is observed at the dispersion of the agents power hi. The critical value fC shows a hysteretic behavior with respect to the initial distribution of hi. fC decreases with the system size; this decrease can be compensated by a greater number of fights between a global reduction of the distribution width of hi. The latter step is equivalent to a partial forgetting.

The fully differential top decay distribution

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

Aguilar-Saavedra, J. A.; Boudreau, J.; Escobar, C.

We write down the four-dimensional fully differential decay distribution for the top quark decay t → Wb → ℓνb. We discuss how its eight physical parameters can be measured, either with a global fit or with the use of selected one-dimensional distributions and asymmetries. We give expressions for the top decay amplitudes for a general tbW interaction, and show how the untangled measurement of the two components of the fraction of longitudinal W bosons – those with b quark helicities of 1/2 and –1/2, respectively – could improve the precision of a global fit to the tbW vertex.

The fully differential top decay distribution

DOE PAGES

Aguilar-Saavedra, J. A.; Boudreau, J.; Escobar, C.; ...

2017-03-29

We write down the four-dimensional fully differential decay distribution for the top quark decay t → Wb → ℓνb. We discuss how its eight physical parameters can be measured, either with a global fit or with the use of selected one-dimensional distributions and asymmetries. We give expressions for the top decay amplitudes for a general tbW interaction, and show how the untangled measurement of the two components of the fraction of longitudinal W bosons – those with b quark helicities of 1/2 and –1/2, respectively – could improve the precision of a global fit to the tbW vertex.

Performance Analysis for Channel Estimation With 1-Bit ADC and Unknown Quantization Threshold

NASA Astrophysics Data System (ADS)

Stein, Manuel S.; Bar, Shahar; Nossek, Josef A.; Tabrikian, Joseph

2018-05-01

In this work, the problem of signal parameter estimation from measurements acquired by a low-complexity analog-to-digital converter (ADC) with $1$-bit output resolution and an unknown quantization threshold is considered. Single-comparator ADCs are energy-efficient and can be operated at ultra-high sampling rates. For analysis of such systems, a fixed and known quantization threshold is usually assumed. In the symmetric case, i.e., zero hard-limiting offset, it is known that in the low signal-to-noise ratio (SNR) regime the signal processing performance degrades moderately by ${2}/{\\pi}$ ($-1.96$ dB) when comparing to an ideal $\\infty$-bit converter. Due to hardware imperfections, low-complexity $1$-bit ADCs will in practice exhibit an unknown threshold different from zero. Therefore, we study the accuracy which can be obtained with receive data processed by a hard-limiter with unknown quantization level by using asymptotically optimal channel estimation algorithms. To characterize the estimation performance of these nonlinear algorithms, we employ analytic error expressions for different setups while modeling the offset as a nuisance parameter. In the low SNR regime, we establish the necessary condition for a vanishing loss due to missing offset knowledge at the receiver. As an application, we consider the estimation of single-input single-output wireless channels with inter-symbol interference and validate our analysis by comparing the analytic and experimental performance of the studied estimation algorithms. Finally, we comment on the extension to multiple-input multiple-output channel models.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras.

PubMed

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-08-30

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

PubMed Central

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-01-01

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme. PMID:27589748

Fully-Coupled Dynamical Jitter Modeling of Momentum Exchange Devices

NASA Astrophysics Data System (ADS)

Alcorn, John

A primary source of spacecraft jitter is due to mass imbalances within momentum exchange devices (MEDs) used for fine pointing, such as reaction wheels (RWs) and variable-speed control moment gyroscopes (VSCMGs). Although these effects are often characterized through experimentation in order to validate pointing stability requirements, it is of interest to include jitter in a computer simulation of the spacecraft in the early stages of spacecraft development. An estimate of jitter amplitude may be found by modeling MED imbalance torques as external disturbance forces and torques on the spacecraft. In this case, MED mass imbalances are lumped into static and dynamic imbalance parameters, allowing jitter force and torque to be simply proportional to wheel speed squared. A physically realistic dynamic model may be obtained by defining mass imbalances in terms of a wheel center of mass location and inertia tensor. The fully-coupled dynamic model allows for momentum and energy validation of the system. This is often critical when modeling additional complex dynamical behavior such as flexible dynamics and fuel slosh. Furthermore, it is necessary to use the fully-coupled model in instances where the relative mass properties of the spacecraft with respect to the RWs cause the simplified jitter model to be inaccurate. This thesis presents a generalized approach to MED imbalance modeling of a rigid spacecraft hub with N RWs or VSCMGs. A discussion is included to convert from manufacturer specifications of RW imbalances to the parameters introduced within each model. Implementations of the fully-coupled RW and VSCMG models derived within this thesis are released open-source as part of the Basilisk astrodynamics software.

Mean-square state and parameter estimation for stochastic linear systems with Gaussian and Poisson noises

NASA Astrophysics Data System (ADS)

Basin, M.; Maldonado, J. J.; Zendejo, O.

2016-07-01

This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.

Estimation of nonlinear pilot model parameters including time delay.

NASA Technical Reports Server (NTRS)

Schiess, J. R.; Roland, V. R.; Wells, W. R.

1972-01-01

Investigation of the feasibility of using a Kalman filter estimator for the identification of unknown parameters in nonlinear dynamic systems with a time delay. The problem considered is the application of estimation theory to determine the parameters of a family of pilot models containing delayed states. In particular, the pilot-plant dynamics are described by differential-difference equations of the retarded type. The pilot delay, included as one of the unknown parameters to be determined, is kept in pure form as opposed to the Pade approximations generally used for these systems. Problem areas associated with processing real pilot response data are included in the discussion.

Fully Coupled Aero-Thermochemical-Elastic Simulations of an Eroding Graphite Nozzle

NASA Technical Reports Server (NTRS)

Blades, E. L.; Reveles, N. D.; Nucci, M.; Maclean, M.

2017-01-01

A multiphysics simulation capability has been developed that incorporates mutual interactions between aerodynamics, structural response from aero/thermal loading, ablation/pyrolysis, heating, and surface-to-surface radiation to perform high-fidelity, fully coupled aerothermoelastic ablation simulations, which to date had been unattainable. The multiphysics framework couples CHAR (a 3-D implicit charring ablator solver), Loci/CHEM (a computational fluid dynamics solver for high-speed chemically reacting flows), and Abaqus (a nonlinear structural dynamics solver) to create a fully coupled aerothermoelastic charring ablative solver. The solvers are tightly coupled in a fully integrated fashion to resolve the effects of the ablation pyrolysis and charring process and chemistry products upon the flow field, the changes in surface geometry due to recession upon the flow field, and thermal-structural analysis of the body from the induced aerodynamic heating from the flow field. The multiphysics framework was successfully demonstrated on a solid rocket motor graphite nozzle erosion application. Comparisons were made with available experimental data that measured the throat erosion during the motor firing. The erosion data is well characterized, as the test rig was equipped with a windowed nozzle section for real-time X-ray radiography diagnostics of the instantaneous throat variations for deducing the instantaneous erosion rates. The nozzle initially undergoes a nozzle contraction due to thermal expansion before ablation effects are able to widen the throat. A series of parameters studies were conducted using the coupled simulation capability to determine the sensitivity of the nozzle erosion to different parameters. The parameter studies included the shape of the nozzle throat (flat versus rounded), the material properties, the effect of the choice of turbulence model, and the inclusion or exclusion of the mechanical thermal expansion. Overall, the predicted results match

Quantum Optimization of Fully Connected Spin Glasses

NASA Astrophysics Data System (ADS)

Venturelli, Davide; Mandrà, Salvatore; Knysh, Sergey; O'Gorman, Bryan; Biswas, Rupak; Smelyanskiy, Vadim

2015-07-01

Many NP-hard problems can be seen as the task of finding a ground state of a disordered highly connected Ising spin glass. If solutions are sought by means of quantum annealing, it is often necessary to represent those graphs in the annealer's hardware by means of the graph-minor embedding technique, generating a final Hamiltonian consisting of coupled chains of ferromagnetically bound spins, whose binding energy is a free parameter. In order to investigate the effect of embedding on problems of interest, the fully connected Sherrington-Kirkpatrick model with random ±1 couplings is programmed on the D-Wave TwoTM annealer using up to 270 qubits interacting on a Chimera-type graph. We present the best embedding prescriptions for encoding the Sherrington-Kirkpatrick problem in the Chimera graph. The results indicate that the optimal choice of embedding parameters could be associated with the emergence of the spin-glass phase of the embedded problem, whose presence was previously uncertain. This optimal parameter setting allows the performance of the quantum annealer to compete with (and potentially outperform, in the absence of analog control errors) optimized simulated annealing algorithms.

A fully automated cell segmentation and morphometric parameter system for quantifying corneal endothelial cell morphology.

PubMed

Al-Fahdawi, Shumoos; Qahwaji, Rami; Al-Waisy, Alaa S; Ipson, Stanley; Ferdousi, Maryam; Malik, Rayaz A; Brahma, Arun

2018-07-01

Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction. We developed and applied a fully-automated and real-time system, termed the Corneal Endothelium Analysis System (CEAS) for the segmentation and computation of endothelial cells in images of the human cornea obtained by in vivo corneal confocal microscopy. First, a Fast Fourier Transform (FFT) Band-pass filter is applied to reduce noise and enhance the image quality to make the cells more visible. Secondly, endothelial cell boundaries are detected using watershed transformations and Voronoi tessellations to accurately quantify the morphological parameters of the human corneal endothelial cells. The performance of the automated segmentation system was tested against manually traced ground-truth images based on a database consisting of 40 corneal confocal endothelial cell images in terms of segmentation accuracy and obtained clinical features. In addition, the robustness and efficiency of the proposed CEAS system were compared with manually obtained cell densities using a separate database of 40 images from controls (n = 11), obese subjects (n = 16) and patients with diabetes (n = 13). The Pearson correlation coefficient between automated and manual endothelial cell densities is 0.9 (p < 0.0001) and a Bland-Altman plot shows that 95% of the data are between the 2SD agreement lines. We demonstrate the effectiveness and robustness of the CEAS system, and the possibility of utilizing it in a real world clinical setting to

Methods to examine reproductive biology in free-ranging, fully-marine mammals.

PubMed

Lanyon, Janet M; Burgess, Elizabeth A

2014-01-01

Historical overexploitation of marine mammals, combined with present-day pressures, has resulted in severely depleted populations, with many species listed as threatened or endangered. Understanding breeding patterns of threatened marine mammals is crucial to assessing population viability, potential recovery and conservation actions. However, determining reproductive parameters of wild fully-marine mammals (cetaceans and sirenians) is challenging due to their wide distributions, high mobility, inaccessible habitats, cryptic lifestyles and in many cases, large body size and intractability. Consequently, reproductive biologists employ an innovative suite of methods to collect useful information from these species. This chapter reviews historic, recent and state-of-the-art methods to examine diverse aspects of reproduction in fully-aquatic mammals.

A semi-phenomenological model to predict the acoustic behavior of fully and partially reticulated polyurethane foams

NASA Astrophysics Data System (ADS)

Doutres, Olivier; Atalla, Noureddine; Dong, Kevin

2013-02-01

This paper proposes simple semi-phenomenological models to predict the sound absorption efficiency of highly porous polyurethane foams from microstructure characterization. In a previous paper [J. Appl. Phys. 110, 064901 (2011)], the authors presented a 3-parameter semi-phenomenological model linking the microstructure properties of fully and partially reticulated isotropic polyurethane foams (i.e., strut length l, strut thickness t, and reticulation rate Rw) to the macroscopic non-acoustic parameters involved in the classical Johnson-Champoux-Allard model (i.e., porosity ϕ, airflow resistivity σ, tortuosity α∝, viscous Λ, and thermal Λ' characteristic lengths). The model was based on existing scaling laws, validated for fully reticulated polyurethane foams, and improved using both geometrical and empirical approaches to account for the presence of membrane closing the pores. This 3-parameter model is applied to six polyurethane foams in this paper and is found highly sensitive to the microstructure characterization; particularly to strut's dimensions. A simplified micro-/macro model is then presented. It is based on the cell size Cs and reticulation rate Rw only, assuming that the geometric ratio between strut length l and strut thickness t is known. This simplified model, called the 2-parameter model, considerably simplifies the microstructure characterization procedure. A comparison of the two proposed semi-phenomenological models is presented using six polyurethane foams being either fully or partially reticulated, isotropic or anisotropic. It is shown that the 2-parameter model is less sensitive to measurement uncertainties compared to the original model and allows a better estimation of polyurethane foams sound absorption behavior.

Known knowns, known unknowns and unknown unknowns in prokaryotic transposition.

PubMed

Siguier, Patricia; Gourbeyre, Edith; Chandler, Michael

2017-08-01

Although the phenomenon of transposition has been known for over 60 years, its overarching importance in modifying and streamlining genomes took some time to recognize. In spite of a robust understanding of transposition of some TE, there remain a number of important TE groups with potential high genome impact and unknown transposition mechanisms and yet others, only recently identified by bioinformatics, yet to be formally confirmed as mobile. Here, we point to some areas of limited understanding concerning well established important TE groups with DDE Tpases, to address central gaps in our knowledge of characterised Tn with other types of Tpases and finally, to highlight new potentially mobile DNA species. It is not exhaustive. Examples have been chosen to provide encouragement in the continued exploration of the considerable prokaryotic mobilome especially in light of the current threat to public health posed by the spread of multiple Ab R . Copyright © 2017 Elsevier Ltd. All rights reserved.

The classical equation of state of fully ionized plasmas

NASA Astrophysics Data System (ADS)

Eisa, Dalia Ahmed

2011-03-01

The aim of this paper is to calculate the analytical form of the equation of state until the third virial coefficient of a classical system interacting via an effective potential of fully Ionized Plasmas. The excess osmotic pressure is represented in the forms of a convergent series expansions in terms of the plasma Parameter μ _{ab} = {{{e_a e_b χ } over {DKT}}}, where χ2 is the square of the inverse Debye radius. We consider only the thermal equilibrium plasma.

Exact closed-form solutions of a fully nonlinear asymptotic two-fluid model

NASA Astrophysics Data System (ADS)

Cheviakov, Alexei F.

2018-05-01

A fully nonlinear model of Choi and Camassa (1999) describing one-dimensional incompressible dynamics of two non-mixing fluids in a horizontal channel, under a shallow water approximation, is considered. An equivalence transformation is presented, leading to a special dimensionless form of the system, involving a single dimensionless constant physical parameter, as opposed to five parameters present in the original model. A first-order dimensionless ordinary differential equation describing traveling wave solutions is analyzed. Several multi-parameter families of physically meaningful exact closed-form solutions of the two-fluid model are derived, corresponding to periodic, solitary, and kink-type bidirectional traveling waves; specific examples are given, and properties of the exact solutions are analyzed.

Optimal SVM parameter selection for non-separable and unbalanced datasets.

PubMed

Jiang, Peng; Missoum, Samy; Chen, Zhao

2014-10-01

This article presents a study of three validation metrics used for the selection of optimal parameters of a support vector machine (SVM) classifier in the case of non-separable and unbalanced datasets. This situation is often encountered when the data is obtained experimentally or clinically. The three metrics selected in this work are the area under the ROC curve (AUC), accuracy, and balanced accuracy. These validation metrics are tested using computational data only, which enables the creation of fully separable sets of data. This way, non-separable datasets, representative of a real-world problem, can be created by projection onto a lower dimensional sub-space. The knowledge of the separable dataset, unknown in real-world problems, provides a reference to compare the three validation metrics using a quantity referred to as the "weighted likelihood". As an application example, the study investigates a classification model for hip fracture prediction. The data is obtained from a parameterized finite element model of a femur. The performance of the various validation metrics is studied for several levels of separability, ratios of unbalance, and training set sizes.

Carcinoma of Unknown Primary—Patient Version

Cancer.gov

Carcinoma of unknown primary (CUP) occurs when cancer cells have spread in the body and formed metastatic tumors but the site of the primary cancer is not known. There are a number of reasons why the primary cancer may not be found. Start here to find treatment information for carcinoma of unknown primary.

Anelastic Models of Fully-Convective Stars: Differential Rotation, Meridional Circulation and Residual Entropy

NASA Astrophysics Data System (ADS)

Sainsbury-Martinez, Felix; Browning, Matthew; Miesch, Mark; Featherstone, Nicholas A.

2018-01-01

Low-Mass stars are typically fully convective, and as such their dynamics may differ significantly from sun-like stars. Here we present a series of 3D anelastic HD and MHD simulations of fully convective stars, designed to investigate how the meridional circulation, the differential rotation, and residual entropy are affected by both varying stellar parameters, such as the luminosity or the rotation rate, and by the presence of a magnetic field. We also investigate, more specifically, a theoretical model in which isorotation contours and residual entropy (σ‧ = σ ‑ σ(r)) are intrinsically linked via the thermal wind equation (as proposed in the Solar context by Balbus in 2009). We have selected our simulation parameters in such as way as to span the transition between Solar-like differential rotation (fast equator + slow poles) and ‘anti-Solar’ differential rotation (slow equator + fast poles), as characterised by the convective Rossby number and △Ω. We illustrate the transition from single-celled to multi-celled MC profiles, and from positive to negative latitudinal entropy gradients. We show that an extrapolation involving both TWB and the σ‧/Ω link provides a reasonable estimate for the interior profile of our fully convective stars. Finally, we also present a selection of MHD simulations which exhibit an almost unsuppressed differential rotation profile, with energy balances remaining dominated by kinetic components.

Initial clinical trial of a closed loop, fully automatic intra-aortic balloon pump.

PubMed

Kantrowitz, A; Freed, P S; Cardona, R R; Gage, K; Marinescu, G N; Westveld, A H; Litch, B; Suzuki, A; Hayakawa, H; Takano, T

1992-01-01

A new generation, closed loop, fully automatic intraaortic balloon pump (CL-IABP) system continuously optimizes diastolic augmentation by adjusting balloon pump parameters beat by beat without operator intervention. In dogs in sinus rhythm and with experimentally induced arrhythmias, the new CL-IABP system provided safe, effective augmentation. To investigate the system's suitability for clinical use, 10 patients meeting standard indications for IABP were studied. The patients were pumped by the fully automatic IABP system for an average of 20 hr (range, 1-48 hr). At start-up, the system optimized pumping parameters within 7-20 sec. Evaluation of 186 recordings made at hourly intervals showed that inflation began within 20 msec of the dicrotic notch 99% of the time. In 100% of the recordings, deflation straddled the first half of ventricular ejection. Peak pressure across the balloon membrane averaged 55 mmHg and, in no case, exceeded 100 mmHg. Examination of the data showed that as soon as the system was actuated it provided consistently beneficial diastolic augmentation without any further operator intervention. Eight patients improved and two died (one of irreversible cardiogenic shock and one of ischemic cardiomyopathy). No complications were attributable to the investigational aspects of the system. A fully automated IABP is feasible in the clinical setting, and it may have advantages relative to current generation IABP systems.

A novel fully automatic scheme for fiducial marker-based alignment in electron tomography.

PubMed

Han, Renmin; Wang, Liansan; Liu, Zhiyong; Sun, Fei; Zhang, Fa

2015-12-01

Although the topic of fiducial marker-based alignment in electron tomography (ET) has been widely discussed for decades, alignment without human intervention remains a difficult problem. Specifically, the emergence of subtomogram averaging has increased the demand for batch processing during tomographic reconstruction; fully automatic fiducial marker-based alignment is the main technique in this process. However, the lack of an accurate method for detecting and tracking fiducial markers precludes fully automatic alignment. In this paper, we present a novel, fully automatic alignment scheme for ET. Our scheme has two main contributions: First, we present a series of algorithms to ensure a high recognition rate and precise localization during the detection of fiducial markers. Our proposed solution reduces fiducial marker detection to a sampling and classification problem and further introduces an algorithm to solve the parameter dependence of marker diameter and marker number. Second, we propose a novel algorithm to solve the tracking of fiducial markers by reducing the tracking problem to an incomplete point set registration problem. Because a global optimization of a point set registration occurs, the result of our tracking is independent of the initial image position in the tilt series, allowing for the robust tracking of fiducial markers without pre-alignment. The experimental results indicate that our method can achieve an accurate tracking, almost identical to the current best one in IMOD with half automatic scheme. Furthermore, our scheme is fully automatic, depends on fewer parameters (only requires a gross value of the marker diameter) and does not require any manual interaction, providing the possibility of automatic batch processing of electron tomographic reconstruction. Copyright © 2015 Elsevier Inc. All rights reserved.

A fully Sinc-Galerkin method for Euler-Bernoulli beam models

NASA Technical Reports Server (NTRS)

Smith, R. C.; Bowers, K. L.; Lund, J.

1990-01-01

A fully Sinc-Galerkin method in both space and time is presented for fourth-order time-dependent partial differential equations with fixed and cantilever boundary conditions. The Sinc discretizations for the second-order temporal problem and the fourth-order spatial problems are presented. Alternate formulations for variable parameter fourth-order problems are given which prove to be especially useful when applying the forward techniques to parameter recovery problems. The discrete system which corresponds to the time-dependent partial differential equations of interest are then formulated. Computational issues are discussed and a robust and efficient algorithm for solving the resulting matrix system is outlined. Numerical results which highlight the method are given for problems with both analytic and singular solutions as well as fixed and cantilever boundary conditions.

Dynamic parameter identification of robot arms with servo-controlled electrical motors

NASA Astrophysics Data System (ADS)

Jiang, Zhao-Hui; Senda, Hiroshi

2005-12-01

This paper addresses the issue of dynamic parameter identification of the robot manipulator with servo-controlled electrical motors. An assumption is made that all kinematical parameters, such as link lengths, are known, and only dynamic parameters containing mass, moment of inertia, and their functions need to be identified. First, we derive dynamics of the robot arm with a linear form of the unknown dynamic parameters by taking dynamic characteristics of the motor and servo unit into consideration. Then, we implement the parameter identification approach to identify the unknown parameters with respect to individual link separately. A pseudo-inverse matrix is used for formulation of the parameter identification. The optimal solution is guaranteed in a sense of least-squares of the mean errors. A Direct Drive (DD) SCARA type industrial robot arm AdeptOne is used as an application example of the parameter identification. Simulations and experiments for both open loop and close loop controls are carried out. Comparison of the results confirms the correctness and usefulness of the parameter identification and the derived dynamic model.

Existence conditions for unknown input functional observers

NASA Astrophysics Data System (ADS)

Fernando, T.; MacDougall, S.; Sreeram, V.; Trinh, H.

2013-01-01

This article presents necessary and sufficient conditions for the existence and design of an unknown input Functional observer. The existence of the observer can be verified by computing a nullspace of a known matrix and testing some matrix rank conditions. The existence of the observer does not require the satisfaction of the observer matching condition (i.e. Equation (16) in Hou and Muller 1992, 'Design of Observers for Linear Systems with Unknown Inputs', IEEE Transactions on Automatic Control, 37, 871-875), is not limited to estimating scalar functionals and allows for arbitrary pole placement. The proposed observer always exists when a state observer exists for the unknown input system, and furthermore, the proposed observer can exist even in some instances when an unknown input state observer does not exist.

Nonlinear adaptive control system design with asymptotically stable parameter estimation error

NASA Astrophysics Data System (ADS)

Mishkov, Rumen; Darmonski, Stanislav

2018-01-01

The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

Back analysis of geomechanical parameters in underground engineering using artificial bee colony.

PubMed

Zhu, Changxing; Zhao, Hongbo; Zhao, Ming

2014-01-01

Accurate geomechanical parameters are critical in tunneling excavation, design, and supporting. In this paper, a displacements back analysis based on artificial bee colony (ABC) algorithm is proposed to identify geomechanical parameters from monitored displacements. ABC was used as global optimal algorithm to search the unknown geomechanical parameters for the problem with analytical solution. To the problem without analytical solution, optimal back analysis is time-consuming, and least square support vector machine (LSSVM) was used to build the relationship between unknown geomechanical parameters and displacement and improve the efficiency of back analysis. The proposed method was applied to a tunnel with analytical solution and a tunnel without analytical solution. The results show the proposed method is feasible.

Nonlinear robust controller design for multi-robot systems with unknown payloads

NASA Technical Reports Server (NTRS)

Song, Y. D.; Anderson, J. N.; Homaifar, A.; Lai, H. Y.

1992-01-01

This work is concerned with the control problem of a multi-robot system handling a payload with unknown mass properties. Force constraints at the grasp points are considered. Robust control schemes are proposed that cope with the model uncertainty and achieve asymptotic path tracking. To deal with the force constraints, a strategy for optimally sharing the task is suggested. This strategy basically consists of two steps. The first detects the robots that need help and the second arranges that help. It is shown that the overall system is not only robust to uncertain payload parameters, but also satisfies the force constraints.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

A fully resolved consensus between fully resolved phylogenetic trees.

PubMed

Quitzau, José Augusto Amgarten; Meidanis, João

2006-03-31

Nowadays, there are many phylogeny reconstruction methods, each with advantages and disadvantages. We explored the advantages of each method, putting together the common parts of trees constructed by several methods, by means of a consensus computation. A number of phylogenetic consensus methods are already known. Unfortunately, there is also a taboo concerning consensus methods, because most biologists see them mainly as comparators and not as phylogenetic tree constructors. We challenged this taboo by defining a consensus method that builds a fully resolved phylogenetic tree based on the most common parts of fully resolved trees in a given collection. We also generated results showing that this consensus is in a way a kind of "median" of the input trees; as such it can be closer to the correct tree in many situations.

Online fully automated three-dimensional surface reconstruction of unknown objects

NASA Astrophysics Data System (ADS)

Khalfaoui, Souhaiel; Aigueperse, Antoine; Fougerolle, Yohan; Seulin, Ralph; Fofi, David

2015-04-01

This paper presents a novel scheme for automatic and intelligent 3D digitization using robotic cells. The advantage of our procedure is that it is generic since it is not performed for a specific scanning technology. Moreover, it is not dependent on the methods used to perform the tasks associated with each elementary process. The comparison of results between manual and automatic scanning of complex objects shows that our digitization strategy is very efficient and faster than trained experts. The 3D models of the different objects are obtained with a strongly reduced number of acquisitions while moving efficiently the ranging device.

Passive Fully Polarimetric W-Band Millimeter-Wave Imaging

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

Bernacki, Bruce E.; Kelly, James F.; Sheen, David M.

2012-04-01

We present the theory, design, and experimental results obtained from a scanning passive W-band fully polarimetric imager. Passive millimeter-wave imaging offers persistent day/nighttime imaging and the ability to penetrate dust, clouds and other obscurants, including clothing and dry soil. The single-pixel scanning imager includes both far-field and near-field fore-optics for investigation of polarization phenomena. Using both fore-optics, a variety of scenes including natural and man-made objects was imaged and these results are presented showing the utility of polarimetric imaging for anomaly detection. Analysis includes conventional Stokes-parameter based approaches as well as multivariate image analysis methods.

A highly precise frequency-based method for estimating the tension of an inclined cable with unknown boundary conditions

NASA Astrophysics Data System (ADS)

Ma, Lin

2017-11-01

This paper develops a method for precisely determining the tension of an inclined cable with unknown boundary conditions. First, the nonlinear motion equation of an inclined cable is derived, and a numerical model of the motion of the cable is proposed using the finite difference method. The proposed numerical model includes the sag-extensibility, flexural stiffness, inclination angle and rotational stiffness at two ends of the cable. Second, the influence of the dynamic parameters of the cable on its frequencies is discussed in detail, and a method for precisely determining the tension of an inclined cable is proposed based on the derivatives of the eigenvalues of the matrices. Finally, a multiparameter identification method is developed that can simultaneously identify multiple parameters, including the rotational stiffness at two ends. This scheme is applicable to inclined cables with varying sag, varying flexural stiffness and unknown boundary conditions. Numerical examples indicate that the method provides good precision. Because the parameters of cables other than tension (e.g., the flexural stiffness and rotational stiffness at the ends) are not accurately known in practical engineering, the multiparameter identification method could further improve the accuracy of cable tension measurements.

76 FR 35086 - Proposed Information Collection (Fully Developed Claim (Fully Developed Claims-Applications for...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-15

... DEPARTMENT OF VETERANS AFFAIRS [OMB Control No. 2900-0747] Proposed Information Collection (Fully Developed Claim (Fully Developed Claims--Applications for Compensation, Pension, DIC, Death Pension, and/or... Claims--Applications for Compensation, Pension, DIC, Death Pension, and/or Accrued Benefits, VA Forms 21...

Discriminative parameter estimation for random walks segmentation.

PubMed

Baudin, Pierre-Yves; Goodman, Danny; Kumrnar, Puneet; Azzabou, Noura; Carlier, Pierre G; Paragios, Nikos; Kumar, M Pawan

2013-01-01

The Random Walks (RW) algorithm is one of the most efficient and easy-to-use probabilistic segmentation methods. By combining contrast terms with prior terms, it provides accurate segmentations of medical images in a fully automated manner. However, one of the main drawbacks of using the RW algorithm is that its parameters have to be hand-tuned. we propose a novel discriminative learning framework that estimates the parameters using a training dataset. The main challenge we face is that the training samples are not fully supervised. Specifically, they provide a hard segmentation of the images, instead of a probabilistic segmentation. We overcome this challenge by treating the optimal probabilistic segmentation that is compatible with the given hard segmentation as a latent variable. This allows us to employ the latent support vector machine formulation for parameter estimation. We show that our approach significantly outperforms the baseline methods on a challenging dataset consisting of real clinical 3D MRI volumes of skeletal muscles.

Multi-objective optimization in quantum parameter estimation

NASA Astrophysics Data System (ADS)

Gong, BeiLi; Cui, Wei

2018-04-01

We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.

A novel sensitivity-based method for damage detection of structures under unknown periodic excitations

NASA Astrophysics Data System (ADS)

Naseralavi, S. S.; Salajegheh, E.; Fadaee, M. J.; Salajegheh, J.

2014-06-01

This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.

Ensemble-Based Parameter Estimation in a Coupled General Circulation Model

DOE PAGES

Liu, Y.; Liu, Z.; Zhang, S.; ...

2014-09-10

Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less

Distributed Synchronization Control of Multiagent Systems With Unknown Nonlinearities.

PubMed

Su, Shize; Lin, Zongli; Garcia, Alfredo

2016-01-01

This paper revisits the distributed adaptive control problem for synchronization of multiagent systems where the dynamics of the agents are nonlinear, nonidentical, unknown, and subject to external disturbances. Two communication topologies, represented, respectively, by a fixed strongly-connected directed graph and by a switching connected undirected graph, are considered. Under both of these communication topologies, we use distributed neural networks to approximate the uncertain dynamics. Decentralized adaptive control protocols are then constructed to solve the cooperative tracker problem, the problem of synchronization of all follower agents to a leader agent. In particular, we show that, under the proposed decentralized control protocols, the synchronization errors are ultimately bounded, and their ultimate bounds can be reduced arbitrarily by choosing the control parameter appropriately. Simulation study verifies the effectiveness of our proposed protocols.

Measurement-based perturbation theory and differential equation parameter estimation with applications to satellite gravimetry

NASA Astrophysics Data System (ADS)

Xu, Peiliang

2018-06-01

The numerical integration method has been routinely used by major institutions worldwide, for example, NASA Goddard Space Flight Center and German Research Center for Geosciences (GFZ), to produce global gravitational models from satellite tracking measurements of CHAMP and/or GRACE types. Such Earth's gravitational products have found widest possible multidisciplinary applications in Earth Sciences. The method is essentially implemented by solving the differential equations of the partial derivatives of the orbit of a satellite with respect to the unknown harmonic coefficients under the conditions of zero initial values. From the mathematical and statistical point of view, satellite gravimetry from satellite tracking is essentially the problem of estimating unknown parameters in the Newton's nonlinear differential equations from satellite tracking measurements. We prove that zero initial values for the partial derivatives are incorrect mathematically and not permitted physically. The numerical integration method, as currently implemented and used in mathematics and statistics, chemistry and physics, and satellite gravimetry, is groundless, mathematically and physically. Given the Newton's nonlinear governing differential equations of satellite motion with unknown equation parameters and unknown initial conditions, we develop three methods to derive new local solutions around a nominal reference orbit, which are linked to measurements to estimate the unknown corrections to approximate values of the unknown parameters and the unknown initial conditions. Bearing in mind that satellite orbits can now be tracked almost continuously at unprecedented accuracy, we propose the measurement-based perturbation theory and derive global uniformly convergent solutions to the Newton's nonlinear governing differential equations of satellite motion for the next generation of global gravitational models. Since the solutions are global uniformly convergent, theoretically speaking

Carcinoma of Unknown Primary—Health Professional Version

Cancer.gov

Carcinoma of unknown primary (CUP) is a rare disease in which malignant cells are found in the body but the site of the primary cancer is not known. Most CUPs are adenocarcinomas, or undifferentiated tumors. Find evidence-based information on the treatment for carcinoma of unknown primary.

37 CFR 260.7 - Unknown copyright owners.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Unknown copyright owners. 260.7 Section 260.7 Patents, Trademarks, and Copyrights U.S. COPYRIGHT OFFICE, LIBRARY OF CONGRESS... SERVICES' DIGITAL TRANSMISSIONS OF SOUND RECORDINGS AND MAKING OF EPHEMERAL PHONORECORDS § 260.7 Unknown...

High-throughput, fully-automated volumetry for prediction of MMSE and CDR decline in mild cognitive impairment

PubMed Central

Kovacevic, Sanja; Rafii, Michael S.; Brewer, James B.

2008-01-01

Medial temporal lobe (MTL) atrophy is associated with increased risk for conversion to Alzheimer's disease (AD), but manual tracing techniques and even semi-automated techniques for volumetric assessment are not practical in the clinical setting. In addition, most studies that examined MTL atrophy in AD have focused only on the hippocampus. It is unknown the extent to which volumes of amygdala and temporal horn of the lateral ventricle predict subsequent clinical decline. This study examined whether measures of hippocampus, amygdala, and temporal horn volume predict clinical decline over the following 6-month period in patients with mild cognitive impairment (MCI). Fully-automated volume measurements were performed in 269 MCI patients. Baseline volumes of the hippocampus, amygdala, and temporal horn were evaluated as predictors of change in Mini-mental State Exam (MMSE) and Clinical Dementia Rating Sum of Boxes (CDR SB) over a 6-month interval. Fully-automated measurements of baseline hippocampus and amygdala volumes correlated with baseline delayed recall scores. Patients with smaller baseline volumes of the hippocampus and amygdala or larger baseline volumes of the temporal horn had more rapid subsequent clinical decline on MMSE and CDR SB. Fully-automated and rapid measurement of segmental MTL volumes may help clinicians predict clinical decline in MCI patients. PMID:19474571

Fully implicit adaptive mesh refinement MHD algorithm

NASA Astrophysics Data System (ADS)

Philip, Bobby

2005-10-01

In the macroscopic simulation of plasmas, the numerical modeler is faced with the challenge of dealing with multiple time and length scales. The former results in stiffness due to the presence of very fast waves. The latter requires one to resolve the localized features that the system develops. Traditional approaches based on explicit time integration techniques and fixed meshes are not suitable for this challenge, as such approaches prevent the modeler from using realistic plasma parameters to keep the computation feasible. We propose here a novel approach, based on implicit methods and structured adaptive mesh refinement (SAMR). Our emphasis is on both accuracy and scalability with the number of degrees of freedom. To our knowledge, a scalable, fully implicit AMR algorithm has not been accomplished before for MHD. As a proof-of-principle, we focus on the reduced resistive MHD model as a basic MHD model paradigm, which is truly multiscale. The approach taken here is to adapt mature physics-based technologyootnotetextL. Chac'on et al., J. Comput. Phys. 178 (1), 15- 36 (2002) to AMR grids, and employ AMR-aware multilevel techniques (such as fast adaptive composite --FAC-- algorithms) for scalability. We will demonstrate that the concept is indeed feasible, featuring optimal scalability under grid refinement. Results of fully-implicit, dynamically-adaptive AMR simulations will be presented on a variety of problems.

Approximation-based adaptive tracking control of pure-feedback nonlinear systems with multiple unknown time-varying delays.

PubMed

Wang, Min; Ge, Shuzhi Sam; Hong, Keum-Shik

2010-11-01

This paper presents adaptive neural tracking control for a class of non-affine pure-feedback systems with multiple unknown state time-varying delays. To overcome the design difficulty from non-affine structure of pure-feedback system, mean value theorem is exploited to deduce affine appearance of state variables x(i) as virtual controls α(i), and of the actual control u. The separation technique is introduced to decompose unknown functions of all time-varying delayed states into a series of continuous functions of each delayed state. The novel Lyapunov-Krasovskii functionals are employed to compensate for the unknown functions of current delayed state, which is effectively free from any restriction on unknown time-delay functions and overcomes the circular construction of controller caused by the neural approximation of a function of u and [Formula: see text] . Novel continuous functions are introduced to overcome the design difficulty deduced from the use of one adaptive parameter. To achieve uniformly ultimate boundedness of all the signals in the closed-loop system and tracking performance, control gains are effectively modified as a dynamic form with a class of even function, which makes stability analysis be carried out at the present of multiple time-varying delays. Simulation studies are provided to demonstrate the effectiveness of the proposed scheme.

The microbiology "unknown" misadventure.

PubMed

Boyer, B; DeBenedictis, K J; Master, R; Jones, R S

1998-06-01

A 19-year-old nursing student was hospitalized after several days of nausea, vomiting, diarrhea, and fevers. Salmonella paratyphi A was isolated from multiple blood cultures. Because this is an unlikely isolate in the United States, an investigation ensued. Two and a half weeks earlier, the student had been working on a microbiology laboratory exercise "unknown." Both the "unknown" organism and the patient's blood culture isolates were identified as S. paratyphi A, with the same biochemical reactions and antimicrobial susceptibility results. The patient's condition improved with antibiotic therapy, and she was discharged after 9 days in the hospital. Conclusions related to our investigation are as follows: (1) relatively virulent organisms were unnecessary to fulfill the laboratory objectives, (2) pipetting by mouth must never be allowed, (3) proper labeling of specimens is imperative, (4) instructors should have knowledge of laboratory safety regulations, and (5) it is the obligation of laboratory directors and administrators to provide a safe academic environment.

Assessment of preparation time with fully-liquid versus non-fully liquid paediatric hexavalent vaccines. A time and motion study.

PubMed

De Coster, Ilse; Fournie, Xavier; Faure, Céline; Ziani, Eddy; Nicolas, Laurence; Soubeyrand, Benoit; Van Damme, Pierre

2015-07-31

Simplified vaccine preparation steps would save time and reduce potential immunisation errors. The aim of the study was to assess vaccine preparation time with fully-liquid hexavalent vaccine (DTaP-IPV-HB-PRP-T, Sanofi Pasteur MSD) versus non-fully liquid hexavalent vaccine that needs reconstitution (DTPa-HBV-IPV/Hib, GlaxoSmithKline Biologicals). Ninety-six Health Care Professionals (HCPs) participated in a randomised, cross-over, open-label, time and motion study in Belgium (2014). HCPs prepared each vaccine in a cross-over manner with a wash-out period of 3-5min. An independent nurse assessed preparation time and immunisation errors by systematic review of the videos. HCPs satisfaction and preference were evaluated by a self-administered questionnaire. Average preparation time was 36s for the fully-liquid vaccine and 70.5s for the non-fully liquid vaccine. The time saved using the fully-liquid vaccine was 34.5s (p≤0.001). On 192 preparations, 57 immunisation errors occurred: 47 in the non-fully liquid vaccine group (including one missing reconstitution of Hib component), 10 in the fully-liquid vaccine group. 71.9% of HCPs were very or somewhat satisfied with the ease of handling of both vaccines; 66.7% and 67.7% were very or somewhat satisfied with speed of preparation in the fully-liquid vaccine and the non-fully liquid vaccine groups, respectively. Almost all HCPs (97.6%) stated they would prefer the use of the fully-liquid vaccine in their daily practice. Preparation of a fully-liquid hexavalent vaccine can be completed in half the time necessary to prepare a non-fully liquid vaccine. The simplicity of the fully-liquid hexavalent vaccine preparation helps optimise reduction of immunisation errors. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Earth-moon system: Dynamics and parameter estimation

NASA Technical Reports Server (NTRS)

Breedlove, W. J., Jr.

1975-01-01

A theoretical development of the equations of motion governing the earth-moon system is presented. The earth and moon were treated as finite rigid bodies and a mutual potential was utilized. The sun and remaining planets were treated as particles. Relativistic, non-rigid, and dissipative effects were not included. The translational and rotational motion of the earth and moon were derived in a fully coupled set of equations. Euler parameters were used to model the rotational motions. The mathematical model is intended for use with data analysis software to estimate physical parameters of the earth-moon system using primarily LURE type data. Two program listings are included. Program ANEAMO computes the translational/rotational motion of the earth and moon from analytical solutions. Program RIGEM numerically integrates the fully coupled motions as described above.

76 FR 36176 - Fully Developed Claim (Fully Developed Claims-Applications for Compensation, Pension, DIC, Death...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-06-21

... DEPARTMENT OF VETERANS AFFAIRS [OMB Control No. 2900-0747] Fully Developed Claim (Fully Developed Claims--Applications for Compensation, Pension, DIC, Death Pension, and/or Accrued Benefits); Correction AGENCY: Veterans Benefits Administration, Department of Veterans Affairs. ACTION: Notice; correction...

Computational methods for estimation of parameters in hyperbolic systems

NASA Technical Reports Server (NTRS)

Banks, H. T.; Ito, K.; Murphy, K. A.

1983-01-01

Approximation techniques for estimating spatially varying coefficients and unknown boundary parameters in second order hyperbolic systems are discussed. Methods for state approximation (cubic splines, tau-Legendre) and approximation of function space parameters (interpolatory splines) are outlined and numerical findings for use of the resulting schemes in model "one dimensional seismic inversion' problems are summarized.

Characterizing heterogeneous properties of cerebral aneurysms with unknown stress-free geometry: a precursor to in vivo identification.

PubMed

Zhao, Xuefeng; Raghavan, Madhavan L; Lu, Jia

2011-05-01

Knowledge of elastic properties of cerebral aneurysms is crucial for understanding the biomechanical behavior of the lesion. However, characterizing tissue properties using in vivo motion data presents a tremendous challenge. Aside from the limitation of data accuracy, a pressing issue is that the in vivo motion does not expose the stress-free geometry. This is compounded by the nonlinearity, anisotropy, and heterogeneity of the tissue behavior. This article introduces a method for identifying the heterogeneous properties of aneurysm wall tissue under unknown stress-free configuration. In the proposed approach, an accessible configuration is taken as the reference; the unknown stress-free configuration is represented locally by a metric tensor describing the prestrain from the stress-free configuration to the reference configuration. Material parameters are identified together with the metric tensor pointwisely. The paradigm is tested numerically using a forward-inverse analysis loop. An image-derived sac is considered. The aneurysm tissue is modeled as an eightply laminate whose constitutive behavior is described by an anisotropic hyperelastic strain-energy function containing four material parameters. The parameters are assumed to vary continuously in two assigned patterns to represent two types of material heterogeneity. Nine configurations between the diastolic and systolic pressures are generated by forward quasi-static finite element analyses. These configurations are fed to the inverse analysis to delineate the material parameters and the metric tensor. The recovered and the assigned distributions are in good agreement. A forward verification is conducted by comparing the displacement solutions obtained from the recovered and the assigned material parameters at a different pressure. The nodal displacements are found in excellent agreement.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

PubMed

Karr, Jonathan R; Williams, Alex H; Zucker, Jeremy D; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A; Bot, Brian M; Hoff, Bruce R; Kellen, Michael R; Covert, Markus W; Stolovitzky, Gustavo A; Meyer, Pablo

2015-05-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models

PubMed Central

Karr, Jonathan R.; Williams, Alex H.; Zucker, Jeremy D.; Raue, Andreas; Steiert, Bernhard; Timmer, Jens; Kreutz, Clemens; Wilkinson, Simon; Allgood, Brandon A.; Bot, Brian M.; Hoff, Bruce R.; Kellen, Michael R.; Covert, Markus W.; Stolovitzky, Gustavo A.; Meyer, Pablo

2015-01-01

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model’s structure and in silico “experimental” data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation. PMID:26020786

Towards quantitative imaging: stability of fully automated nodule segmentation across varied dose levels and reconstruction parameters in a low-dose CT screening patient cohort

NASA Astrophysics Data System (ADS)

Wahi-Anwar, M. Wasil; Emaminejad, Nastaran; Hoffman, John; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael F.

2018-02-01

Quantitative imaging in lung cancer CT seeks to characterize nodules through quantitative features, usually from a region of interest delineating the nodule. The segmentation, however, can vary depending on segmentation approach and image quality, which can affect the extracted feature values. In this study, we utilize a fully-automated nodule segmentation method - to avoid reader-influenced inconsistencies - to explore the effects of varied dose levels and reconstruction parameters on segmentation. Raw projection CT images from a low-dose screening patient cohort (N=59) were reconstructed at multiple dose levels (100%, 50%, 25%, 10%), two slice thicknesses (1.0mm, 0.6mm), and a medium kernel. Fully-automated nodule detection and segmentation was then applied, from which 12 nodules were selected. Dice similarity coefficient (DSC) was used to assess the similarity of the segmentation ROIs of the same nodule across different reconstruction and dose conditions. Nodules at 1.0mm slice thickness and dose levels of 25% and 50% resulted in DSC values greater than 0.85 when compared to 100% dose, with lower dose leading to a lower average and wider spread of DSC values. At 0.6mm, the increased bias and wider spread of DSC values from lowering dose were more pronounced. The effects of dose reduction on DSC for CAD-segmented nodules were similar in magnitude to reducing the slice thickness from 1.0mm to 0.6mm. In conclusion, variation of dose and slice thickness can result in very different segmentations because of noise and image quality. However, there exists some stability in segmentation overlap, as even at 1mm, an image with 25% of the lowdose scan still results in segmentations similar to that seen in a full-dose scan.

Impact of polymer structure and composition on fully resorbable endovascular scaffold performance

PubMed Central

Ferdous, Jahid; Kolachalama, Vijaya B.; Shazly, Tarek

2014-01-01

Fully erodible endovascular scaffolds are being increasingly considered for the treatment of obstructive arterial disease owing to their potential to mitigate long-term risks associated with permanent alternatives. While complete scaffold erosion facilitates vessel healing, generation and release of material degradation by-products from candidate materials such as poly-l-lactide (PLLA) may elicit local inflammatory responses that limit implant efficacy. We developed a computational framework to quantify how the compositional and structural parameters of PLLA-based fully erodible endovascular scaffolds affect degradation kinetics, erosion kinetics and the transient accumulation of material by-products within the arterial wall. Parametric studies reveal that, while some material properties have similar effects on these critical processes, others induce qualitatively opposing responses. For example, scaffold degradation is only mildly responsive to changes in either PLLA polydispersity or the initial degree of crystallinity, while the erosion kinetics is comparatively sensitive to crystallinity. Moreover, lactide doping can effectively tune both scaffold degradation and erosion, but a concomitant increase in local byproduct accumulation raises concerns about implant safety. Optimized erodible endovascular scaffolds must precisely balance therapeutic function and biological response over the implant lifetime, where compositional and structural parameters will have differential effects on implant performance. PMID:23261926

A continuous optimization approach for inferring parameters in mathematical models of regulatory networks.

PubMed

Deng, Zhimin; Tian, Tianhai

2014-07-29

The advances of systems biology have raised a large number of sophisticated mathematical models for describing the dynamic property of complex biological systems. One of the major steps in developing mathematical models is to estimate unknown parameters of the model based on experimentally measured quantities. However, experimental conditions limit the amount of data that is available for mathematical modelling. The number of unknown parameters in mathematical models may be larger than the number of observation data. The imbalance between the number of experimental data and number of unknown parameters makes reverse-engineering problems particularly challenging. To address the issue of inadequate experimental data, we propose a continuous optimization approach for making reliable inference of model parameters. This approach first uses a spline interpolation to generate continuous functions of system dynamics as well as the first and second order derivatives of continuous functions. The expanded dataset is the basis to infer unknown model parameters using various continuous optimization criteria, including the error of simulation only, error of both simulation and the first derivative, or error of simulation as well as the first and second derivatives. We use three case studies to demonstrate the accuracy and reliability of the proposed new approach. Compared with the corresponding discrete criteria using experimental data at the measurement time points only, numerical results of the ERK kinase activation module show that the continuous absolute-error criteria using both function and high order derivatives generate estimates with better accuracy. This result is also supported by the second and third case studies for the G1/S transition network and the MAP kinase pathway, respectively. This suggests that the continuous absolute-error criteria lead to more accurate estimates than the corresponding discrete criteria. We also study the robustness property of these three

Fully localised nonlinear energy growth optimals in pipe flow

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

Pringle, Chris C. T.; Willis, Ashley P.; Kerswell, Rich R.

A new, fully localised, energy growth optimal is found over large times and in long pipe domains at a given mass flow rate. This optimal emerges at a threshold disturbance energy below which a nonlinear version of the known (streamwise-independent) linear optimal [P. J. Schmid and D. S. Henningson, “Optimal energy density growth in Hagen-Poiseuille flow,” J. Fluid Mech. 277, 192–225 (1994)] is selected and appears to remain the optimal up until the critical energy at which transition is triggered. The form of this optimal is similar to that found in short pipes [Pringle et al., “Minimal seeds for shearmore » flow turbulence: Using nonlinear transient growth to touch the edge of chaos,” J. Fluid Mech. 702, 415–443 (2012)], but now with full localisation in the streamwise direction. This fully localised optimal perturbation represents the best approximation yet of the minimal seed (the smallest perturbation which is arbitrarily close to states capable of triggering a turbulent episode) for “real” (laboratory) pipe flows. Dependence of the optimal with respect to several parameters has been computed and establishes that the structure is robust.« less

Combined p16 and p53 expression in cervical cancer of unknown primary and other prognostic parameters : A single-center analysis.

PubMed

Yildirim, Müjdat; Müller von der Grün, Jens; Winkelmann, Ria; Fokas, Emmanouil; Rödel, Franz; Ackermann, Hanns; Rödel, Claus; Balermpas, Panagiotis

2017-04-01

Cervical cancer of unknown primary (CUP) represents an uncommon and heterogeneous subentity of head and neck cancer. However, both optimal diagnostics and therapy remain unclear. An improved understanding of the underlying pathology is essential to enable future tailored therapies and optimized outcomes. We retrospectively analyzed 53 patients with head and neck CUP and 48 available cervical lymph node specimens. All patients have received radiotherapy between 2007 and 2015. Preradiotherapy involved lymph node specimens were analyzed for p16 and p53 immunoreactivity. The prognostic relevance of the combined p16 and p53 status and other clinical parameters were examined by univariate and multivariate analyses. Median patient age was 61.5 years and median irradiation dose to the involved nodal levels was 66 Gy. Of the 48 evaluated specimens, 13 (27%) were p16-positive and 31 (64.6%) p53-positive. After a median follow up of 32.9 months, patients with p16-negative and simultaneously p53-positive tumors showed a significantly inferior tumor-specific survival (TSS) compared to those with either p16+/p53-, p16+/p53+, or p16-/p53- (univariate: p = 0.055, multivariate: p = 0.038). Other factors with an adverse impact on TSS in the univariate analysis were smoking history (p = 0.032) and nodal stage (p = 0.038). The combined p16- and p53-expression status in cervical metastases of CUP may represent a simple method for risk stratification. Further validation of these biomarkers in large prospective trials is essential to design rational trials for CUP treatment optimization.

Complex Dynamical Networks Constructed with Fully Controllable Nonlinear Nanomechanical Oscillators.

PubMed

Fon, Warren; Matheny, Matthew H; Li, Jarvis; Krayzman, Lev; Cross, Michael C; D'Souza, Raissa M; Crutchfield, James P; Roukes, Michael L

2017-10-11

Control of the global parameters of complex networks has been explored experimentally in a variety of contexts. Yet, the more difficult prospect of realizing arbitrary network architectures, especially analog physical networks that provide dynamical control of individual nodes and edges, has remained elusive. Given the vast hierarchy of time scales involved, it also proves challenging to measure a complex network's full internal dynamics. These span from the fastest nodal dynamics to very slow epochs over which emergent global phenomena, including network synchronization and the manifestation of exotic steady states, eventually emerge. Here, we demonstrate an experimental system that satisfies these requirements. It is based upon modular, fully controllable, nonlinear radio frequency nanomechanical oscillators, designed to form the nodes of complex dynamical networks with edges of arbitrary topology. The dynamics of these oscillators and their surrounding network are analog and continuous-valued and can be fully interrogated in real time. They comprise a piezoelectric nanomechanical membrane resonator, which serves as the frequency-determining element within an electrical feedback circuit. This embodiment permits network interconnections entirely within the electrical domain and provides unprecedented node and edge control over a vast region of parameter space. Continuous measurement of the instantaneous amplitudes and phases of every constituent oscillator node are enabled, yielding full and detailed network data without reliance upon statistical quantities. We demonstrate the operation of this platform through the real-time capture of the dynamics of a three-node ring network as it evolves from the uncoupled state to full synchronization.

Measurement of pixel response functions of a fully depleted CCD

NASA Astrophysics Data System (ADS)

Kobayashi, Yukiyasu; Niwa, Yoshito; Yano, Taihei; Gouda, Naoteru; Hara, Takuji; Yamada, Yoshiyuki

2014-07-01

We describe the measurement of detailed and precise Pixel Response Functions (PRFs) of a fully depleted CCD. Measurements were performed under different physical conditions, such as different wavelength light sources or CCD operating temperatures. We determined the relations between these physical conditions and the forms of the PRF. We employ two types of PRFs: one is the model PRF (mPRF) that can represent the shape of a PRF with one characteristic parameter and the other is the simulated PRF (sPRF) that is the resultant PRF from simulating physical phenomena. By using measured, model, and simulated PRFs, we determined the relations between operational parameters and the PRFs. Using the obtained relations, we can now estimate a PRF under conditions that will be encountered during the course of Nano-JASMINE observations. These estimated PRFs will be utilized in the analysis of the Nano-JASMINE data.

Distributed parameter estimation in unreliable sensor networks via broadcast gossip algorithms.

PubMed

Wang, Huiwei; Liao, Xiaofeng; Wang, Zidong; Huang, Tingwen; Chen, Guo

2016-01-01

In this paper, we present an asynchronous algorithm to estimate the unknown parameter under an unreliable network which allows new sensors to join and old sensors to leave, and can tolerate link failures. Each sensor has access to partially informative measurements when it is awakened. In addition, the proposed algorithm can avoid the interference among messages and effectively reduce the accumulated measurement and quantization errors. Based on the theory of stochastic approximation, we prove that our proposed algorithm almost surely converges to the unknown parameter. Finally, we present a numerical example to assess the performance and the communication cost of the algorithm. Copyright © 2015 Elsevier Ltd. All rights reserved.

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Learning Unknown Event Models

DTIC Science & Technology

2014-07-01

Intelligence (www.aaai.org). All rights reserved. knowledge engineering, but it is often impractical due to high environment variance, or unknown events...distribution unlimited 13. SUPPLEMENTARY NOTES In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence , 27-31 July 2014...autonomy for responding to unexpected events in strategy simulations. Computational Intelligence , 29(2), 187-206. Leake, D. B. (1991), Goal-based

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

NASA Astrophysics Data System (ADS)

Singh, R.; Verma, H. K.

2013-12-01

This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

Unknown foundation determination for scour.

DOT National Transportation Integrated Search

2012-04-01

Unknown foundations affect about 9,000 bridges in Texas. For bridges over rivers, this creates a problem : regarding scour decisions as the calculated scour depth cannot be compared to the foundation depth, and a : very conservative costly approach m...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 5 Administrative Personnel 3 2012-01-01 2012-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 5 Administrative Personnel 3 2013-01-01 2013-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 5 Administrative Personnel 3 2010-01-01 2010-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 5 Administrative Personnel 3 2011-01-01 2011-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

5 CFR 1651.16 - Missing and unknown beneficiaries.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 5 Administrative Personnel 3 2014-01-01 2014-01-01 false Missing and unknown beneficiaries. 1651... § 1651.16 Missing and unknown beneficiaries. (a) Locate and identify beneficiaries. (1) The TSP record... one or more beneficiaries (and not all) appear to be missing, payment of part of the participant's...

Topology-selective jamming of fully-connected, code-division random-access networks

NASA Technical Reports Server (NTRS)

Polydoros, Andreas; Cheng, Unjeng

1990-01-01

The purpose is to introduce certain models of topology selective stochastic jamming and examine its impact on a class of fully-connected, spread-spectrum, slotted ALOHA-type random access networks. The theory covers dedicated as well as half-duplex units. The dominant role of the spatial duty factor is established, and connections with the dual concept of time selective jamming are discussed. The optimal choices of coding rate and link access parameters (from the users' side) and the jamming spatial fraction are numerically established for DS and FH spreading.

iGeoT v1.0: Automatic Parameter Estimation for Multicomponent Geothermometry, User's Guide

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

Spycher, Nicolas; Finsterle, Stefan

GeoT implements the multicomponent geothermometry method developed by Reed and Spycher [1984] into a stand-alone computer program to ease the application of this method and to improve the prediction of geothermal reservoir temperatures using full and integrated chemical analyses of geothermal fluids. Reservoir temperatures are estimated from statistical analyses of mineral saturation indices computed as a function of temperature. The reconstruction of the deep geothermal fluid compositions, and geothermometry computations, are all implemented into the same computer program, allowing unknown or poorly constrained input parameters to be estimated by numerical optimization. This integrated geothermometry approach presents advantages over classical geothermometersmore » for fluids that have not fully equilibrated with reservoir minerals and/or that have been subject to processes such as dilution and gas loss. This manual contains installation instructions for iGeoT, and briefly describes the input formats needed to run iGeoT in Automatic or Expert Mode. An example is also provided to demonstrate the use of iGeoT.« less

A Regev-type fully homomorphic encryption scheme using modulus switching.

PubMed

Chen, Zhigang; Wang, Jian; Chen, Liqun; Song, Xinxia

2014-01-01

A critical challenge in a fully homomorphic encryption (FHE) scheme is to manage noise. Modulus switching technique is currently the most efficient noise management technique. When using the modulus switching technique to design and implement a FHE scheme, how to choose concrete parameters is an important step, but to our best knowledge, this step has drawn very little attention to the existing FHE researches in the literature. The contributions of this paper are twofold. On one hand, we propose a function of the lower bound of dimension value in the switching techniques depending on the LWE specific security levels. On the other hand, as a case study, we modify the Brakerski FHE scheme (in Crypto 2012) by using the modulus switching technique. We recommend concrete parameter values of our proposed scheme and provide security analysis. Our result shows that the modified FHE scheme is more efficient than the original Brakerski scheme in the same security level.

A Regev-Type Fully Homomorphic Encryption Scheme Using Modulus Switching

PubMed Central

Chen, Zhigang; Wang, Jian; Song, Xinxia

2014-01-01

A critical challenge in a fully homomorphic encryption (FHE) scheme is to manage noise. Modulus switching technique is currently the most efficient noise management technique. When using the modulus switching technique to design and implement a FHE scheme, how to choose concrete parameters is an important step, but to our best knowledge, this step has drawn very little attention to the existing FHE researches in the literature. The contributions of this paper are twofold. On one hand, we propose a function of the lower bound of dimension value in the switching techniques depending on the LWE specific security levels. On the other hand, as a case study, we modify the Brakerski FHE scheme (in Crypto 2012) by using the modulus switching technique. We recommend concrete parameter values of our proposed scheme and provide security analysis. Our result shows that the modified FHE scheme is more efficient than the original Brakerski scheme in the same security level. PMID:25093212

An almost-parameter-free harmony search algorithm for groundwater pollution source identification.

PubMed

Jiang, Simin; Zhang, Yali; Wang, Pei; Zheng, Maohui

2013-01-01

The spatiotemporal characterization of unknown sources of groundwater pollution is frequently encountered in environmental problems. This study adopts a simulation-optimization approach that combines a contaminant transport simulation model with a heuristic harmony search algorithm to identify unknown pollution sources. In the proposed methodology, an almost-parameter-free harmony search algorithm is developed. The performance of this methodology is evaluated on an illustrative groundwater pollution source identification problem, and the identified results indicate that the proposed almost-parameter-free harmony search algorithm-based optimization model can give satisfactory estimations, even when the irregular geometry, erroneous monitoring data, and prior information shortage of potential locations are considered.

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.

Semi-empirical modelling for forest above ground biomass estimation using hybrid and fully PolSAR data

NASA Astrophysics Data System (ADS)

Tomar, Kiledar S.; Kumar, Shashi; Tolpekin, Valentyn A.; Joshi, Sushil K.

2016-05-01

Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m-alpha and Yamaguchi decomposition modelling were extracted. The R2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha-1) and 73.424 (t ha-1) respectively. On the basis of RMSE and R2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering

Benefits from bremsstrahlung distribution evaluation to get unknown information from specimen in SEM and TEM

NASA Astrophysics Data System (ADS)

Eggert, F.; Camus, P. P.; Schleifer, M.; Reinauer, F.

2018-01-01

The energy-dispersive X-ray spectrometer (EDS or EDX) is a commonly used device to characterise the composition of investigated material in scanning and transmission electron microscopes (SEM and TEM). One major benefit compared to wavelength-dispersive X-ray spectrometers (WDS) is that EDS systems collect the entire spectrum simultaneously. Therefore, not only are all emitted characteristic X-ray lines in the spectrum, but also the complete bremsstrahlung distribution is included. It is possible to get information about the specimen even from this radiation, which is usually perceived more as a disturbing background. This is possible by using theoretical model knowledge about bremsstrahlung excitation and absorption in the specimen in comparison to the actual measured spectrum. The core aim of this investigation is to present a method for better bremsstrahlung fitting in unknown geometry cases by variation of the geometry parameters and to utilise this knowledge also for characteristic radiation evaluation. A method is described, which allows the parameterisation of the true X-ray absorption conditions during spectrum acquisition. An ‘effective tilt’ angle parameter is determined by evaluation of the bremsstrahlung shape of the measured SEM spectra. It is useful for bremsstrahlung background approximation, with exact calculations of the absorption edges below the characteristic peaks, required for P/B-ZAF model based quantification methods. It can even be used for ZAF based quantification models as a variable input parameter. The analytical results are then much more reliable for the different absorption effects from irregular specimen surfaces because the unknown absorption dependency is considered. Finally, the method is also applied for evaluation of TEM spectra. In this case, the real physical parameter optimisation is with sample thickness (mass thickness), which is influencing the emitted and measured spectrum due to different absorption with TEM

Fully automated, deep learning segmentation of oxygen-induced retinopathy images

PubMed Central

Xiao, Sa; Bucher, Felicitas; Wu, Yue; Rokem, Ariel; Lee, Cecilia S.; Marra, Kyle V.; Fallon, Regis; Diaz-Aguilar, Sophia; Aguilar, Edith; Friedlander, Martin; Lee, Aaron Y.

2017-01-01

Oxygen-induced retinopathy (OIR) is a widely used model to study ischemia-driven neovascularization (NV) in the retina and to serve in proof-of-concept studies in evaluating antiangiogenic drugs for ocular, as well as nonocular, diseases. The primary parameters that are analyzed in this mouse model include the percentage of retina with vaso-obliteration (VO) and NV areas. However, quantification of these two key variables comes with a great challenge due to the requirement of human experts to read the images. Human readers are costly, time-consuming, and subject to bias. Using recent advances in machine learning and computer vision, we trained deep learning neural networks using over a thousand segmentations to fully automate segmentation in OIR images. While determining the percentage area of VO, our algorithm achieved a similar range of correlation coefficients to that of expert inter-human correlation coefficients. In addition, our algorithm achieved a higher range of correlation coefficients compared with inter-expert correlation coefficients for quantification of the percentage area of neovascular tufts. In summary, we have created an open-source, fully automated pipeline for the quantification of key values of OIR images using deep learning neural networks. PMID:29263301

Learning from the Unknown Student

ERIC Educational Resources Information Center

Barlow, Angela T.; Gerstenschlager, Natasha E.; Harmon, Shannon E.

2016-01-01

In this article, three instructional situations demonstrate the value of using an "unknown" student's work to allow the advancement of students' mathematical thinking as well as their engagement in the mathematical practice of critiquing the reasoning of others: (1) introducing alternative solution strategies; (2) critiquing inaccuracies…

A simple but fully nonlocal correction to the random phase approximation

NASA Astrophysics Data System (ADS)

Ruzsinszky, Adrienn; Perdew, John P.; Csonka, Gábor I.

2011-03-01

The random phase approximation (RPA) stands on the top rung of the ladder of ground-state density functional approximations. The simple or direct RPA has been found to predict accurately many isoelectronic energy differences. A nonempirical local or semilocal correction to this direct RPA leaves isoelectronic energy differences almost unchanged, while improving total energies, ionization energies, etc., but fails to correct the RPA underestimation of molecular atomization energies. Direct RPA and its semilocal correction may miss part of the middle-range multicenter nonlocality of the correlation energy in a molecule. Here we propose a fully nonlocal, hybrid-functional-like addition to the semilocal correction. The added full nonlocality is important in molecules, but not in atoms. Under uniform-density scaling, this fully nonlocal correction scales like the second-order-exchange contribution to the correlation energy, an important part of the correction to direct RPA, and like the semilocal correction itself. For the atomization energies of ten molecules, and with the help of one fit parameter, it performs much better than the elaborate second-order screened exchange correction.

Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints.

PubMed

Li, Da-Peng; Li, Dong-Juan; Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip

2017-10-01

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.

Pregnancy of unknown location: Outcome in a tertiary care hospital.

PubMed

Amer, Nuzhat; Amer, Muhammad; Kolkaila, Mohamed Abdoh; Yaqoob, Shahida

2015-10-01

To find out the outcome of a cohort of women with pregnancy of unknown location presenting to a tertiary care hospital. The prospective study was conducted from January to December, 2011, at Early Pregnancy Assessment Unit, King Faisal Military Hospital, Khamis Mushait, Saudi Arabia. Data was collected for women with early pregnancy or with history of amenorrhoea, bleeding or pain. These women were investigated with serum beta-human chorionic gonadotrophin levels twice weekly and transvaginal ultrasonography weekly. Expectant management was done for failing pregnancy of unknown location while medical or surgical management was considered for persistent pregnancy of unknown location and ectopic pregnancy. During study period, 7215 patients were admitted, and, of them, 2212(30.6%) were patients with early pregnancy. Meeting the inclusion criteria were 183(2.53%) patients who formed the study sample. There were 131(71.6%) patients presenting with amenorrhoea, 90(49.2%) had bleeding and 93(50.8%) presented with pain. Outcome of 100(54.6%) patients was failing pregnancy of unknown location, 58(31.7%) had intrauterine pregnancy, 14(7.7%) converted to ectopic pregnancy, while 11(6%) had persistent pregnancy of unknown location. All patients with persistent pregnancy of unknown location and 5(36%) patients with ectopic pregnancy were medically treated. Five (36%) patients having ectopic pregnancy were managed surgically. Management of choice for asymptomatic patients having pregnancy of unknown location is expectant management. Most of the patients suspected to have Most of the patients with persistent pregnancy of unknown location and ectopic pregnancy can be managed medically.

Students' Conscious Unknowns about Artefacts and Natural Objects

ERIC Educational Resources Information Center

Vaz-Rebelo, Piedade; Fernandes, Paula; Morgado, Julia; Monteiro, António; Otero, José

2016-01-01

This study attempts to characterise what 7th- and 12th-grade students believe they do not know about artefacts and natural objects, as well as the dependence of what is unknown on a knowledge of these objects. The students were asked to make explicit through questioning what they did not know about a sample of objects. The unknowns generated were…

Clinical characteristics of children with mental retardation of unknown etiology in Korea.

PubMed Central

Yim, S. Y.; Lee, I. Y.

1999-01-01

The purpose of this study was to investigate the clinical characteristics of children with mental retardation (MR) of unknown etiology for early recognition and intervention. In this study, we defined children with MR of unknown etiology as those without clear etiologies for MR despite extensive evaluation and were not associated with pathological behavioral problems such as pervasive developmental disorders and attention-deficit/hyperactivity disorder. The clinical characteristics of children with MR of unknown etiology were as follows. 1) MR of unknown etiology was 48.8% of all MR. 2) MR of unknown etiology was more common in males. 3) Delayed language development was a leading factor that made the parents of children with MR of unknown etiology seek help from physicians. However, most of the children with MR of unknown etiology showed a relatively uniform delay in several areas of development. 4) Most children with MR of unknown etiology were delayed walkers. 5) Most children with MR of unknown etiology were mild cases. PMID:10331556

Estimation of Ordinary Differential Equation Parameters Using Constrained Local Polynomial Regression.

PubMed

Ding, A Adam; Wu, Hulin

2014-10-01

We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unknown parameters in the differential equation model. We also derive the asymptotic bias and variance of the proposed estimator. Our simulation studies show that our new estimator is clearly better than the pseudo-least squares estimator in estimation accuracy with a small price of computational cost. An application example on immune cell kinetics and trafficking for influenza infection further illustrates the benefits of the proposed new method.

A Sparse Bayesian Learning Algorithm for White Matter Parameter Estimation from Compressed Multi-shell Diffusion MRI.

PubMed

Pisharady, Pramod Kumar; Sotiropoulos, Stamatios N; Sapiro, Guillermo; Lenglet, Christophe

2017-09-01

We propose a sparse Bayesian learning algorithm for improved estimation of white matter fiber parameters from compressed (under-sampled q-space) multi-shell diffusion MRI data. The multi-shell data is represented in a dictionary form using a non-monoexponential decay model of diffusion, based on continuous gamma distribution of diffusivities. The fiber volume fractions with predefined orientations, which are the unknown parameters, form the dictionary weights. These unknown parameters are estimated with a linear un-mixing framework, using a sparse Bayesian learning algorithm. A localized learning of hyperparameters at each voxel and for each possible fiber orientations improves the parameter estimation. Our experiments using synthetic data from the ISBI 2012 HARDI reconstruction challenge and in-vivo data from the Human Connectome Project demonstrate the improvements.

Tune-stabilized, non-scaling, fixed-field, alternating gradient accelerator

DOEpatents

Johnstone, Carol J [Warrenville, IL

2011-02-01

A FFAG is a particle accelerator having turning magnets with a linear field gradient for confinement and a large edge angle to compensate for acceleration. FODO cells contain focus magnets and defocus magnets that are specified by a number of parameters. A set of seven equations, called the FFAG equations relate the parameters to one another. A set of constraints, call the FFAG constraints, constrain the FFAG equations. Selecting a few parameters, such as injection momentum, extraction momentum, and drift distance reduces the number of unknown parameters to seven. Seven equations with seven unknowns can be solved to yield the values for all the parameters and to thereby fully specify a FFAG.

A fully Bayesian method for jointly fitting instrumental calibration and X-ray spectral models

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

Xu, Jin; Yu, Yaming; Van Dyk, David A.

2014-10-20

Owing to a lack of robust principled methods, systematic instrumental uncertainties have generally been ignored in astrophysical data analysis despite wide recognition of the importance of including them. Ignoring calibration uncertainty can cause bias in the estimation of source model parameters and can lead to underestimation of the variance of these estimates. We previously introduced a pragmatic Bayesian method to address this problem. The method is 'pragmatic' in that it introduced an ad hoc technique that simplified computation by neglecting the potential information in the data for narrowing the uncertainty for the calibration product. Following that work, we use amore » principal component analysis to efficiently represent the uncertainty of the effective area of an X-ray (or γ-ray) telescope. Here, however, we leverage this representation to enable a principled, fully Bayesian method that coherently accounts for the calibration uncertainty in high-energy spectral analysis. In this setting, the method is compared with standard analysis techniques and the pragmatic Bayesian method. The advantage of the fully Bayesian method is that it allows the data to provide information not only for estimation of the source parameters but also for the calibration product—here the effective area, conditional on the adopted spectral model. In this way, it can yield more accurate and efficient estimates of the source parameters along with valid estimates of their uncertainty. Provided that the source spectrum can be accurately described by a parameterized model, this method allows rigorous inference about the effective area by quantifying which possible curves are most consistent with the data.« less

Fully Dynamic Bin Packing

NASA Astrophysics Data System (ADS)

Ivković, Zoran; Lloyd, Errol L.

Classic bin packing seeks to pack a given set of items of possibly varying sizes into a minimum number of identical sized bins. A number of approximation algorithms have been proposed for this NP-hard problem for both the on-line and off-line cases. In this chapter we discuss fully dynamic bin packing, where items may arrive (Insert) and depart (Delete) dynamically. In accordance with standard practice for fully dynamic algorithms, it is assumed that the packing may be arbitrarily rearranged to accommodate arriving and departing items. The goal is to maintain an approximately optimal solution of provably high quality in a total amount of time comparable to that used by an off-line algorithm delivering a solution of the same quality.

Time‐dependent renewal‐model probabilities when date of last earthquake is unknown

USGS Publications Warehouse

Field, Edward H.; Jordan, Thomas H.

2015-01-01

We derive time-dependent, renewal-model earthquake probabilities for the case in which the date of the last event is completely unknown, and compare these with the time-independent Poisson probabilities that are customarily used as an approximation in this situation. For typical parameter values, the renewal-model probabilities exceed Poisson results by more than 10% when the forecast duration exceeds ~20% of the mean recurrence interval. We also derive probabilities for the case in which the last event is further constrained to have occurred before historical record keeping began (the historic open interval), which can only serve to increase earthquake probabilities for typically applied renewal models.We conclude that accounting for the historic open interval can improve long-term earthquake rupture forecasts for California and elsewhere.

A review on classification methods for solving fully fuzzy linear systems

NASA Astrophysics Data System (ADS)

Daud, Wan Suhana Wan; Ahmad, Nazihah; Aziz, Khairu Azlan Abd

2015-12-01

Fully Fuzzy Linear System (FFLS) exists when there are fuzzy numbers on both sides of the linear systems. This system is quite significant today since most of the linear systems play with uncertainties of parameters especially in mathematics, engineering and finance. Many researchers and practitioners used the FFLS to model their problem and they apply various methods to solve it. In this paper, we present the outcome of a comprehensive review that we have done on various methods used for solving the FFLS. We classify our findings based on parameters' type used for the FFLS either restricted or unrestricted. We also discuss some of the methods by illustrating numerical examples and identify the differences between the methods. Ultimately, we summarize all findings in a table. We hope this study will encourage researchers to appreciate the use of this method and with that it will be easier for them to choose the right method or to propose any new method for solving the FFLS.

Fully polynomial-time approximation scheme for a special case of a quadratic Euclidean 2-clustering problem

NASA Astrophysics Data System (ADS)

Kel'manov, A. V.; Khandeev, V. I.

2016-02-01

The strongly NP-hard problem of partitioning a finite set of points of Euclidean space into two clusters of given sizes (cardinalities) minimizing the sum (over both clusters) of the intracluster sums of squared distances from the elements of the clusters to their centers is considered. It is assumed that the center of one of the sought clusters is specified at the desired (arbitrary) point of space (without loss of generality, at the origin), while the center of the other one is unknown and determined as the mean value over all elements of this cluster. It is shown that unless P = NP, there is no fully polynomial-time approximation scheme for this problem, and such a scheme is substantiated in the case of a fixed space dimension.

A dissipative random velocity field for fully developed fluid turbulence

NASA Astrophysics Data System (ADS)

Chevillard, Laurent; Pereira, Rodrigo; Garban, Christophe

2016-11-01

We investigate the statistical properties, based on numerical simulations and analytical calculations, of a recently proposed stochastic model for the velocity field of an incompressible, homogeneous, isotropic and fully developed turbulent flow. A key step in the construction of this model is the introduction of some aspects of the vorticity stretching mechanism that governs the dynamics of fluid particles along their trajectory. An additional further phenomenological step aimed at including the long range correlated nature of turbulence makes this model depending on a single free parameter that can be estimated from experimental measurements. We confirm the realism of the model regarding the geometry of the velocity gradient tensor, the power-law behaviour of the moments of velocity increments, including the intermittent corrections, and the existence of energy transfers across scales. We quantify the dependence of these basic properties of turbulent flows on the free parameter and derive analytically the spectrum of exponents of the structure functions in a simplified non dissipative case. A perturbative expansion shows that energy transfers indeed take place, justifying the dissipative nature of this random field.

Deterministic Joint Assisted Cloning of Unknown Two-Qubit Entangled States

NASA Astrophysics Data System (ADS)

Zhan, You-Bang

2012-06-01

We present two schemes for perfect cloning unknown two-qubit and general two-qubit entangled states with assistance from two state preparers, respectively. In the schemes, the sender wish to teleport an unknown two-qubit (or general two-qubit) entangled state which from two state preparers to a remote receiver, and then create a perfect copy of the unknown state at her place. The schemes include two stages. The first stage of the schemes requires usual teleportation. In the second stage, to help the sender realize the quantum cloning, two state preparers perform two-qubit projective measurements on their own qubits which from the sender, then the sender can acquire a perfect copy of the unknown state. To complete the assisted cloning schemes, several novel sets of mutually orthogonal basis vectors are introduced. It is shown that, only if two state preparers collaborate with each other, and perform projective measurements under suitable measuring basis on their own qubit respectively, the sender can create a copy of the unknown state by means of some appropriate unitary operations. The advantage of the present schemes is that the total success probability for assisted cloning a perfect copy of the unknown state can reach 1.

5. Photographic copy of photograph (date unknown, original print in ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. Photographic copy of photograph (date unknown, original print in the possession of the Wisconsin Veterans Museums). SIX COTTAGES. VIEW UNKNOWN. - Wisconsin Home for Veterans, King, Waupaca County, WI

8. Photographic copy of photograph (date unknown, original print in ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

8. Photographic copy of photograph (date unknown, original print in the possession of the Wisconsin Veterans Museums). SEVEN COTTAGES. VIEW UNKNOWN. - Wisconsin Home for Veterans, King, Waupaca County, WI

7 CFR 718.304 - Failure to fully comply.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 7 2013-01-01 2013-01-01 false Failure to fully comply. 718.304 Section 718.304... MULTIPLE PROGRAMS Equitable Relief From Ineligibility § 718.304 Failure to fully comply. (a) Under a covered program, when the failure of a participant to fully comply with the terms and conditions of a...

7 CFR 718.304 - Failure to fully comply.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 7 2014-01-01 2014-01-01 false Failure to fully comply. 718.304 Section 718.304... MULTIPLE PROGRAMS Equitable Relief From Ineligibility § 718.304 Failure to fully comply. (a) Under a covered program, when the failure of a participant to fully comply with the terms and conditions of a...

7 CFR 718.304 - Failure to fully comply.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 7 2012-01-01 2012-01-01 false Failure to fully comply. 718.304 Section 718.304... MULTIPLE PROGRAMS Equitable Relief From Ineligibility § 718.304 Failure to fully comply. (a) Under a covered program, when the failure of a participant to fully comply with the terms and conditions of a...

Fully printed flexible fingerprint-like three-axis tactile and slip force and temperature sensors for artificial skin.

PubMed

Harada, Shingo; Kanao, Kenichiro; Yamamoto, Yuki; Arie, Takayuki; Akita, Seiji; Takei, Kuniharu

2014-12-23

A three-axis tactile force sensor that determines the touch and slip/friction force may advance artificial skin and robotic applications by fully imitating human skin. The ability to detect slip/friction and tactile forces simultaneously allows unknown objects to be held in robotic applications. However, the functionalities of flexible devices have been limited to a tactile force in one direction due to difficulties fabricating devices on flexible substrates. Here we demonstrate a fully printed fingerprint-like three-axis tactile force and temperature sensor for artificial skin applications. To achieve economic macroscale devices, these sensors are fabricated and integrated using only printing methods. Strain engineering enables the strain distribution to be detected upon applying a slip/friction force. By reading the strain difference at four integrated force sensors for a pixel, both the tactile and slip/friction forces can be analyzed simultaneously. As a proof of concept, the high sensitivity and selectivity for both force and temperature are demonstrated using a 3×3 array artificial skin that senses tactile, slip/friction, and temperature. Multifunctional sensing components for a flexible device are important advances for both practical applications and basic research in flexible electronics.

Identification of vehicle suspension parameters by design optimization

NASA Astrophysics Data System (ADS)

Tey, J. Y.; Ramli, R.; Kheng, C. W.; Chong, S. Y.; Abidin, M. A. Z.

2014-05-01

The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.

Estimation of Ordinary Differential Equation Parameters Using Constrained Local Polynomial Regression

PubMed Central

Ding, A. Adam; Wu, Hulin

2015-01-01

We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unknown parameters in the differential equation model. We also derive the asymptotic bias and variance of the proposed estimator. Our simulation studies show that our new estimator is clearly better than the pseudo-least squares estimator in estimation accuracy with a small price of computational cost. An application example on immune cell kinetics and trafficking for influenza infection further illustrates the benefits of the proposed new method. PMID:26401093

Parameter Estimation for a Turbulent Buoyant Jet Using Approximate Bayesian Computation

NASA Astrophysics Data System (ADS)

Christopher, Jason D.; Wimer, Nicholas T.; Hayden, Torrey R. S.; Lapointe, Caelan; Grooms, Ian; Rieker, Gregory B.; Hamlington, Peter E.

2016-11-01

Approximate Bayesian Computation (ABC) is a powerful tool that allows sparse experimental or other "truth" data to be used for the prediction of unknown model parameters in numerical simulations of real-world engineering systems. In this presentation, we introduce the ABC approach and then use ABC to predict unknown inflow conditions in simulations of a two-dimensional (2D) turbulent, high-temperature buoyant jet. For this test case, truth data are obtained from a simulation with known boundary conditions and problem parameters. Using spatially-sparse temperature statistics from the 2D buoyant jet truth simulation, we show that the ABC method provides accurate predictions of the true jet inflow temperature. The success of the ABC approach in the present test suggests that ABC is a useful and versatile tool for engineering fluid dynamics research.

A review of the meteorological parameters which affect aerial application

NASA Technical Reports Server (NTRS)

Christensen, L. S.; Frost, W.

1979-01-01

The ambient wind field and temperature gradient were found to be the most important parameters. Investigation results indicated that the majority of meteorological parameters affecting dispersion were interdependent and the exact mechanism by which these factors influence the particle dispersion was largely unknown. The types and approximately ranges of instrumented capabilities for a systematic study of the significant meteorological parameters influencing aerial applications were defined. Current mathematical dispersion models were also briefly reviewed. Unfortunately, a rigorous dispersion model which could be applied to aerial application was not available.

IMPLEMENTATION AND VALIDATION OF A FULLY IMPLICIT ACCUMULATOR MODEL IN RELAP-7

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

Zhao, Haihua; Zou, Ling; Zhang, Hongbin

2016-01-01

This paper presents the implementation and validation of an accumulator model in RELAP-7 under the framework of preconditioned Jacobian free Newton Krylov (JFNK) method, based on the similar model used in RELAP5. RELAP-7 is a new nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). RELAP-7 is a fully implicit system code. The JFNK and preconditioning methods used in RELAP-7 is briefly discussed. The slightly modified accumulator model is summarized for completeness. The implemented model was validated with LOFT L3-1 test and benchmarked with RELAP5 results. RELAP-7 and RELAP5 had almost identical results for themore » accumulator gas pressure and water level, although there were some minor difference in other parameters such as accumulator gas temperature and tank wall temperature. One advantage of the JFNK method is its easiness to maintain and modify models due to fully separation of numerical methods from physical models. It would be straightforward to extend the current RELAP-7 accumulator model to simulate the advanced accumulator design.« less

A novel KFCM based fault diagnosis method for unknown faults in satellite reaction wheels.

PubMed

Hu, Di; Sarosh, Ali; Dong, Yun-Feng

2012-03-01

Reaction wheels are one of the most critical components of the satellite attitude control system, therefore correct diagnosis of their faults is quintessential for efficient operation of these spacecraft. The known faults in any of the subsystems are often diagnosed by supervised learning algorithms, however, this method fails to work correctly when a new or unknown fault occurs. In such cases an unsupervised learning algorithm becomes essential for obtaining the correct diagnosis. Kernel Fuzzy C-Means (KFCM) is one of the unsupervised algorithms, although it has its own limitations; however in this paper a novel method has been proposed for conditioning of KFCM method (C-KFCM) so that it can be effectively used for fault diagnosis of both known and unknown faults as in satellite reaction wheels. The C-KFCM approach involves determination of exact class centers from the data of known faults, in this way discrete number of fault classes are determined at the start. Similarity parameters are derived and determined for each of the fault data point. Thereafter depending on the similarity threshold each data point is issued with a class label. The high similarity points fall into one of the 'known-fault' classes while the low similarity points are labeled as 'unknown-faults'. Simulation results show that as compared to the supervised algorithm such as neural network, the C-KFCM method can effectively cluster historical fault data (as in reaction wheels) and diagnose the faults to an accuracy of more than 91%. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

46. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

46. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angeles, CA, Photographer, Date unknown NORTH ELEVATION - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

47. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

47. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angleles, CA, Photographer, Date unknown WEST ELEVATION - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

1. Historic American Buildings Survey Photographer Unknown. Furnished by Mrs ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

1. Historic American Buildings Survey Photographer Unknown. Furnished by Mrs Mecia, Tombstone, Arizona. Date Unknown GENERAL VIEW MAIN CHURCH (SOUTHEAST ELEVATION). - San Xavier del Bac Mission, Mission Road, Tucson, Pima County, AZ

Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

PubMed

Sokoloski, Sacha

2017-09-01

In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

44. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

44. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angeles, CA, Photographer, Date unknown FIRST FLOOR PLAN - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

45. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

45. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angeles, CA, Photographer, Date unknown SECOND FLOOR PLAN - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

51. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

51. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angeles, CA, Photographer, Date unknown EXTERIOR, ELEVATION DETAILS - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

4. Photographic copy of photograph (date unknown, original print in ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. Photographic copy of photograph (date unknown, original print in the possession of the Wisconsin Veterans Museums). COTTAGES WITH DIRT ROAD IN FOREGROUND. LOCATION UNKNOWN. - Wisconsin Home for Veterans, King, Waupaca County, WI

A Priori Method of Using Photon Activation Analysis to Determine Unknown Trace Element Concentrations in NIST Standards

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

Green, Jaromy; Sun Zaijing; Wells, Doug

2009-03-10

Photon activation analysis detected elements in two NIST standards that did not have reported concentration values. A method is currently being developed to infer these concentrations by using scaling parameters and the appropriate known quantities within the NIST standard itself. Scaling parameters include: threshold, peak and endpoint energies; photo-nuclear cross sections for specific isotopes; Bremstrahlung spectrum; target thickness; and photon flux. Photo-nuclear cross sections and energies from the unknown elements must also be known. With these quantities, the same integral was performed for both the known and unknown elements resulting in an inference of the concentration of the un-reported elementmore » based on the reported value. Since Rb and Mn were elements that were reported in the standards, and because they had well-identified peaks, they were used as the standards of inference to determine concentrations of the unreported elements of As, I, Nb, Y, and Zr. This method was tested by choosing other known elements within the standards and inferring a value based on the stated procedure. The reported value of Mn in the first NIST standard was 403{+-}15 ppm and the reported value of Ca in the second NIST standard was 87000 ppm (no reported uncertainty). The inferred concentrations were 370{+-}23 ppm and 80200{+-}8700 ppm respectively.« less

17. Photocopy of measured drawing (source unknown) 6 March 1945, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

17. Photocopy of measured drawing (source unknown) 6 March 1945, delineator unknown PROPOSED ADAPTIVE REUSE AS CLEMSON COLLEGE FACULTY CLUB, BASEMENT PLAN - Woodburn, Woodburn Road, U.S. Route 76 vicinity, Pendleton, Anderson County, SC

20. Photocopy of measured drawing (source unknown) 6 March 1945, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

20. Photocopy of measured drawing (source unknown) 6 March 1945, delineator unknown PROPOSED ADAPTIVE REUSE AS CLEMSON COLLEGE FACULTY CLUB, ATTIC PLAN - Woodburn, Woodburn Road, U.S. Route 76 vicinity, Pendleton, Anderson County, SC

21. Photocopy of maesured drawing (source unknown) 6 March 1945, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

21. Photocopy of maesured drawing (source unknown) 6 March 1945, delineator unknown PROPOSED ADAPTIVE REUSE AS CLEMSON COLLEGE FACULTY CLUB, SITE PLAN - Woodburn, Woodburn Road, U.S. Route 76 vicinity, Pendleton, Anderson County, SC

Parameter Estimation for a Pulsating Turbulent Buoyant Jet Using Approximate Bayesian Computation

NASA Astrophysics Data System (ADS)

Christopher, Jason; Wimer, Nicholas; Lapointe, Caelan; Hayden, Torrey; Grooms, Ian; Rieker, Greg; Hamlington, Peter

2017-11-01

Approximate Bayesian Computation (ABC) is a powerful tool that allows sparse experimental or other ``truth'' data to be used for the prediction of unknown parameters, such as flow properties and boundary conditions, in numerical simulations of real-world engineering systems. Here we introduce the ABC approach and then use ABC to predict unknown inflow conditions in simulations of a two-dimensional (2D) turbulent, high-temperature buoyant jet. For this test case, truth data are obtained from a direct numerical simulation (DNS) with known boundary conditions and problem parameters, while the ABC procedure utilizes lower fidelity large eddy simulations. Using spatially-sparse statistics from the 2D buoyant jet DNS, we show that the ABC method provides accurate predictions of true jet inflow parameters. The success of the ABC approach in the present test suggests that ABC is a useful and versatile tool for predicting flow information, such as boundary conditions, that can be difficult to determine experimentally.

49. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

49. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angeles, CA, Photographer, Date unknown SECTION THROUGH BUILDING, LOOKING EAST - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

48. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

48. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angeles, CA., Photographer, Date unknown SECTION THROUGH BUILDING, LOOKING NORTH - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

19. Photocopy of measured drawing (source unknown) 6 March 1945, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

19. Photocopy of measured drawing (source unknown) 6 March 1945, delineator unknown PROPOSED ADAPTIVE REUSE AS CLEMSON COLLEGE FACULTY CLUB, SECOND FLOOR PLAN - Woodburn, Woodburn Road, U.S. Route 76 vicinity, Pendleton, Anderson County, SC

18. Photocopy of measured drawing (source unknown) 6 March 1945, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

18. Photocopy of measured drawing (source unknown) 6 March 1945, delineator unknown PROPOSED ADAPTIVE REUSE AS CLEMSON COLLEGE FACULTY CLUB, FIRST FLOOR PLAN - Woodburn, Woodburn Road, U.S. Route 76 vicinity, Pendleton, Anderson County, SC

General Unknown Screening by Ion Trap LC/MS/MS

DTIC Science & Technology

2010-04-01

Subtitle 5 . Report Date April 2010 General Unknown Screening by Ion Trap LC/MS/MS 6 . Performing Organization Code 7. Author(s) 8... 5 Table 1: Analytical Data for Each of the...359 Compounds in the LC/MS/MS Library . . . . . . . . . . . 6 1 General Unknown ScreeninG by ion Trap lc/MS/MS INTrOduCTION The Federal Aviation

52. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

52. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angeles, CA, Photographer, Date unknown DETAILS OF MAIN FLOOR ELEVATOR LOBBY - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

53. Retail Pockets, Looking West, date unknown Historic Photograph, Photogapher ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

53. Retail Pockets, Looking West, date unknown Historic Photograph, Photogapher Unknown; Collection of William Everett, Jr. (Wilkes-Barre, PA), photocopy by Joseph E.B. Elliot - Huber Coal Breaker, 101 South Main Street, Ashley, Luzerne County, PA

50. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

50. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angleles, CA, Photographer, Date unknown ENTRANCE AND TYPICAL BAY ON FLOWER STREET - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

53. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

53. Photocopy of drawing (Source unknown, 1928) Rapid Blue Print Co., Los Angeles, CA, Photographer, Date unknown DETAILS OF CORRIDORS ON SECOND - TWELFTH FLOORS - Richfield Oil Building, 555 South Flower Street, Los Angeles, Los Angeles County, CA

A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.

PubMed

Tsai, Jason S-H; Hsu, Wen-Teng; Lin, Long-Guei; Guo, Shu-Mei; Tann, Joseph W

2014-01-01

A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input-output direct transmission term, which also has measurement and system noises and inaccessible system states. Besides, an effective state space self-turner with fault tolerance scheme is presented for the unknown multivariable stochastic system. A quantitative criterion is suggested by comparing the innovation process error estimated by the Kalman filter estimation algorithm, so that a weighting matrix resetting technique by adjusting and resetting the covariance matrices of parameter estimate obtained by the Kalman filter estimation algorithm is utilized to achieve the parameter estimation for faulty system recovery. Consequently, the proposed method can effectively cope with partially abrupt and/or gradual system faults and input failures by the fault detection. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Surface tension effects on fully developed liquid layer flow over a convex corner

NASA Astrophysics Data System (ADS)

Bhatti, Ifrah; Farid, Saadia; Ullah, Saif; Riaz, Samia; Faryad, Maimoona

2018-04-01

This investigation deals with the study of fully developed liquid layer flow along with surface tension effects, confronting a convex corner in the direction of fluid flow. At the point of interaction, the related equations are formulated using double deck structure and match asymptotic techniques. Linearized solutions for small angle are obtained analytically. The solutions corresponding to similar flow neglecting surface tension effects are also recovered as special case of our general solutions. Finally, the influence of pertinent parameters on the flow, as well as a comparison between models, are shown by graphical illustration.

GRID-BASED EXPLORATION OF COSMOLOGICAL PARAMETER SPACE WITH SNAKE

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

Mikkelsen, K.; Næss, S. K.; Eriksen, H. K., E-mail: kristin.mikkelsen@astro.uio.no

2013-11-10

We present a fully parallelized grid-based parameter estimation algorithm for investigating multidimensional likelihoods called Snake, and apply it to cosmological parameter estimation. The basic idea is to map out the likelihood grid-cell by grid-cell according to decreasing likelihood, and stop when a certain threshold has been reached. This approach improves vastly on the 'curse of dimensionality' problem plaguing standard grid-based parameter estimation simply by disregarding grid cells with negligible likelihood. The main advantages of this method compared to standard Metropolis-Hastings Markov Chain Monte Carlo methods include (1) trivial extraction of arbitrary conditional distributions; (2) direct access to Bayesian evidences; (3)more » better sampling of the tails of the distribution; and (4) nearly perfect parallelization scaling. The main disadvantage is, as in the case of brute-force grid-based evaluation, a dependency on the number of parameters, N{sub par}. One of the main goals of the present paper is to determine how large N{sub par} can be, while still maintaining reasonable computational efficiency; we find that N{sub par} = 12 is well within the capabilities of the method. The performance of the code is tested by comparing cosmological parameters estimated using Snake and the WMAP-7 data with those obtained using CosmoMC, the current standard code in the field. We find fully consistent results, with similar computational expenses, but shorter wall time due to the perfect parallelization scheme.« less

Demonstration of a fully differential VGA chip with small THD for ECG acquisition system

NASA Astrophysics Data System (ADS)

Gongli, Xiao; Yuliang, Qin; Weilin, Xu; Baolin, Wei; Jihai, Duan; Xueming, Wei

2015-10-01

We present both a theoretical and experimental demonstration of a fully differential variable gain amplifier (VGA) with small total harmonic distortion (THD) for an electrocardiogram (ECG) acquisition system. Capacitive feedback technology is adopted to reduce the nonlinearity of VGA. The fully differential VGA has been fabricated in SMIC 0.18-μm CMOS process, and it only occupies 0.11 mm2. The measurements are in good agreement with simulation results. Experimental results show that the gain of VGA changes from 6.17 to 43.75 dB with a gain step of 3 dB. The high-pass corner frequency and low-pass corner frequency are around 0.22 Hz and 7.9 kHz, respectively. For each gain configuration, a maximal THD of 0.13% is obtained. The fully differential VGA has a low THD and its key performance parameters are well satisfied with the demands of ECG acquisition system application in the UWB wireless body area network. Project supported by the National Natural Science Foundation of China (Nos. 61264001, 61465004, 61161003, 61166004), the Guangxi Natural Science Foundation (Nos. 2013GXNSFAA019333, 2013GXNSFAA019338), the Science and Technology Research Key Project of Guangxi Department of Education (No. 2013ZD026), and the Innovation Project of GUET Graduate Education (No. GDYCSZ201457).

Recovering an unknown source in a fractional diffusion problem

NASA Astrophysics Data System (ADS)

Rundell, William; Zhang, Zhidong

2018-09-01

A standard inverse problem is to determine a source which is supported in an unknown domain D from external boundary measurements. Here we consider the case of a time-independent situation where the source is equal to unity in an unknown subdomain D of a larger given domain Ω and the boundary of D has the star-like shape, i.e.

Variational formulation of hybrid problems for fully 3-D transonic flow with shocks in rotor

NASA Technical Reports Server (NTRS)

Liu, Gao-Lian

1991-01-01

Based on previous research, the unified variable domain variational theory of hybrid problems for rotor flow is extended to fully 3-D transonic rotor flow with shocks, unifying and generalizing the direct and inverse problems. Three variational principles (VP) families were established. All unknown boundaries and flow discontinuities (such as shocks, free trailing vortex sheets) are successfully handled via functional variations with variable domain, converting almost all boundary and interface conditions, including the Rankine Hugoniot shock relations, into natural ones. This theory provides a series of novel ways for blade design or modification and a rigorous theoretical basis for finite element applications and also constitutes an important part of the optimal design theory of rotor bladings. Numerical solutions to subsonic flow by finite elements with self-adapting nodes given in Refs., show good agreement with experimental results.

Quantum jointly assisted cloning of an unknown three-dimensional equatorial state

NASA Astrophysics Data System (ADS)

Ma, Peng-Cheng; Chen, Gui-Bin; Li, Xiao-Wei; Zhan, You-Bang

2018-02-01

We present two schemes for perfectly cloning an unknown single-qutrit equatorial state with assistance from two and N state preparers, respectively. In the first scheme, the sender wishes to teleport an unknown single-qutrit equatorial state from two state preparers to a remote receiver, and then to create a perfect copy of the unknown state at her location. The scheme consists of two stages. The first stage of the scheme requires the usual teleportation. In the second stage, to help the sender realize the quantum cloning, two state preparers perform single-qutrit projective measurements on their own qutrits from the sender, then the sender can acquire a perfect copy of the unknown state. It is shown that, only if the two state preparers collaborate with each other, the sender can create a copy of the unknown state by means of some appropriate unitary operations. In the second scheme, we generalized the jointly assisted cloning in the first scheme to the case of N state prepares. In the present schemes, the total probability of success for assisted cloning of a perfect copy of the unknown state can reach 1.

Mechanical Fluidity of Fully Suspended Biological Cells

PubMed Central

Maloney, John M.; Lehnhardt, Eric; Long, Alexandra F.; Van Vliet, Krystyn J.

2013-01-01

Mechanical characteristics of single biological cells are used to identify and possibly leverage interesting differences among cells or cell populations. Fluidity—hysteresivity normalized to the extremes of an elastic solid or a viscous liquid—can be extracted from, and compared among, multiple rheological measurements of cells: creep compliance versus time, complex modulus versus frequency, and phase lag versus frequency. With multiple strategies available for acquisition of this nondimensional property, fluidity may serve as a useful and robust parameter for distinguishing cell populations, and for understanding the physical origins of deformability in soft matter. Here, for three disparate eukaryotic cell types deformed in the suspended state via optical stretching, we examine the dependence of fluidity on chemical and environmental influences at a timescale of ∼1 s. We find that fluidity estimates are consistent in the time and frequency domains under a structural damping (power-law or fractional-derivative) model, but not under an equivalent-complexity, lumped-component (spring-dashpot) model; the latter predicts spurious time constants. Although fluidity is suppressed by chemical cross-linking, we find that ATP depletion in the cell does not measurably alter the parameter, and we thus conclude that active ATP-driven events are not a crucial enabler of fluidity during linear viscoelastic deformation of a suspended cell. Finally, by using the capacity of optical stretching to produce near-instantaneous increases in cell temperature, we establish that fluidity increases with temperature—now measured in a fully suspended, sortable cell without the complicating factor of cell-substratum adhesion. PMID:24138852

Nonlinear interaction between underwater explosion bubble and structure based on fully coupled model

NASA Astrophysics Data System (ADS)

Zhang, A. M.; Wu, W. B.; Liu, Y. L.; Wang, Q. X.

2017-08-01

The interaction between an underwater explosion bubble and an elastic-plastic structure is a complex transient process, accompanying violent bubble collapsing, jet impact, penetration through the bubble, and large structural deformation. In the present study, the bubble dynamics are modeled using the boundary element method and the nonlinear transient structural response is modeled using the explicit finite element method. A new fully coupled 3D model is established through coupling the equations for the state variables of the fluid and structure and solving them as a set of coupled linear algebra equations. Based on the acceleration potential theory, the mutual dependence between the hydrodynamic load and the structural motion is decoupled. The pressure distribution in the flow field is calculated with the Bernoulli equation, where the partial derivative of the velocity potential in time is calculated using the boundary integral method to avoid numerical instabilities. To validate the present fully coupled model, the experiments of small-scale underwater explosion near a stiffened plate are carried out. High-speed imaging is used to capture the bubble behaviors and strain gauges are used to measure the strain response. The numerical results correspond well with the experimental data, in terms of bubble shapes and structural strain response. By both the loosely coupled model and the fully coupled model, the interaction between a bubble and a hollow spherical shell is studied. The bubble patterns vary with different parameters. When the fully coupled model and the loosely coupled model are advanced with the same time step, the error caused by the loosely coupled model becomes larger with the coupling effect becoming stronger. The fully coupled model is more stable than the loosely coupled model. Besides, the influences of the internal fluid on the dynamic response of the spherical shell are studied. At last, the case that the bubble interacts with an air

Theoretical effects of fully ductile versus fully brittle behaviors of bone tissue on the strength of the human proximal femur and vertebral body.

PubMed

Nawathe, Shashank; Yang, Haisheng; Fields, Aaron J; Bouxsein, Mary L; Keaveny, Tony M

2015-05-01

The influence of the ductility of bone tissue on whole-bone strength represents a fundamental issue of multi-scale biomechanics. To gain insight, we performed a computational study of 16 human proximal femurs and 12 T9 vertebral bodies, comparing the whole-bone strength for the two hypothetical bounding cases of fully brittle versus fully ductile tissue-level failure behaviors, all other factors, including tissue-level elastic modulus and yield stress, held fixed. For each bone, a finite element model was generated (60-82 μm element size; up to 120 million elements) and was virtually loaded in habitual (stance for femur, compression for vertebra) and non-habitual (sideways fall, only for femur) loading modes. Using a geometrically and materially non-linear model, the tissue was assumed to be either fully brittle or fully ductile. We found that, under habitual loading, changing the tissue behavior from fully ductile to fully brittle reduced whole-bone strength by 38.3±2.4% (mean±SD) and 39.4±1.9% for the femur and vertebra, respectively (p=0.39 for site difference). These reductions were remarkably uniform across bones, but (for the femur) were greater for non-habitual (57.1±4.7%) than habitual loading (p<0.001). At overall structural failure, there was 5-10-fold less failed tissue for the fully brittle than fully ductile cases. These theoretical results suggest that the whole-bone strength of the proximal femur and vertebra can vary substantially between fully brittle and fully ductile tissue-level behaviors, an effect that is relatively insensitive to bone morphology but greater for non-habitual loading. Copyright © 2015 Elsevier Ltd. All rights reserved.

Method for identifying known materials within a mixture of unknowns

DOEpatents

Wagner, John S.

2000-01-01

One or both of two methods and systems are used to determine concentration of a known material in an unknown mixture on the basis of the measured interaction of electromagnetic waves upon the mixture. One technique is to utilize a multivariate analysis patch technique to develop a library of optimized patches of spectral signatures of known materials containing only those pixels most descriptive of the known materials by an evolutionary algorithm. Identity and concentration of the known materials within the unknown mixture is then determined by minimizing the residuals between the measurements from the library of optimized patches and the measurements from the same pixels from the unknown mixture. Another technique is to train a neural network by the genetic algorithm to determine the identity and concentration of known materials in the unknown mixture. The two techniques may be combined into an expert system providing cross checks for accuracy.

System for identifying known materials within a mixture of unknowns

DOEpatents

Wagner, John S.

1999-01-01

One or both of two methods and systems are used to determine concentration of a known material in an unknown mixture on the basis of the measured interaction of electromagnetic waves upon the mixture. One technique is to utilize a multivariate analysis patch technique to develop a library of optimized patches of spectral signatures of known materials containing only those pixels most descriptive of the known materials by an evolutionary algorithm. Identity and concentration of the known materials within the unknown mixture is then determined by minimizing the residuals between the measurements from the library of optimized patches and the measurements from the same pixels from the unknown mixture. Another technique is to train a neural network by the genetic algorithm to determine the identity and concentration of known materials in the unknown mixture. The two techniques may be combined into an expert system providing cross checks for accuracy.

System for identifying known materials within a mixture of unknowns

DOEpatents

Wagner, J.S.

1999-07-20

One or both of two methods and systems are used to determine concentration of a known material in an unknown mixture on the basis of the measured interaction of electromagnetic waves upon the mixture. One technique is to utilize a multivariate analysis patch technique to develop a library of optimized patches of spectral signatures of known materials containing only those pixels most descriptive of the known materials by an evolutionary algorithm. Identity and concentration of the known materials within the unknown mixture is then determined by minimizing the residuals between the measurements from the library of optimized patches and the measurements from the same pixels from the unknown mixture. Another technique is to train a neural network by the genetic algorithm to determine the identity and concentration of known materials in the unknown mixture. The two techniques may be combined into an expert system providing cross checks for accuracy. 37 figs.

Scalable implicit incompressible resistive MHD with stabilized FE and fully-coupled Newton–Krylov-AMG

DOE PAGES

Shadid, J. N.; Pawlowski, R. P.; Cyr, E. C.; ...

2016-02-10

Here, we discuss that the computational solution of the governing balance equations for mass, momentum, heat transfer and magnetic induction for resistive magnetohydrodynamics (MHD) systems can be extremely challenging. These difficulties arise from both the strong nonlinear, nonsymmetric coupling of fluid and electromagnetic phenomena, as well as the significant range of time- and length-scales that the interactions of these physical mechanisms produce. This paper explores the development of a scalable, fully-implicit stabilized unstructured finite element (FE) capability for 3D incompressible resistive MHD. The discussion considers the development of a stabilized FE formulation in context of the variational multiscale (VMS) method,more » and describes the scalable implicit time integration and direct-to-steady-state solution capability. The nonlinear solver strategy employs Newton–Krylov methods, which are preconditioned using fully-coupled algebraic multilevel preconditioners. These preconditioners are shown to enable a robust, scalable and efficient solution approach for the large-scale sparse linear systems generated by the Newton linearization. Verification results demonstrate the expected order-of-accuracy for the stabilized FE discretization. The approach is tested on a variety of prototype problems, that include MHD duct flows, an unstable hydromagnetic Kelvin–Helmholtz shear layer, and a 3D island coalescence problem used to model magnetic reconnection. Initial results that explore the scaling of the solution methods are also presented on up to 128K processors for problems with up to 1.8B unknowns on a CrayXK7.« less

Fully nonlinear theory of transcritical shallow-water flow past topography

NASA Astrophysics Data System (ADS)

El, Gennady; Grimshaw, Roger; Smyth, Noel

2010-05-01

In this talk recent results on the generation of undular bores in one-dimensional fully nonlinear shallow-water flows past localised topographies will be presented. The description is made in the framework of the forced Su-Gardner (a.k.a. 1D Green-Naghdi) system of equations, with a primary focus on the transcritical regime when the Froude number of the oncoming flow is close to unity. A combination of the local transcritical hydraulic solution over the localized topography, which produces upstream and downstream hydraulic jumps, and unsteady undular bore solutions describing the resolution of these hydraulic jumps, is used to describe various flow regimes depending on the combination of the topography height and the Froude number. We take advantage of the recently developed modulation theory of Su-Gardner undular bores to derive the main parameters of transcritical fully nonlinear shallow-water flow, such as the leading solitary wave amplitudes for the upstream and downstream undular bores, the speeds of the undular bores edges and the drag force. Our results confirm that most of the features of the previously developed description in the framework of the uni-directional forced KdV model hold up qualitatively for finite amplitude waves, while the quantitative description can be obtained in the framework of the bi-directional forced Su-Gardner system.

Fully implicit moving mesh adaptive algorithm

NASA Astrophysics Data System (ADS)

Chacon, Luis

2005-10-01

In many problems of interest, the numerical modeler is faced with the challenge of dealing with multiple time and length scales. The former is best dealt with with fully implicit methods, which are able to step over fast frequencies to resolve the dynamical time scale of interest. The latter requires grid adaptivity for efficiency. Moving-mesh grid adaptive methods are attractive because they can be designed to minimize the numerical error for a given resolution. However, the required grid governing equations are typically very nonlinear and stiff, and of considerably difficult numerical treatment. Not surprisingly, fully coupled, implicit approaches where the grid and the physics equations are solved simultaneously are rare in the literature, and circumscribed to 1D geometries. In this study, we present a fully implicit algorithm for moving mesh methods that is feasible for multidimensional geometries. A crucial element is the development of an effective multilevel treatment of the grid equation.ootnotetextL. Chac'on, G. Lapenta, A fully implicit, nonlinear adaptive grid strategy, J. Comput. Phys., accepted (2005) We will show that such an approach is competitive vs. uniform grids both from the accuracy (due to adaptivity) and the efficiency standpoints. Results for a variety of models 1D and 2D geometries, including nonlinear diffusion, radiation-diffusion, Burgers equation, and gas dynamics will be presented.

Sequencing the Unknown

NASA Image and Video Library

2017-12-19

Being able to identify microbes in real time aboard the International Space Station, without having to send them back to Earth for identification first, would be revolutionary for the world of microbiology and space exploration, and the Genes in Space-3 team turned that possibility into a reality this year when it completed the first-ever sample-to-sequence process entirely aboard the space station. This advance could aid in the ability to diagnose and treat astronaut ailments in real time, as well as assisting in the identification of DNA-based life on other planets. It could also benefit other experiments aboard the orbiting laboratory. HD Download: https://archive.org/details/jsc2017m001160_Sequencing_the_Unknown _______________________________________ FOLLOW THE SPACE STATION! Twitter: https://twitter.com/Space_Station Facebook: https://www.facebook.com/ISS Instagram: https://instagram.com/iss/

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

[Fully implantable hearing systems].

PubMed

Maurer, J

2009-03-01

As yet comparatively little experience has been gained with fully implantable hearing systems, as the two systems available at present have only recently received CE permission for Europe and the FDA permissions are still pending in the USA. Additionally the technology is expensive and usually not covered by insurance companies. However, it could be shown that by careful patient selection and very careful surgical techniques, good results can be achieved with this highly sensitive technology, often with better patient satisfaction and hearing quality than with conventional hearing aids. To spread the technology further, the systems must also show reliable results on a broad application. Further surgery to change the batteries should not be necessary more frequently than with cardiac pacemakers. Not all technical problems are finally solved. However, it is to be foreseen that fully implantable hearing systems will be a good long-term alternative to conventional hearing aids for some patients.

Fully integrated biochip platforms for advanced healthcare.

PubMed

Carrara, Sandro; Ghoreishizadeh, Sara; Olivo, Jacopo; Taurino, Irene; Baj-Rossi, Camilla; Cavallini, Andrea; de Beeck, Maaike Op; Dehollain, Catherine; Burleson, Wayne; Moussy, Francis Gabriel; Guiseppi-Elie, Anthony; De Micheli, Giovanni

2012-01-01

Recent advances in microelectronics and biosensors are enabling developments of innovative biochips for advanced healthcare by providing fully integrated platforms for continuous monitoring of a large set of human disease biomarkers. Continuous monitoring of several human metabolites can be addressed by using fully integrated and minimally invasive devices located in the sub-cutis, typically in the peritoneal region. This extends the techniques of continuous monitoring of glucose currently being pursued with diabetic patients. However, several issues have to be considered in order to succeed in developing fully integrated and minimally invasive implantable devices. These innovative devices require a high-degree of integration, minimal invasive surgery, long-term biocompatibility, security and privacy in data transmission, high reliability, high reproducibility, high specificity, low detection limit and high sensitivity. Recent advances in the field have already proposed possible solutions for several of these issues. The aim of the present paper is to present a broad spectrum of recent results and to propose future directions of development in order to obtain fully implantable systems for the continuous monitoring of the human metabolism in advanced healthcare applications.

Statistical inference involving binomial and negative binomial parameters.

PubMed

García-Pérez, Miguel A; Núñez-Antón, Vicente

2009-05-01

Statistical inference about two binomial parameters implies that they are both estimated by binomial sampling. There are occasions in which one aims at testing the equality of two binomial parameters before and after the occurrence of the first success along a sequence of Bernoulli trials. In these cases, the binomial parameter before the first success is estimated by negative binomial sampling whereas that after the first success is estimated by binomial sampling, and both estimates are related. This paper derives statistical tools to test two hypotheses, namely, that both binomial parameters equal some specified value and that both parameters are equal though unknown. Simulation studies are used to show that in small samples both tests are accurate in keeping the nominal Type-I error rates, and also to determine sample size requirements to detect large, medium, and small effects with adequate power. Additional simulations also show that the tests are sufficiently robust to certain violations of their assumptions.

Estimation of time- and state-dependent delays and other parameters in functional differential equations

NASA Technical Reports Server (NTRS)

Murphy, K. A.

1988-01-01

A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.

Estimation of time- and state-dependent delays and other parameters in functional differential equations

NASA Technical Reports Server (NTRS)

Murphy, K. A.

1990-01-01

A parameter estimation algorithm is developed which can be used to estimate unknown time- or state-dependent delays and other parameters (e.g., initial condition) appearing within a nonlinear nonautonomous functional differential equation. The original infinite dimensional differential equation is approximated using linear splines, which are allowed to move with the variable delay. The variable delays are approximated using linear splines as well. The approximation scheme produces a system of ordinary differential equations with nice computational properties. The unknown parameters are estimated within the approximating systems by minimizing a least-squares fit-to-data criterion. Convergence theorems are proved for time-dependent delays and state-dependent delays within two classes, which say essentially that fitting the data by using approximations will, in the limit, provide a fit to the data using the original system. Numerical test examples are presented which illustrate the method for all types of delay.

FDG PET detection of unknown primary tumors.

PubMed

Bohuslavizki, K H; Klutmann, S; Kröger, S; Sonnemann, U; Buchert, R; Werner, J A; Mester, J; Clausen, M

2000-05-01

The management of patients presenting with metastases of unknown primary origin remains a clinical challenge despite a large variety of imaging modalities. The aim of this study was to evaluate FDG PET in detecting the sites of primary cancer in these patients. Fifty-three patients with metastatic cervical adenopathy (n = 44) or extracervical metastases (n = 9) of unknown primary origin were included after extensive but inconclusive conventional diagnostic work-up. Patients received 370 MBq FDG (10 mCi) intravenously, and whole-body images were acquired at 60 min after injection. Clinical, surgical, and histopathologic findings and complete correlative imaging were used to assess the results. In 27 of 53 patients FDG PET showed focal tracer accumulations corresponding to potential primary tumor sites located in the lungs (n = 12), the palatine tonsil (n = 5), the salivary glands (n = 2), the nasopharynx (n = 1), the oropharynx (n = 3), the maxillary sinus (n = 1), and the larynx (n = 1). Moreover, in 2 patients FDG PET revealed lesions suspected to be tumors in the breast and the ileocolonic area. In 20 (37.8%) of these 53 patients FDG PET was true-positive, identifying the primary tumor in the lungs (n = 10), the head and neck region (n = 8), the breast (n = 1), and the ileocolonic area (n = 1). In 6 of 27 patients FDG PET was false-positive, predominantly identifying suspicious areas in the palatine tonsil (n = 3). One patient denied further diagnostic work-up after PET; thus, positive PET could not be evaluated. In 26 of 53 patients PET did not reveal lesions suspected to be the primary. However, primary tumors were not found in these patients at clinical follow-up. FDG PET is a valuable diagnostic tool in patients with cancer of unknown primary because it imaged unknown primary tumors in about one third of all patients investigated. In addition, FDG PET assists in both guiding biopsies for histologic evaluation and selecting the appropriate treatment protocols

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

PubMed

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

2017-10-03

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

Off-Policy Actor-Critic Structure for Optimal Control of Unknown Systems With Disturbances.

PubMed

Song, Ruizhuo; Lewis, Frank L; Wei, Qinglai; Zhang, Huaguang

2016-05-01

An optimal control method is developed for unknown continuous-time systems with unknown disturbances in this paper. The integral reinforcement learning (IRL) algorithm is presented to obtain the iterative control. Off-policy learning is used to allow the dynamics to be completely unknown. Neural networks are used to construct critic and action networks. It is shown that if there are unknown disturbances, off-policy IRL may not converge or may be biased. For reducing the influence of unknown disturbances, a disturbances compensation controller is added. It is proven that the weight errors are uniformly ultimately bounded based on Lyapunov techniques. Convergence of the Hamiltonian function is also proven. The simulation study demonstrates the effectiveness of the proposed optimal control method for unknown systems with disturbances.

A fully electric field driven scalable magnetoelectric switching element

NASA Astrophysics Data System (ADS)

Ahmed, R.; Victora, R. H.

2018-04-01

A technique for micromagnetic simulation of the magnetoelectric (ME) effect in Cr2O3 based structures has been developed. It has been observed that the microscopic ME susceptibility differs significantly from the experimentally measured values. The deviation between the two susceptibilities becomes more prominent near the Curie temperature, affecting the operation of the device at room temperature. A fully electric field controlled ME switching element has been proposed for use at technologically interesting densities: it employs quantum mechanical exchange at the boundaries instead of the applied magnetic field needed in traditional switching schemes. After establishing temperature dependent physics-based parameters, switching performances have been studied for different temperatures, applied electric fields, and Cr2O3 cross-sections. It has been found that our proposed use of quantum mechanical exchange favors reduced electric field operation and enhanced scalability while retaining reliable thermal stability.

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

NASA Astrophysics Data System (ADS)

Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

2014-12-01

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached.

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model

PubMed Central

Boulton, Chris A.; Allison, Lesley C.; Lenton, Timothy M.

2014-01-01

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached. PMID:25482065

Early warning signals of Atlantic Meridional Overturning Circulation collapse in a fully coupled climate model.

PubMed

Boulton, Chris A; Allison, Lesley C; Lenton, Timothy M

2014-12-08

The Atlantic Meridional Overturning Circulation (AMOC) exhibits two stable states in models of varying complexity. Shifts between alternative AMOC states are thought to have played a role in past abrupt climate changes, but the proximity of the climate system to a threshold for future AMOC collapse is unknown. Generic early warning signals of critical slowing down before AMOC collapse have been found in climate models of low and intermediate complexity. Here we show that early warning signals of AMOC collapse are present in a fully coupled atmosphere-ocean general circulation model, subject to a freshwater hosing experiment. The statistical significance of signals of increasing lag-1 autocorrelation and variance vary with latitude. They give up to 250 years warning before AMOC collapse, after ~550 years of monitoring. Future work is needed to clarify suggested dynamical mechanisms driving critical slowing down as the AMOC collapse is approached.

Minimal-Approximation-Based Distributed Consensus Tracking of a Class of Uncertain Nonlinear Multiagent Systems With Unknown Control Directions.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2017-03-28

A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.

[Badminton--unknown sport].

PubMed

Zekan-Petrinović, Lidija

2007-01-01

For a long time, badminton was considered to be only a slow and light game for children, a game that is played outdoors and is structurally undemanding.Today, it is not an unknown and unrecognised sport, especially after it was included into the Olympics Games in 1992. Badminton is one of the oldest sports in the world. It is suitable for all ages (for children and elderly equally), women and men and even handicapped persons. Beginners can start playing badminton matches early because the basics are learned quickly. As a recreational activity, badminton is very popular in Zagreb. In the last 10 years, a number of halls specialized for badminton or offering badminton as one of available sports activities have been opened in Zagreb. At present, there are over 70 professional playgrounds for training of top contestants but also for the citizens who can play recreational badminton.

Fully invariant wavelet enhanced minimum average correlation energy filter for object recognition in cluttered and occluded environments

NASA Astrophysics Data System (ADS)

Tehsin, Sara; Rehman, Saad; Riaz, Farhan; Saeed, Omer; Hassan, Ali; Khan, Muazzam; Alam, Muhammad S.

2017-05-01

A fully invariant system helps in resolving difficulties in object detection when camera or object orientation and position are unknown. In this paper, the proposed correlation filter based mechanism provides the capability to suppress noise, clutter and occlusion. Minimum Average Correlation Energy (MACE) filter yields sharp correlation peaks while considering the controlled correlation peak value. Difference of Gaussian (DOG) Wavelet has been added at the preprocessing stage in proposed filter design that facilitates target detection in orientation variant cluttered environment. Logarithmic transformation is combined with a DOG composite minimum average correlation energy filter (WMACE), capable of producing sharp correlation peaks despite any kind of geometric distortion of target object. The proposed filter has shown improved performance over some of the other variant correlation filters which are discussed in the result section.

Quantum key distribution with an unknown and untrusted source

NASA Astrophysics Data System (ADS)

Zhao, Yi; Qi, Bing; Lo, Hoi-Kwong

2008-05-01

The security of a standard bidirectional “plug-and-play” quantum key distribution (QKD) system has been an open question for a long time. This is mainly because its source is equivalently controlled by an eavesdropper, which means the source is unknown and untrusted. Qualitative discussion on this subject has been made previously. In this paper, we solve this question directly by presenting the quantitative security analysis on a general class of QKD protocols whose sources are unknown and untrusted. The securities of standard Bennett-Brassard 1984 protocol, weak+vacuum decoy state protocol, and one-decoy state protocol, with unknown and untrusted sources are rigorously proved. We derive rigorous lower bounds to the secure key generation rates of the above three protocols. Our numerical simulation results show that QKD with an untrusted source gives a key generation rate that is close to that with a trusted source.

39 CFR 946.4 - Disposition of property of unknown owners.

Code of Federal Regulations, 2010 CFR

2010-07-01

... DISPOSITION OF STOLEN MAIL MATTER AND PROPERTY ACQUIRED BY THE POSTAL INSPECTION SERVICE FOR USE AS EVIDENCE § 946.4 Disposition of property of unknown owners. (a) Where no apparent owner of property subject to... 39 Postal Service 1 2010-07-01 2010-07-01 false Disposition of property of unknown owners. 946.4...

39 CFR 946.4 - Disposition of property of unknown owners.

Code of Federal Regulations, 2011 CFR

2011-07-01

... DISPOSITION OF STOLEN MAIL MATTER AND PROPERTY ACQUIRED BY THE POSTAL INSPECTION SERVICE FOR USE AS EVIDENCE § 946.4 Disposition of property of unknown owners. (a) Where no apparent owner of property subject to... 39 Postal Service 1 2011-07-01 2011-07-01 false Disposition of property of unknown owners. 946.4...

Fully Integrated Biochip Platforms for Advanced Healthcare

PubMed Central

Carrara, Sandro; Ghoreishizadeh, Sara; Olivo, Jacopo; Taurino, Irene; Baj-Rossi, Camilla; Cavallini, Andrea; de Beeck, Maaike Op; Dehollain, Catherine; Burleson, Wayne; Moussy, Francis Gabriel; Guiseppi-Elie, Anthony; De Micheli, Giovanni

2012-01-01

Recent advances in microelectronics and biosensors are enabling developments of innovative biochips for advanced healthcare by providing fully integrated platforms for continuous monitoring of a large set of human disease biomarkers. Continuous monitoring of several human metabolites can be addressed by using fully integrated and minimally invasive devices located in the sub-cutis, typically in the peritoneal region. This extends the techniques of continuous monitoring of glucose currently being pursued with diabetic patients. However, several issues have to be considered in order to succeed in developing fully integrated and minimally invasive implantable devices. These innovative devices require a high-degree of integration, minimal invasive surgery, long-term biocompatibility, security and privacy in data transmission, high reliability, high reproducibility, high specificity, low detection limit and high sensitivity. Recent advances in the field have already proposed possible solutions for several of these issues. The aim of the present paper is to present a broad spectrum of recent results and to propose future directions of development in order to obtain fully implantable systems for the continuous monitoring of the human metabolism in advanced healthcare applications. PMID:23112644

MXLKID: a maximum likelihood parameter identifier. [In LRLTRAN for CDC 7600

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

Gavel, D.T.

MXLKID (MaXimum LiKelihood IDentifier) is a computer program designed to identify unknown parameters in a nonlinear dynamic system. Using noisy measurement data from the system, the maximum likelihood identifier computes a likelihood function (LF). Identification of system parameters is accomplished by maximizing the LF with respect to the parameters. The main body of this report briefly summarizes the maximum likelihood technique and gives instructions and examples for running the MXLKID program. MXLKID is implemented LRLTRAN on the CDC7600 computer at LLNL. A detailed mathematical description of the algorithm is given in the appendices. 24 figures, 6 tables.

Fast grasping of unknown objects using principal component analysis

NASA Astrophysics Data System (ADS)

Lei, Qujiang; Chen, Guangming; Wisse, Martijn

2017-09-01

Fast grasping of unknown objects has crucial impact on the efficiency of robot manipulation especially subjected to unfamiliar environments. In order to accelerate grasping speed of unknown objects, principal component analysis is utilized to direct the grasping process. In particular, a single-view partial point cloud is constructed and grasp candidates are allocated along the principal axis. Force balance optimization is employed to analyze possible graspable areas. The obtained graspable area with the minimal resultant force is the best zone for the final grasping execution. It is shown that an unknown object can be more quickly grasped provided that the component analysis principle axis is determined using single-view partial point cloud. To cope with the grasp uncertainty, robot motion is assisted to obtain a new viewpoint. Virtual exploration and experimental tests are carried out to verify this fast gasping algorithm. Both simulation and experimental tests demonstrated excellent performances based on the results of grasping a series of unknown objects. To minimize the grasping uncertainty, the merits of the robot hardware with two 3D cameras can be utilized to suffice the partial point cloud. As a result of utilizing the robot hardware, the grasping reliance is highly enhanced. Therefore, this research demonstrates practical significance for increasing grasping speed and thus increasing robot efficiency under unpredictable environments.

Directly patching high-level exchange-correlation potential based on fully determined optimized effective potentials

NASA Astrophysics Data System (ADS)

Huang, Chen; Chi, Yu-Chieh

2017-12-01

The key element in Kohn-Sham (KS) density functional theory is the exchange-correlation (XC) potential. We recently proposed the exchange-correlation potential patching (XCPP) method with the aim of directly constructing high-level XC potential in a large system by patching the locally computed, high-level XC potentials throughout the system. In this work, we investigate the patching of the exact exchange (EXX) and the random phase approximation (RPA) correlation potentials. A major challenge of XCPP is that a cluster's XC potential, obtained by solving the optimized effective potential equation, is only determined up to an unknown constant. Without fully determining the clusters' XC potentials, the patched system's XC potential is "uneven" in the real space and may cause non-physical results. Here, we developed a simple method to determine this unknown constant. The performance of XCPP-RPA is investigated on three one-dimensional systems: H20, H10Li8, and the stretching of the H19-H bond. We investigated two definitions of EXX: (i) the definition based on the adiabatic connection and fluctuation dissipation theorem (ACFDT) and (ii) the Hartree-Fock (HF) definition. With ACFDT-type EXX, effective error cancellations were observed between the patched EXX and the patched RPA correlation potentials. Such error cancellations were absent for the HF-type EXX, which was attributed to the fact that for systems with fractional occupation numbers, the integral of the HF-type EXX hole is not -1. The KS spectra and band gaps from XCPP agree reasonably well with the benchmarks as we make the clusters large.

Two similar cases of elderly women with moderate abdominal pain and pneumoperitoneum of unknown origin: a surgeon's successful conservative management.

PubMed

Vinzens, Fabrizio; Zumstein, Valentin; Bieg, Christian; Ackermann, Christoph

2016-05-26

Patients presenting with abdominal pain and pneumoperitoneum in radiological examination usually require emergency explorative laparoscopy or laparotomy. Pneumoperitoneum mostly associates with gastrointestinal perforation. There are very few cases where surgery can be avoided. We present 2 cases of pneumoperitoneum with unknown origin and successful conservative treatment. Both patients were elderly women presenting to our emergency unit, with moderate abdominal pain. There was neither medical intervention nor trauma in their medical history. Physical examination revealed mild abdominal tenderness, but no clinical sign of peritonitis. Cardiopulmonary examination remained unremarkable. Blood studies showed only slight abnormalities, in particular, inflammation parameters were not significantly increased. Finally, obtained CTs showed free abdominal gas of unknown origin in both cases. We performed conservative management with nil per os, nasogastric tube, total parenteral nutrition and prophylactic antibiotics. After 2 weeks, both were discharged home. 2016 BMJ Publishing Group Ltd.

An eigenvalue approach for the automatic scaling of unknowns in model-based reconstructions: Application to real-time phase-contrast flow MRI.

PubMed

Tan, Zhengguo; Hohage, Thorsten; Kalentev, Oleksandr; Joseph, Arun A; Wang, Xiaoqing; Voit, Dirk; Merboldt, K Dietmar; Frahm, Jens

2017-12-01

The purpose of this work is to develop an automatic method for the scaling of unknowns in model-based nonlinear inverse reconstructions and to evaluate its application to real-time phase-contrast (RT-PC) flow magnetic resonance imaging (MRI). Model-based MRI reconstructions of parametric maps which describe a physical or physiological function require the solution of a nonlinear inverse problem, because the list of unknowns in the extended MRI signal equation comprises multiple functional parameters and all coil sensitivity profiles. Iterative solutions therefore rely on an appropriate scaling of unknowns to numerically balance partial derivatives and regularization terms. The scaling of unknowns emerges as a self-adjoint and positive-definite matrix which is expressible by its maximal eigenvalue and solved by power iterations. The proposed method is applied to RT-PC flow MRI based on highly undersampled acquisitions. Experimental validations include numerical phantoms providing ground truth and a wide range of human studies in the ascending aorta, carotid arteries, deep veins during muscular exercise and cerebrospinal fluid during deep respiration. For RT-PC flow MRI, model-based reconstructions with automatic scaling not only offer velocity maps with high spatiotemporal acuity and much reduced phase noise, but also ensure fast convergence as well as accurate and precise velocities for all conditions tested, i.e. for different velocity ranges, vessel sizes and the simultaneous presence of signals with velocity aliasing. In summary, the proposed automatic scaling of unknowns in model-based MRI reconstructions yields quantitatively reliable velocities for RT-PC flow MRI in various experimental scenarios. Copyright © 2017 John Wiley & Sons, Ltd.

FULLY COUPLED "ONLINE" CHEMISTRY WITHIN THE WRF MODEL

EPA Science Inventory

A fully coupled "online" Weather Research and Forecasting/Chemistry (WRF/Chem) model has been developed. The air quality component of the model is fully consistent with the meteorological component; both components use the same transport scheme (mass and scalar preserving), the s...

7 CFR 635.4 - Failure to fully comply.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 6 2014-01-01 2014-01-01 false Failure to fully comply. 635.4 Section 635.4..., DEPARTMENT OF AGRICULTURE LONG TERM CONTRACTING EQUITABLE RELIEF FROM INELIGIBILITY § 635.4 Failure to fully... damages or failure that were minor in nature. ...

7 CFR 635.4 - Failure to fully comply.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 6 2011-01-01 2011-01-01 false Failure to fully comply. 635.4 Section 635.4..., DEPARTMENT OF AGRICULTURE LONG TERM CONTRACTING EQUITABLE RELIEF FROM INELIGIBILITY § 635.4 Failure to fully... damages or failure that were minor in nature. ...

7 CFR 635.4 - Failure to fully comply.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 6 2012-01-01 2012-01-01 false Failure to fully comply. 635.4 Section 635.4..., DEPARTMENT OF AGRICULTURE LONG TERM CONTRACTING EQUITABLE RELIEF FROM INELIGIBILITY § 635.4 Failure to fully... damages or failure that were minor in nature. ...

Quantum key distribution with an unknown and untrusted source

NASA Astrophysics Data System (ADS)

Zhao, Yi; Qi, Bing; Lo, Hoi-Kwong

2009-03-01

The security of a standard bi-directional ``plug & play'' quantum key distribution (QKD) system has been an open question for a long time. This is mainly because its source is equivalently controlled by an eavesdropper, which means the source is unknown and untrusted. Qualitative discussion on this subject has been made previously. In this paper, we present the first quantitative security analysis on a general class of QKD protocols whose sources are unknown and untrusted. The securities of standard BB84 protocol, weak+vacuum decoy state protocol, and one-decoy decoy state protocol, with unknown and untrusted sources are rigorously proved. We derive rigorous lower bounds to the secure key generation rates of the above three protocols. Our numerical simulation results show that QKD with an untrusted source gives a key generation rate that is close to that with a trusted source. Our work is published in [1]. [4pt] [1] Y. Zhao, B. Qi, and H.-K. Lo, Phys. Rev. A, 77:052327 (2008).

Data Series Subtraction with Unknown and Unmodeled Background Noise

NASA Technical Reports Server (NTRS)

Vitale, Stefano; Congedo, Giuseppe; Dolesi, Rita; Ferroni, Valerio; Hueller, Mauro; Vetrugno, Daniele; Weber, William Joseph; Audley, Heather; Danzmann, Karsten; Diepholz, Ingo;

Optical phantoms with adjustable subdiffusive scattering parameters

NASA Astrophysics Data System (ADS)

Krauter, Philipp; Nothelfer, Steffen; Bodenschatz, Nico; Simon, Emanuel; Stocker, Sabrina; Foschum, Florian; Kienle, Alwin

2015-10-01

A new epoxy-resin-based optical phantom system with adjustable subdiffusive scattering parameters is presented along with measurements of the intrinsic absorption, scattering, fluorescence, and refractive index of the matrix material. Both an aluminium oxide powder and a titanium dioxide dispersion were used as scattering agents and we present measurements of their scattering and reduced scattering coefficients. A method is theoretically described for a mixture of both scattering agents to obtain continuously adjustable anisotropy values g between 0.65 and 0.9 and values of the phase function parameter γ in the range of 1.4 to 2.2. Furthermore, we show absorption spectra for a set of pigments that can be added to achieve particular absorption characteristics. By additional analysis of the aging, a fully characterized phantom system is obtained with the novelty of g and γ parameter adjustment.

Algorithm of probabilistic assessment of fully-mechanized longwall downtime

NASA Astrophysics Data System (ADS)

Domrachev, A. N.; Rib, S. V.; Govorukhin, Yu M.; Krivopalov, V. G.

2017-09-01

The problem of increasing the load on a long fully-mechanized longwall has several aspects, one of which is the improvement of efficiency in using available stoping equipment due to the increase in coefficient of the machine operating time of a shearer and other mining machines that form an integral part of the longwall set of equipment. The task of predicting the reliability indicators of stoping equipment is solved by the statistical evaluation of parameters of downtime exponential distribution and failure recovery. It is more difficult to solve the problems of downtime accounting in case of accidents in the face workings and, despite the statistical data on accidents in mine workings, no solution has been found to date. The authors have proposed a variant of probability assessment of workings caving using Poisson distribution and the duration of their restoration using normal distribution. The above results confirm the possibility of implementing the approach proposed by the authors.

Noise parameter estimation for poisson corrupted images using variance stabilization transforms.

PubMed

Jin, Xiaodan; Xu, Zhenyu; Hirakawa, Keigo

2014-03-01

Noise is present in all images captured by real-world image sensors. Poisson distribution is said to model the stochastic nature of the photon arrival process and agrees with the distribution of measured pixel values. We propose a method for estimating unknown noise parameters from Poisson corrupted images using properties of variance stabilization. With a significantly lower computational complexity and improved stability, the proposed estimation technique yields noise parameters that are comparable in accuracy to the state-of-art methods.

High brightness fully coherent x-ray amplifier seeded by a free-electron laser oscillator

NASA Astrophysics Data System (ADS)

Li, Kai; Yan, Jiawei; Feng, Chao; Zhang, Meng; Deng, Haixiao

2018-04-01

X-ray free-electron laser oscillator (XFELO) is expected to be a cutting-edge tool for fully coherent x-ray laser generation, and undulator taper technique is well-known for considerably increasing the efficiency of free-electron lasers (FELs). In order to combine the advantages of these two schemes, FEL amplifier seeded by XFELO is proposed by simply using a chirped electron beam. With the right choice of the beam parameters, the bunch tail is within the gain bandwidth of XFELO, and lase to saturation, which will be served as a seeding for further amplification. Meanwhile, the bunch head which is outside the gain bandwidth of XFELO, is preserved and used in the following FEL amplifier. It is found that the natural "double-horn" beam current, as well as residual energy chirp from chicane compressor, are quite suitable for the new scheme. Inheriting the advantages from XFELO seeding and undulator tapering, it is feasible to generate nearly terawatt level, fully coherent x-ray pulses with unprecedented shot-to-shot stability, which might open up new scientific opportunities in various research fields.

Erythropoietin Levels in Elderly Patients with Anemia of Unknown Etiology

PubMed Central

Sriram, Swetha; Martin, Alison; Xenocostas, Anargyros; Lazo-Langner, Alejandro

2016-01-01

Background In many elderly patients with anemia, a specific cause cannot be identified. This study investigates whether erythropoietin levels are inappropriately low in these cases of “anemia of unknown etiology” and whether this trend persists after accounting for confounders. Methods This study includes all anemic patients over 60 years old who had erythropoietin measured between 2005 and 2013 at a single center. Three independent reviewers used defined criteria to assign each patient’s anemia to one of ten etiologies: chronic kidney disease, iron deficiency, chronic disease, confirmed myelodysplastic syndrome (MDS), suspected MDS, vitamin B12 deficiency, folate deficiency, anemia of unknown etiology, other etiology, or multifactorial etiology. Iron deficiency anemia served as the comparison group in all analyses. We used linear regression to model the relationship between erythropoietin and the presence of each etiology, sequentially adding terms to the model to account for the hemoglobin concentration, estimated glomerular filtration rate (eGFR) and Charlson Comorbidity Index. Results A total of 570 patients met the inclusion criteria. Linear regression analysis showed that erythropoietin levels in chronic kidney disease, anemia of chronic disease and anemia of unknown etiology were lower by 48%, 46% and 27%, respectively, compared to iron deficiency anemia even after adjusting for hemoglobin, eGFR and comorbidities. Conclusions We have shown that erythropoietin levels are inappropriately low in anemia of unknown etiology, even after adjusting for confounders. This suggests that decreased erythropoietin production may play a key role in the pathogenesis of anemia of unknown etiology. PMID:27310832

7 CFR 718.304 - Failure to fully comply.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Failure to fully comply. 718.304 Section 718.304 Agriculture Regulations of the Department of Agriculture (Continued) FARM SERVICE AGENCY, DEPARTMENT OF... MULTIPLE PROGRAMS Equitable Relief From Ineligibility § 718.304 Failure to fully comply. (a) Under a...

7 CFR 718.304 - Failure to fully comply.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 7 2011-01-01 2011-01-01 false Failure to fully comply. 718.304 Section 718.304 Agriculture Regulations of the Department of Agriculture (Continued) FARM SERVICE AGENCY, DEPARTMENT OF... MULTIPLE PROGRAMS Equitable Relief From Ineligibility § 718.304 Failure to fully comply. (a) Under a...

Adaptive backstepping fault-tolerant control for flexible spacecraft with unknown bounded disturbances and actuator failures.

PubMed

Jiang, Ye; Hu, Qinglei; Ma, Guangfu

2010-01-01

In this paper, a robust adaptive fault-tolerant control approach to attitude tracking of flexible spacecraft is proposed for use in situations when there are reaction wheel/actuator failures, persistent bounded disturbances and unknown inertia parameter uncertainties. The controller is designed based on an adaptive backstepping sliding mode control scheme, and a sufficient condition under which this control law can render the system semi-globally input-to-state stable is also 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. Moreover, in the design, the control law does not need a fault detection and isolation mechanism even if the failure time instants, patterns and values on actuator failures are also unknown for the designers, as motivated from a practical spacecraft control application. In addition to detailed derivations of the new controller design and a rigorous sketch of all the associated stability and attitude error convergence proofs, illustrative simulation results of an application to flexible spacecraft show that high precise attitude control and vibration suppression are successfully achieved using various scenarios of controlling effective failures. 2009. Published by Elsevier Ltd.

8. VIEW SHOWING THE DEMOSSING OF GRAND CANAL LOCATION UNKNOWN. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

8. VIEW SHOWING THE DEMOSSING OF GRAND CANAL LOCATION UNKNOWN. AT TEAM OF HORSES ON OPPOSITE BANKS OF THE CANAL DRAG A CHAIN BETWEEN THEM ALONG THE BOTTOM OF THE CANAL, WHICH PULLS THE MOSS AND WEEDS LOOSE. THE PLANS THEN FLOAT DOWN THE CANAL AND ARE CAUGHT IN A SCREEN AND REMOVED. Photographer unknown, 1923 - Grand Canal, North side of Salt River, Tempe, Maricopa County, AZ

37 CFR 260.7 - Unknown copyright owners.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false Unknown copyright owners. 260.7 Section 260.7 Patents, Trademarks, and Copyrights COPYRIGHT OFFICE, LIBRARY OF CONGRESS COPYRIGHT ARBITRATION ROYALTY PANEL RULES AND PROCEDURES RATES AND TERMS FOR PREEXISTING SUBSCRIPTION SERVICES' DIGITAL...

37 CFR 260.7 - Unknown copyright owners.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Unknown copyright owners. 260.7 Section 260.7 Patents, Trademarks, and Copyrights COPYRIGHT OFFICE, LIBRARY OF CONGRESS COPYRIGHT ARBITRATION ROYALTY PANEL RULES AND PROCEDURES RATES AND TERMS FOR PREEXISTING SUBSCRIPTION SERVICES' DIGITAL...

37 CFR 260.7 - Unknown copyright owners.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Unknown copyright owners. 260.7 Section 260.7 Patents, Trademarks, and Copyrights COPYRIGHT OFFICE, LIBRARY OF CONGRESS COPYRIGHT ARBITRATION ROYALTY PANEL RULES AND PROCEDURES RATES AND TERMS FOR PREEXISTING SUBSCRIPTION SERVICES' DIGITAL...

37 CFR 382.7 - Unknown copyright owners.

Code of Federal Regulations, 2010 CFR

2010-07-01

....7 Section 382.7 Patents, Trademarks, and Copyrights COPYRIGHT ROYALTY BOARD, LIBRARY OF CONGRESS RATES AND TERMS FOR STATUTORY LICENSES RATES AND TERMS FOR DIGITAL TRANSMISSIONS OF SOUND RECORDINGS AND... SATELLITE DIGITAL AUDIO RADIO SERVICES Preexisting Subscription Services § 382.7 Unknown copyright owners...

37 CFR 260.7 - Unknown copyright owners.

Code of Federal Regulations, 2011 CFR

2011-07-01

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37 CFR 382.7 - Unknown copyright owners.

Code of Federal Regulations, 2012 CFR

2012-07-01

....7 Section 382.7 Patents, Trademarks, and Copyrights COPYRIGHT ROYALTY BOARD, LIBRARY OF CONGRESS RATES AND TERMS FOR STATUTORY LICENSES RATES AND TERMS FOR DIGITAL TRANSMISSIONS OF SOUND RECORDINGS AND... SATELLITE DIGITAL AUDIO RADIO SERVICES Preexisting Subscription Services § 382.7 Unknown copyright owners...

37 CFR 382.7 - Unknown copyright owners.

Code of Federal Regulations, 2011 CFR

2011-07-01

....7 Section 382.7 Patents, Trademarks, and Copyrights COPYRIGHT ROYALTY BOARD, LIBRARY OF CONGRESS RATES AND TERMS FOR STATUTORY LICENSES RATES AND TERMS FOR DIGITAL TRANSMISSIONS OF SOUND RECORDINGS AND... SATELLITE DIGITAL AUDIO RADIO SERVICES Preexisting Subscription Services § 382.7 Unknown copyright owners...

Molecular toolbox for the identification of unknown genetically modified organisms.

PubMed

Ruttink, Tom; Demeyer, Rolinde; Van Gulck, Elke; Van Droogenbroeck, Bart; Querci, Maddalena; Taverniers, Isabel; De Loose, Marc

2010-03-01

Competent laboratories monitor genetically modified organisms (GMOs) and products derived thereof in the food and feed chain in the framework of labeling and traceability legislation. In addition, screening is performed to detect the unauthorized presence of GMOs including asynchronously authorized GMOs or GMOs that are not officially registered for commercialization (unknown GMOs). Currently, unauthorized or unknown events are detected by screening blind samples for commonly used transgenic elements, such as p35S or t-nos. If (1) positive detection of such screening elements shows the presence of transgenic material and (2) all known GMOs are tested by event-specific methods but are not detected, then the presence of an unknown GMO is inferred. However, such evidence is indirect because it is based on negative observations and inconclusive because the procedure does not identify the causative event per se. In addition, detection of unknown events is hampered in products that also contain known authorized events. Here, we outline alternative approaches for analytical detection and GMO identification and develop new methods to complement the existing routine screening procedure. We developed a fluorescent anchor-polymerase chain reaction (PCR) method for the identification of the sequences flanking the p35S and t-nos screening elements. Thus, anchor-PCR fingerprinting allows the detection of unique discriminative signals per event. In addition, we established a collection of in silico calculated fingerprints of known events to support interpretation of experimentally generated anchor-PCR GM fingerprints of blind samples. Here, we first describe the molecular characterization of a novel GMO, which expresses recombinant human intrinsic factor in Arabidopsis thaliana. Next, we purposefully treated the novel GMO as a blind sample to simulate how the new methods lead to the molecular identification of a novel unknown event without prior knowledge of its transgene

Assessment of source-specific health effects associated with an unknown number of major sources of multiple air pollutants: a unified Bayesian approach.

PubMed

Park, Eun Sug; Hopke, Philip K; Oh, Man-Suk; Symanski, Elaine; Han, Daikwon; Spiegelman, Clifford H

2014-07-01

There has been increasing interest in assessing health effects associated with multiple air pollutants emitted by specific sources. A major difficulty with achieving this goal is that the pollution source profiles are unknown and source-specific exposures cannot be measured directly; rather, they need to be estimated by decomposing ambient measurements of multiple air pollutants. This estimation process, called multivariate receptor modeling, is challenging because of the unknown number of sources and unknown identifiability conditions (model uncertainty). The uncertainty in source-specific exposures (source contributions) as well as uncertainty in the number of major pollution sources and identifiability conditions have been largely ignored in previous studies. A multipollutant approach that can deal with model uncertainty in multivariate receptor models while simultaneously accounting for parameter uncertainty in estimated source-specific exposures in assessment of source-specific health effects is presented in this paper. The methods are applied to daily ambient air measurements of the chemical composition of fine particulate matter ([Formula: see text]), weather data, and counts of cardiovascular deaths from 1995 to 1997 for Phoenix, AZ, USA. Our approach for evaluating source-specific health effects yields not only estimates of source contributions along with their uncertainties and associated health effects estimates but also estimates of model uncertainty (posterior model probabilities) that have been ignored in previous studies. The results from our methods agreed in general with those from the previously conducted workshop/studies on the source apportionment of PM health effects in terms of number of major contributing sources, estimated source profiles, and contributions. However, some of the adverse source-specific health effects identified in the previous studies were not statistically significant in our analysis, which probably resulted because we

Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

Intermediate filament structure in fully differentiated (oxidised) trichocyte keratin.

PubMed

Fraser, R D Bruce; Parry, David A D

2017-10-01

For the past 50years there has been considerable debate over the sub-structure of the fully differentiated (oxidised) trichocyte keratin intermediate filament. Depending on the staining and preparative procedures employed, IF observed in transverse section in the transmission electron microscope have varied in appearance between that of a "ring" and a "ring-core" structure, corresponding to the so-called (8+0) and (7+1) protofilament arrangements. In a new analysis of the fine structure of the 1nm equatorial region of the X-ray diffraction pattern of quill we show that the observed pattern is consistent with the (8+0) model and we are also able to assign values to the various parameters. In contrast, we show that the observed X-ray pattern is inconsistent with a (7+1) arrangement. Furthermore, in the (7+1) model steric hindrance would be encountered between the core protofilament and those constituting the ring. The appearance of a central "core" in transverse TEM sections, previously attributed to a central protofilament, is explained in terms of portions of the apolar, disulfide-bonded head and/or tail domains of the trichocyte keratin IF molecules, including the conserved H subdomains, lying along the axis of the IF, thereby decreasing the efficacy of the reducing agents used prior to staining. The H1 subdomain, previously shown to be important in the assembly of epidermal IF molecules at the two- to four-molecule level, is likely to have a similar role for the trichocyte keratins and may form part of a central scaffold on which the molecules assemble into fully functional IF. Copyright © 2017 Elsevier Inc. All rights reserved.

Characteristics of liver fibrosis with different etiologies using a fully quantitative fibrosis assessment tool.

PubMed

Wu, Q; Zhao, X; You, H

2017-05-18

This study aimed to test the diagnostic performance of a fully quantitative fibrosis assessment tool for liver fibrosis in patients with chronic hepatitis B (CHB), primary biliary cirrhosis (PBC) and non-alcoholic steatohepatitis (NASH). A total of 117 patients with liver fibrosis were included in this study, including 50 patients with CHB, 49 patients with PBC and 18 patients with NASH. All patients underwent liver biopsy (LB). Fibrosis stages were assessed by two experienced pathologists. Histopathological images of LB slices were processed by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy without staining, a system called qFibrosis (quantitative fibrosis) system. Altogether 101 quantitative features of the SHG/TPEF images were acquired. The parameters of aggregated collagen in portal, septal and fibrillar areas increased significantly with stages of liver fibrosis in PBC and CHB (P<0.05), but the same was not found for parameters of distributed collagen (P>0.05). There was a significant correlation between parameters of aggregated collagen in portal, septal and fibrillar areas and stages of liver fibrosis from CHB and PBC (P<0.05), but no correlation was found between the distributed collagen parameters and the stages of liver fibrosis from those patients (P>0.05). There was no significant correlation between NASH parameters and stages of fibrosis (P>0.05). For CHB and PBC patients, the highest correlation was between septal parameters and fibrosis stages, the second highest was between portal parameters and fibrosis stages and the lowest correlation was between fibrillar parameters and fibrosis stages. The correlation between the septal parameters of the PBC and stages is significantly higher than the parameters of the other two areas (P<0.05). The qFibrosis candidate parameters based on CHB were also applicable for quantitative analysis of liver fibrosis in PBC patients. Different parameters should be selected for liver

Characteristics of liver fibrosis with different etiologies using a fully quantitative fibrosis assessment tool

PubMed Central

Wu, Q.; Zhao, X.; You, H.

2017-01-01

This study aimed to test the diagnostic performance of a fully quantitative fibrosis assessment tool for liver fibrosis in patients with chronic hepatitis B (CHB), primary biliary cirrhosis (PBC) and non-alcoholic steatohepatitis (NASH). A total of 117 patients with liver fibrosis were included in this study, including 50 patients with CHB, 49 patients with PBC and 18 patients with NASH. All patients underwent liver biopsy (LB). Fibrosis stages were assessed by two experienced pathologists. Histopathological images of LB slices were processed by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy without staining, a system called qFibrosis (quantitative fibrosis) system. Altogether 101 quantitative features of the SHG/TPEF images were acquired. The parameters of aggregated collagen in portal, septal and fibrillar areas increased significantly with stages of liver fibrosis in PBC and CHB (P<0.05), but the same was not found for parameters of distributed collagen (P>0.05). There was a significant correlation between parameters of aggregated collagen in portal, septal and fibrillar areas and stages of liver fibrosis from CHB and PBC (P<0.05), but no correlation was found between the distributed collagen parameters and the stages of liver fibrosis from those patients (P>0.05). There was no significant correlation between NASH parameters and stages of fibrosis (P>0.05). For CHB and PBC patients, the highest correlation was between septal parameters and fibrosis stages, the second highest was between portal parameters and fibrosis stages and the lowest correlation was between fibrillar parameters and fibrosis stages. The correlation between the septal parameters of the PBC and stages is significantly higher than the parameters of the other two areas (P<0.05). The qFibrosis candidate parameters based on CHB were also applicable for quantitative analysis of liver fibrosis in PBC patients. Different parameters should be selected for liver

Comparing Three Estimation Methods for the Three-Parameter Logistic IRT Model

ERIC Educational Resources Information Center

Lamsal, Sunil

2015-01-01

Different estimation procedures have been developed for the unidimensional three-parameter item response theory (IRT) model. These techniques include the marginal maximum likelihood estimation, the fully Bayesian estimation using Markov chain Monte Carlo simulation techniques, and the Metropolis-Hastings Robbin-Monro estimation. With each…

Parameter Estimation of Partial Differential Equation Models.

PubMed

Xun, Xiaolei; Cao, Jiguo; Mallick, Bani; Carroll, Raymond J; Maity, Arnab

2013-01-01

Partial differential equation (PDE) models are commonly used to model complex dynamic systems in applied sciences such as biology and finance. The forms of these PDE models are usually proposed by experts based on their prior knowledge and understanding of the dynamic system. Parameters in PDE models often have interesting scientific interpretations, but their values are often unknown, and need to be estimated from the measurements of the dynamic system in the present of measurement errors. Most PDEs used in practice have no analytic solutions, and can only be solved with numerical methods. Currently, methods for estimating PDE parameters require repeatedly solving PDEs numerically under thousands of candidate parameter values, and thus the computational load is high. In this article, we propose two methods to estimate parameters in PDE models: a parameter cascading method and a Bayesian approach. In both methods, the underlying dynamic process modeled with the PDE model is represented via basis function expansion. For the parameter cascading method, we develop two nested levels of optimization to estimate the PDE parameters. For the Bayesian method, we develop a joint model for data and the PDE, and develop a novel hierarchical model allowing us to employ Markov chain Monte Carlo (MCMC) techniques to make posterior inference. Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy. The two methods are demonstrated by estimating parameters in a PDE model from LIDAR data.

Progress in Fully Automated Abdominal CT Interpretation

PubMed Central

Summers, Ronald M.

2016-01-01

OBJECTIVE Automated analysis of abdominal CT has advanced markedly over just the last few years. Fully automated assessment of organs, lymph nodes, adipose tissue, muscle, bowel, spine, and tumors are some examples where tremendous progress has been made. Computer-aided detection of lesions has also improved dramatically. CONCLUSION This article reviews the progress and provides insights into what is in store in the near future for automated analysis for abdominal CT, ultimately leading to fully automated interpretation. PMID:27101207

Design of Fully Austenitic Medium Manganese Steels

NASA Astrophysics Data System (ADS)

Luan, G.; Volkova, O.; Mola, J.

2018-06-01

Due to their higher ferrite potential compared to high Mn twinning-induced plasticity (TWIP) steels, medium Mn steels usually exhibit austenitic-ferritic microstructures, which makes them suitable for third-generation advanced high-strength steel applications. Nevertheless, the strain hardening characteristics of medium Mn steels are inferior to those of fully austenitic high Mn steels. The present work introduces alloy design strategies to obtain fully austenitic medium Mn steels capable of the TWIP effect. To achieve a fully austenitic microstructure, the martensite start temperature is reduced by raising the C concentration to above 1 mass-%, which in turn facilitates the formation of cementite. The formation of cementite during cooling from austenitization temperature is counteracted by alloying with Al. Microstructural examination of slowly-cooled Fe‑Mn‑Al‑C and Fe‑Mn‑C steels indicated that Al changes the morphology of intergranular cementite from plate-shaped to equiaxed.

A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks

PubMed Central

Zaikin, Alexey; Míguez, Joaquín

2017-01-01

We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency. PMID:28797087

The Fully-Functioning University and Its Higher Education

ERIC Educational Resources Information Center

Bourner, Tom; Heath, Linda; Rospigliosi, Pericles

2013-01-01

In 2008 an article in this journal introduced the concept of a "fully-functioning university". This new article explores the sort of higher education (HE) that such a university would offer. It starts by examining the idea of a fully-functioning university and its relationship with the "tripartite mission" of a university. In…

Decentralised output feedback control of Markovian jump interconnected systems with unknown interconnections

NASA Astrophysics Data System (ADS)

Li, Li-Wei; Yang, Guang-Hong

2017-07-01

The problem of decentralised output feedback control is addressed for Markovian jump interconnected systems with unknown interconnections and general transition rates (TRs) allowed to be unknown or known with uncertainties. A class of decentralised dynamic output feedback controllers are constructed, and a cyclic-small-gain condition is exploited to dispose the unknown interconnections so that the resultant closed-loop system is stochastically stable and satisfies an H∞ performance. With slack matrices to cope with the nonlinearities incurred by unknown and uncertain TRs in control synthesis, a novel controller design condition is developed in linear matrix inequality formalism. Compared with the existing works, the proposed approach leads to less conservatism. Finally, two examples are used to illustrate the effectiveness of the new results.

Comparison of methods for the detection of gravitational waves from unknown neutron stars

NASA Astrophysics Data System (ADS)

Walsh, S.; Pitkin, M.; Oliver, M.; D'Antonio, S.; Dergachev, V.; Królak, A.; Astone, P.; Bejger, M.; Di Giovanni, M.; Dorosh, O.; Frasca, S.; Leaci, P.; Mastrogiovanni, S.; Miller, A.; Palomba, C.; Papa, M. A.; Piccinni, O. J.; Riles, K.; Sauter, O.; Sintes, A. M.

2016-12-01

Rapidly rotating neutron stars are promising sources of continuous gravitational wave radiation for the LIGO and Virgo interferometers. The majority of neutron stars in our galaxy have not been identified with electromagnetic observations. All-sky searches for isolated neutron stars offer the potential to detect gravitational waves from these unidentified sources. The parameter space of these blind all-sky searches, which also cover a large range of frequencies and frequency derivatives, presents a significant computational challenge. Different methods have been designed to perform these searches within acceptable computational limits. Here we describe the first benchmark in a project to compare the search methods currently available for the detection of unknown isolated neutron stars. The five methods compared here are individually referred to as the PowerFlux, sky Hough, frequency Hough, Einstein@Home, and time domain F -statistic methods. We employ a mock data challenge to compare the ability of each search method to recover signals simulated assuming a standard signal model. We find similar performance among the four quick-look search methods, while the more computationally intensive search method, Einstein@Home, achieves up to a factor of two higher sensitivity. We find that the absence of a second derivative frequency in the search parameter space does not degrade search sensitivity for signals with physically plausible second derivative frequencies. We also report on the parameter estimation accuracy of each search method, and the stability of the sensitivity in frequency and frequency derivative and in the presence of detector noise.

Buoyancy Effects in Fully-Modulated, Turbulent Diffusion Flames

NASA Technical Reports Server (NTRS)

Hermanson, J. C.; Johari, H.; Ghaem-Maghami, E.; Stocker, D. P.; Hegde, U. G.; Page, K. L.

2003-01-01

Pulsed combustion appears to have the potential to provide for rapid fuel/air mixing, compact and economical combustors, and reduced exhaust emissions. The objective of this experiment (PuFF, for Pulsed-Fully Flames) is to increase the fundamental understanding of the fuel/air mixing and combustion behavior of pulsed, turbulent diffusion flames by conducting experiments in microgravity. In this research the fuel jet is fully-modulated (i.e., completely shut off between pulses) by an externally controlled valve system. This gives rise to drastic modification of the combustion and flow characteristics of flames, leading to enhanced fuel/air mixing compared to acoustically excited or partially-modulated jets. Normal-gravity experiments suggest that the fully-modulated technique also has the potential for producing turbulent jet flames significantly more compact than steady flames with no increase in exhaust emissions. The technique also simplifies the combustion process by avoiding the acoustic forcing generally present in pulsed combustors. Fundamental issues addressed in this experiment include the impact of buoyancy on the structure and flame length, temperatures, radiation, and emissions of fully-modulated flames.

Parameter discovery in stochastic biological models using simulated annealing and statistical model checking.

PubMed

Hussain, Faraz; Jha, Sumit K; Jha, Susmit; Langmead, Christopher J

2014-01-01

Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential hypothesis testing, and statistical model checking to learn the parameters in a stochastic model. We apply our technique to a model of glucose and insulin metabolism used for in-silico validation of artificial pancreata and demonstrate its effectiveness by developing parallel CUDA-based implementation for parameter synthesis in this model.

Fully Passive Wireless Acquisition of Neuropotentials

NASA Astrophysics Data System (ADS)

Schwerdt, Helen N.

The ability to monitor electrophysiological signals from the sentient brain is requisite to decipher its enormously complex workings and initiate remedial solutions for the vast amount of neurologically-based disorders. Despite immense advancements in creating a variety of instruments to record signals from the brain, the translation of such neurorecording instrumentation to real clinical domains places heavy demands on their safety and reliability, both of which are not entirely portrayed by presently existing implantable recording solutions. In an attempt to lower these barriers, alternative wireless radar backscattering techniques are proposed to render the technical burdens of the implant chip to entirely passive neurorecording processes that transpire in the absence of formal integrated power sources or powering schemes along with any active circuitry. These radar-like wireless backscattering mechanisms are used to conceive of fully passive neurorecording operations of an implantable microsystem. The fully passive device potentially manifests inherent advantages over current wireless implantable and wired recording systems: negligible heat dissipation to reduce risks of brain tissue damage and minimal circuitry for long term reliability as a chronic implant. Fully passive neurorecording operations are realized via intrinsic nonlinear mixing properties of the varactor diode. These mixing and recording operations are directly activated by wirelessly interrogating the fully passive device with a microwave carrier signal. This fundamental carrier signal, acquired by the implant antenna, mixes through the varactor diode along with the internal targeted neuropotential brain signals to produce higher frequency harmonics containing the targeted neuropotential signals. These harmonics are backscattered wirelessly to the external interrogator that retrieves and recovers the original neuropotential brain signal. The passive approach removes the need for internal power

Parameter redundancy in discrete state-space and integrated models.

PubMed

Cole, Diana J; McCrea, Rachel S

2016-09-01

Discrete state-space models are used in ecology to describe the dynamics of wild animal populations, with parameters, such as the probability of survival, being of ecological interest. For a particular parametrization of a model it is not always clear which parameters can be estimated. This inability to estimate all parameters is known as parameter redundancy or a model is described as nonidentifiable. In this paper we develop methods that can be used to detect parameter redundancy in discrete state-space models. An exhaustive summary is a combination of parameters that fully specify a model. To use general methods for detecting parameter redundancy a suitable exhaustive summary is required. This paper proposes two methods for the derivation of an exhaustive summary for discrete state-space models using discrete analogues of methods for continuous state-space models. We also demonstrate that combining multiple data sets, through the use of an integrated population model, may result in a model in which all parameters are estimable, even though models fitted to the separate data sets may be parameter redundant. © 2016 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fully Resolved Simulations of 3D Printing

NASA Astrophysics Data System (ADS)

Tryggvason, Gretar; Xia, Huanxiong; Lu, Jiacai

2017-11-01

Numerical simulations of Fused Deposition Modeling (FDM) (or Fused Filament Fabrication) where a filament of hot, viscous polymer is deposited to ``print'' a three-dimensional object, layer by layer, are presented. A finite volume/front tracking method is used to follow the injection, cooling, solidification and shrinking of the filament. The injection of the hot melt is modeled using a volume source, combined with a nozzle, modeled as an immersed boundary, that follows a prescribed trajectory. The viscosity of the melt depends on the temperature and the shear rate and the polymer becomes immobile as its viscosity increases. As the polymer solidifies, the stress is found by assuming a hyperelastic constitutive equation. The method is described and its accuracy and convergence properties are tested by grid refinement studies for a simple setup involving two short filaments, one on top of the other. The effect of the various injection parameters, such as nozzle velocity and injection velocity are briefly examined and the applicability of the approach to simulate the construction of simple multilayer objects is shown. The role of fully resolved simulations for additive manufacturing and their use for novel processes and as the ``ground truth'' for reduced order models is discussed.

Adaptive estimation of nonlinear parameters of a nonholonomic spherical robot using a modified fuzzy-based speed gradient algorithm

NASA Astrophysics Data System (ADS)

Roozegar, Mehdi; Mahjoob, Mohammad J.; Ayati, Moosa

2017-05-01

This paper deals with adaptive estimation of the unknown parameters and states of a pendulum-driven spherical robot (PDSR), which is a nonlinear in parameters (NLP) chaotic system with parametric uncertainties. Firstly, the mathematical model of the robot is deduced by applying the Newton-Euler methodology for a system of rigid bodies. Then, based on the speed gradient (SG) algorithm, the states and unknown parameters of the robot are estimated online for different step length gains and initial conditions. The estimated parameters are updated adaptively according to the error between estimated and true state values. Since the errors of the estimated states and parameters as well as the convergence rates depend significantly on the value of step length gain, this gain should be chosen optimally. Hence, a heuristic fuzzy logic controller is employed to adjust the gain adaptively. Simulation results indicate that the proposed approach is highly encouraging for identification of this NLP chaotic system even if the initial conditions change and the uncertainties increase; therefore, it is reliable to be implemented on a real robot.

Towards high-speed autonomous navigation of unknown environments

NASA Astrophysics Data System (ADS)

Richter, Charles; Roy, Nicholas

2015-05-01

In this paper, we summarize recent research enabling high-speed navigation in unknown environments for dynamic robots that perceive the world through onboard sensors. Many existing solutions to this problem guarantee safety by making the conservative assumption that any unknown portion of the map may contain an obstacle, and therefore constrain planned motions to lie entirely within known free space. In this work, we observe that safety constraints may significantly limit performance and that faster navigation is possible if the planner reasons about collision with unobserved obstacles probabilistically. Our overall approach is to use machine learning to approximate the expected costs of collision using the current state of the map and the planned trajectory. Our contribution is to demonstrate fast but safe planning using a learned function to predict future collision probabilities.

Fully depleted back illuminated CCD

DOEpatents

Holland, Stephen Edward

2001-01-01

A backside illuminated charge coupled device (CCD) is formed of a relatively thick high resistivity photon sensitive silicon substrate, with frontside electronic circuitry, and an optically transparent backside ohmic contact for applying a backside voltage which is at least sufficient to substantially fully deplete the substrate. A greater bias voltage which overdepletes the substrate may also be applied. One way of applying the bias voltage to the substrate is by physically connecting the voltage source to the ohmic contact. An alternate way of applying the bias voltage to the substrate is to physically connect the voltage source to the frontside of the substrate, at a point outside the depletion region. Thus both frontside and backside contacts can be used for backside biasing to fully deplete the substrate. Also, high resistivity gaps around the CCD channels and electrically floating channel stop regions can be provided in the CCD array around the CCD channels. The CCD array forms an imaging sensor useful in astronomy.

The Information Available to a Moving Observer on Shape with Unknown, Isotropic BRDFs.

PubMed

Chandraker, Manmohan

2016-07-01

Psychophysical studies show motion cues inform about shape even with unknown reflectance. Recent works in computer vision have considered shape recovery for an object of unknown BRDF using light source or object motions. This paper proposes a theory that addresses the remaining problem of determining shape from the (small or differential) motion of the camera, for unknown isotropic BRDFs. Our theory derives a differential stereo relation that relates camera motion to surface depth, which generalizes traditional Lambertian assumptions. Under orthographic projection, we show differential stereo may not determine shape for general BRDFs, but suffices to yield an invariant for several restricted (still unknown) BRDFs exhibited by common materials. For the perspective case, we show that differential stereo yields the surface depth for unknown isotropic BRDF and unknown directional lighting, while additional constraints are obtained with restrictions on the BRDF or lighting. The limits imposed by our theory are intrinsic to the shape recovery problem and independent of choice of reconstruction method. We also illustrate trends shared by theories on shape from differential motion of light source, object or camera, to relate the hardness of surface reconstruction to the complexity of imaging setup.

Component spectra extraction from terahertz measurements of unknown mixtures.

PubMed

Li, Xian; Hou, D B; Huang, P J; Cai, J H; Zhang, G X

2015-10-20

The aim of this work is to extract component spectra from unknown mixtures in the terahertz region. To that end, a method, hard modeling factor analysis (HMFA), was applied to resolve terahertz spectral matrices collected from the unknown mixtures. This method does not require any expertise of the user and allows the consideration of nonlinear effects such as peak variations or peak shifts. It describes the spectra using a peak-based nonlinear mathematic model and builds the component spectra automatically by recombination of the resolved peaks through correlation analysis. Meanwhile, modifications on the method were made to take the features of terahertz spectra into account and to deal with the artificial baseline problem that troubles the extraction process of some terahertz spectra. In order to validate the proposed method, simulated wideband terahertz spectra of binary and ternary systems and experimental terahertz absorption spectra of amino acids mixtures were tested. In each test, not only the number of pure components could be correctly predicted but also the identified pure spectra had a good similarity with the true spectra. Moreover, the proposed method associated the molecular motions with the component extraction, making the identification process more physically meaningful and interpretable compared to other methods. The results indicate that the HMFA method with the modifications can be a practical tool for identifying component terahertz spectra in completely unknown mixtures. This work reports the solution to this kind of problem in the terahertz region for the first time, to the best of the authors' knowledge, and represents a significant advance toward exploring physical or chemical mechanisms of unknown complex systems by terahertz spectroscopy.

Brute force meets Bruno force in parameter optimisation: introduction of novel constraints for parameter accuracy improvement by symbolic computation.

PubMed

Nakatsui, M; Horimoto, K; Lemaire, F; Ürgüplü, A; Sedoglavic, A; Boulier, F

2011-09-01

Recent remarkable advances in computer performance have enabled us to estimate parameter values by the huge power of numerical computation, the so-called 'Brute force', resulting in the high-speed simultaneous estimation of a large number of parameter values. However, these advancements have not been fully utilised to improve the accuracy of parameter estimation. Here the authors review a novel method for parameter estimation using symbolic computation power, 'Bruno force', named after Bruno Buchberger, who found the Gröbner base. In the method, the objective functions combining the symbolic computation techniques are formulated. First, the authors utilise a symbolic computation technique, differential elimination, which symbolically reduces an equivalent system of differential equations to a system in a given model. Second, since its equivalent system is frequently composed of large equations, the system is further simplified by another symbolic computation. The performance of the authors' method for parameter accuracy improvement is illustrated by two representative models in biology, a simple cascade model and a negative feedback model in comparison with the previous numerical methods. Finally, the limits and extensions of the authors' method are discussed, in terms of the possible power of 'Bruno force' for the development of a new horizon in parameter estimation.

Parameter and state estimation in a Neisseria meningitidis model: A study case of Niger

NASA Astrophysics Data System (ADS)

Bowong, S.; Mountaga, L.; Bah, A.; Tewa, J. J.; Kurths, J.

2016-12-01

Neisseria meningitidis (Nm) is a major cause of bacterial meningitidis outbreaks in Africa and the Middle East. The availability of yearly reported meningitis cases in the African meningitis belt offers the opportunity to analyze the transmission dynamics and the impact of control strategies. In this paper, we propose a method for the estimation of state variables that are not accessible to measurements and an unknown parameter in a Nm model. We suppose that the yearly number of Nm induced mortality and the total population are known inputs, which can be obtained from data, and the yearly number of new Nm cases is the model output. We also suppose that the Nm transmission rate is an unknown parameter. We first show how the recruitment rate into the population can be estimated using real data of the total population and Nm induced mortality. Then, we use an auxiliary system called observer whose solutions converge exponentially to those of the original model. This observer does not use the unknown infection transmission rate but only uses the known inputs and the model output. This allows us to estimate unmeasured state variables such as the number of carriers that play an important role in the transmission of the infection and the total number of infected individuals within a human community. Finally, we also provide a simple method to estimate the unknown Nm transmission rate. In order to validate the estimation results, numerical simulations are conducted using real data of Niger.

Fully Nonlinear Modeling and Analysis of Precision Membranes

NASA Technical Reports Server (NTRS)

Pai, P. Frank; Young, Leyland G.

2003-01-01

High precision membranes are used in many current space applications. This paper presents a fully nonlinear membrane theory with forward and inverse analyses of high precision membrane structures. The fully nonlinear membrane theory is derived from Jaumann strains and stresses, exact coordinate transformations, the concept of local relative displacements, and orthogonal virtual rotations. In this theory, energy and Newtonian formulations are fully correlated, and every structural term can be interpreted in terms of vectors. Fully nonlinear ordinary differential equations (ODES) governing the large static deformations of known axisymmetric membranes under known axisymmetric loading (i.e., forward problems) are presented as first-order ODES, and a method for obtaining numerically exact solutions using the multiple shooting procedure is shown. A method for obtaining the undeformed geometry of any axisymmetric membrane with a known inflated geometry and a known internal pressure (i.e., inverse problems) is also derived. Numerical results from forward analysis are verified using results in the literature, and results from inverse analysis are verified using known exact solutions and solutions from the forward analysis. Results show that the membrane theory and the proposed numerical methods for solving nonlinear forward and inverse membrane problems are accurate.

Lod score curves for phase-unknown matings.

PubMed

Hulbert-Shearon, T; Boehnke, M; Lange, K

1996-01-01

For a phase-unknown nuclear family, we show that the likelihood and lod score are unimodal, and we describe conditions under which the maximum occurs at recombination fraction theta = 0, theta = 1/2, and 0 < theta < 1/2. These simply stated necessary and sufficient conditions seem to have escaped the notice of previous statistical geneticists.

Method for genetic identification of unknown organisms

DOEpatents

Colston, Jr., Billy W.; Fitch, Joseph P.; Hindson, Benjamin J.; Carter, Chance J.; Beer, Neil Reginald

2016-08-23

A method of rapid, genome and proteome based identification of unknown pathogenic or non-pathogenic organisms in a complex sample. The entire sample is analyzed by creating millions of emulsion encapsulated microdroplets, each containing a single pathogenic or non-pathogenic organism sized particle and appropriate reagents for amplification. Following amplification, the amplified product is analyzed.

Finite-time sliding surface constrained control for a robot manipulator with an unknown deadzone and disturbance.

PubMed

Ik Han, Seong; Lee, Jangmyung

2016-11-01

This paper presents finite-time sliding mode control (FSMC) with predefined constraints for the tracking error and sliding surface in order to obtain robust positioning of a robot manipulator with input nonlinearity due to an unknown deadzone and external disturbance. An assumed model feedforward FSMC was designed to avoid tedious identification procedures for the manipulator parameters and to obtain a fast response time. Two constraint switching control functions based on the tracking error and finite-time sliding surface were added to the FSMC to guarantee the predefined tracking performance despite the presence of an unknown deadzone and disturbance. The tracking error due to the deadzone and disturbance can be suppressed within the predefined error boundary simply by tuning the gain value of the constraint switching function and without the addition of an extra compensator. Therefore, the designed constraint controller has a simpler structure than conventional transformed error constraint methods and the sliding surface constraint scheme can also indirectly guarantee the tracking error constraint while being more stable than the tracking error constraint control. A simulation and experiment were performed on an articulated robot manipulator to validate the proposed control schemes. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Incentive Controls for Stackelberg Games with Unknown Cost Functionals.

DTIC Science & Technology

1984-01-01

APR EZT:: F I AN 73S e OsL:-: UNCLASSI?:-- Q4~.’~- .A.., 6, *~*i i~~*~~*.- U ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH UNKNOWN COST...AD-A161 885 ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH i/1 UNKNOWN COST FUNCTIONALSCU) ILLINOIS UNIV AT URBANA DECISION AND CONTROL LAB T...ORGANIZATION 6b. OFFICE SYMBOL 7.. NAME OF MONITORING ORGANIZATION CoriaeLcenef~pda~ Joint Services Electronics Program Laboratory, Univ. of Illinois N/A

A Concept Analysis of Fully Informed: Breastfeeding Promotion

DTIC Science & Technology

2005-12-21

updated breastfeeding policy statement, the American Academy of Pediatrics 3 ( AAP , 2005) identified the compelling advantages of breastfeeding and urged...healthcare 4 professionals to implement principles to promote breastfeeding . The AAP cited obstacles 5 to the initiation and continuation of...Analysis of Fully Informed 2 14 A Concept Analysis of Fully Informed: Breastfeeding Promotion 15 In February 2005, the American Academy of Pediatrics ( AAP

Parameter estimation in nonlinear distributed systems - Approximation theory and convergence results

NASA Technical Reports Server (NTRS)

Banks, H. T.; Reich, Simeon; Rosen, I. G.

1988-01-01

An abstract approximation framework and convergence theory is described for Galerkin approximations applied to inverse problems involving nonlinear distributed parameter systems. Parameter estimation problems are considered and formulated as the minimization of a least-squares-like performance index over a compact admissible parameter set subject to state constraints given by an inhomogeneous nonlinear distributed system. The theory applies to systems whose dynamics can be described by either time-independent or nonstationary strongly maximal monotonic operators defined on a reflexive Banach space which is densely and continuously embedded in a Hilbert space. It is demonstrated that if readily verifiable conditions on the system's dependence on the unknown parameters are satisfied, and the usual Galerkin approximation assumption holds, then solutions to the approximating problems exist and approximate a solution to the original infinite-dimensional identification problem.

Buckling Behavior of Long Anisotropic Plates Subjected to Fully Restrained Thermal Expansion

NASA Technical Reports Server (NTRS)

Nemeth, Michael P.

2003-01-01

An approach for synthesizing buckling results and behavior for thin, balanced and unbalanced symmetric laminates that are subjected to uniform heating or cooling and which are fully-restrained against thermal expansion or contraction is presented. This approach uses a nondimensional analysis for infinitely long, flexurally anisotropic plates that are subjected to combined mechanical loads and is based on useful nondimensional parameters. In addition, stiffness-weighted laminate thermal-expansion parameters are derived and used to determine critical temperature changes in terms of physically intuitive mechanical buckling coefficients. The effects of membrane orthotropy and anisotropy are included. Many results are presented for some common laminates that are intended to facilitate a structural designer's transition to the use of the generic buckling design curves that are presented in the paper. Several generic buckling design curves are presented that provide physical insight into buckling response and provide useful design data. Examples are presented that demonstrate the use of generic design curves. The analysis approach and generic results indicate the effects and characteristics of laminate thermal expansion, membrane orthotropy and anisotropy, and flexural orthotropy and anisotropy in a very general, unifying manner.

Buckling Behavior of Long Anisotropic Plates Subjected to Fully Restrained Thermal Expansion

NASA Technical Reports Server (NTRS)

Nemeth, Michael P.

2001-01-01

An approach for synthesizing buckling results and behavior for thin balanced and unbalanced symmetric laminates that are subjected to uniform heating or cooling and fully restrained against thermal expansion or contraction is presented. This approach uses a nondimensional analysis for infinitely long, flexurally anisotropic plates that are subjected to combined mechanical loads and is based on useful nondimensional parameters. In addition, stiffness-weighted laminate thermal-expansion parameters are derived that are used to determine critical temperatures in terms of physically intuitive mechanical buckling coefficients, and the effects of membrane orthotropy and membrane anisotropy are included. Many results are presented for some common laminates that are intended to facilitate a structural designer's transition to the use of the generic buckling design curves that are presented in the paper. Several generic buckling design curves are presented that provide physical insight into the buckling response in addition to providing useful design data. Examples are presented that demonstrate the use of the generic design curves. The analysis approach and generic results indicate the effects and characteristics of laminate thermal expansion, membrane orthotropy and anisotropy, and flexural orthotropy and anisotropy in a very general and unifying manner.

A new design concept of fully grouted rock bolts in underground construction

NASA Astrophysics Data System (ADS)

Phich Nguyen, Quang; Nguyen, Van Manh; Tuong Nguyen, Ke

2018-04-01

The main problem after excavating an underground excavation is to maintain the stability of the excavation for a certain period of time. Failure in meeting this demand is a threat to safety of men and equipment. Support and reinforcement are different instruments with different mechanisms. Among the common support systems in tunnelling and mining, rock bolts have been widely used to reinforce rock mass and also to reduce geological hazards. Furthermore rock bolts can be applied under varying different geological conditions with cost-effectiveness. Although different methods are developed for grouted rock bolts design until now, the interaction mechanism of the rock bolts and rock mass is still very complicated issue. The paper addresses an analytical model for the analysis and design of fully grouted rock bolts based on the reinforcement principle. According to this concept the jointed rock mass reinforced by grouted rock bolts is considered as composite material which includes rock mass, the grout material and the bolt shank. The mechanical properties of this composite material depend on the ratio of the components. The closed-form solution was developed based on the assumption that the rock mass arround a circular tunnel remained elastic after installing fully grouted rock bolts. The main parameters of the rock-bolt system (the diameter and length of bolt shank, the space between the bolts) are then easily estimated from the obtained solution.

A new polytopic approach for the unknown input functional observer design

NASA Astrophysics Data System (ADS)

Bezzaoucha, Souad; Voos, Holger; Darouach, Mohamed

2018-03-01

In this paper, a constructive procedure to design Functional Unknown Input Observers for nonlinear continuous time systems is proposed under the Polytopic Takagi-Sugeno framework. An equivalent representation for the nonlinear model is achieved using the sector nonlinearity transformation. Applying the Lyapunov theory and the ? attenuation, linear matrix inequalities conditions are deduced which are solved for feasibility to obtain the observer design matrices. To cope with the effect of unknown inputs, classical approach of decoupling the unknown input for the linear case is used. Both algebraic and solver-based solutions are proposed (relaxed conditions). Necessary and sufficient conditions for the existence of the functional polytopic observer are given. For both approaches, the general and particular cases (measurable premise variables, full state estimation with full and reduced order cases) are considered and it is shown that the proposed conditions correspond to the one presented for standard linear case. To illustrate the proposed theoretical results, detailed numerical simulations are presented for a Quadrotor Aerial Robots Landing and a Waste Water Treatment Plant. Both systems are highly nonlinear and represented in a T-S polytopic form with unmeasurable premise variables and unknown inputs.

17. Photographic copy of photograph. Location unknown but assumed to ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

17. Photographic copy of photograph. Location unknown but assumed to be uper end of canal. Features no longer extant. (Source: U.S. Department of Interior. Office of Indian Affairs. Indian Irrigation service. Annual Report, Fiscal Year 1925. Vol. I, Narrative and Photographs, Irrigation District #4, California and Southern Arizona, RG 75, Entry 655, Box 28, National Archives, Washington, DC.) Photographer unknown. MAIN (TITLED FLORENCE) CANAL, WASTEWAY, SLUICEWAY, & BRIDGE, 1/26/25. - San Carlos Irrigation Project, Marin Canal, Amhurst-Hayden Dam to Picacho Reservoir, Coolidge, Pinal County, AZ

Optimization of Biomathematical Model Predictions for Cognitive Performance Impairment in Individuals: Accounting for Unknown Traits and Uncertain States in Homeostatic and Circadian Processes

PubMed Central

Van Dongen, Hans P. A.; Mott, Christopher G.; Huang, Jen-Kuang; Mollicone, Daniel J.; McKenzie, Frederic D.; Dinges, David F.

2007-01-01

Current biomathematical models of fatigue and performance do not accurately predict cognitive performance for individuals with a priori unknown degrees of trait vulnerability to sleep loss, do not predict performance reliably when initial conditions are uncertain, and do not yield statistically valid estimates of prediction accuracy. These limitations diminish their usefulness for predicting the performance of individuals in operational environments. To overcome these 3 limitations, a novel modeling approach was developed, based on the expansion of a statistical technique called Bayesian forecasting. The expanded Bayesian forecasting procedure was implemented in the two-process model of sleep regulation, which has been used to predict performance on the basis of the combination of a sleep homeostatic process and a circadian process. Employing the two-process model with the Bayesian forecasting procedure to predict performance for individual subjects in the face of unknown traits and uncertain states entailed subject-specific optimization of 3 trait parameters (homeostatic build-up rate, circadian amplitude, and basal performance level) and 2 initial state parameters (initial homeostatic state and circadian phase angle). Prior information about the distribution of the trait parameters in the population at large was extracted from psychomotor vigilance test (PVT) performance measurements in 10 subjects who had participated in a laboratory experiment with 88 h of total sleep deprivation. The PVT performance data of 3 additional subjects in this experiment were set aside beforehand for use in prospective computer simulations. The simulations involved updating the subject-specific model parameters every time the next performance measurement became available, and then predicting performance 24 h ahead. Comparison of the predictions to the subjects' actual data revealed that as more data became available for the individuals at hand, the performance predictions became

Fully probabilistic seismic source inversion - Part 2: Modelling errors and station covariances

NASA Astrophysics Data System (ADS)

Stähler, Simon C.; Sigloch, Karin

2016-11-01

Seismic source inversion, a central task in seismology, is concerned with the estimation of earthquake source parameters and their uncertainties. Estimating uncertainties is particularly challenging because source inversion is a non-linear problem. In a companion paper, Stähler and Sigloch (2014) developed a method of fully Bayesian inference for source parameters, based on measurements of waveform cross-correlation between broadband, teleseismic body-wave observations and their modelled counterparts. This approach yields not only depth and moment tensor estimates but also source time functions. A prerequisite for Bayesian inference is the proper characterisation of the noise afflicting the measurements, a problem we address here. We show that, for realistic broadband body-wave seismograms, the systematic error due to an incomplete physical model affects waveform misfits more strongly than random, ambient background noise. In this situation, the waveform cross-correlation coefficient CC, or rather its decorrelation D = 1 - CC, performs more robustly as a misfit criterion than ℓp norms, more commonly used as sample-by-sample measures of misfit based on distances between individual time samples. From a set of over 900 user-supervised, deterministic earthquake source solutions treated as a quality-controlled reference, we derive the noise distribution on signal decorrelation D = 1 - CC of the broadband seismogram fits between observed and modelled waveforms. The noise on D is found to approximately follow a log-normal distribution, a fortunate fact that readily accommodates the formulation of an empirical likelihood function for D for our multivariate problem. The first and second moments of this multivariate distribution are shown to depend mostly on the signal-to-noise ratio (SNR) of the CC measurements and on the back-azimuthal distances of seismic stations. By identifying and quantifying this likelihood function, we make D and thus waveform cross

Parameter estimation for stiff deterministic dynamical systems via ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Arnold, Andrea; Calvetti, Daniela; Somersalo, Erkki

2014-10-01

A commonly encountered problem in numerous areas of applications is to estimate the unknown coefficients of a dynamical system from direct or indirect observations at discrete times of some of the components of the state vector. A related problem is to estimate unobserved components of the state. An egregious example of such a problem is provided by metabolic models, in which the numerous model parameters and the concentrations of the metabolites in tissue are to be estimated from concentration data in the blood. A popular method for addressing similar questions in stochastic and turbulent dynamics is the ensemble Kalman filter (EnKF), a particle-based filtering method that generalizes classical Kalman filtering. In this work, we adapt the EnKF algorithm for deterministic systems in which the numerical approximation error is interpreted as a stochastic drift with variance based on classical error estimates of numerical integrators. This approach, which is particularly suitable for stiff systems where the stiffness may depend on the parameters, allows us to effectively exploit the parallel nature of particle methods. Moreover, we demonstrate how spatial prior information about the state vector, which helps the stability of the computed solution, can be incorporated into the filter. The viability of the approach is shown by computed examples, including a metabolic system modeling an ischemic episode in skeletal muscle, with a high number of unknown parameters.

16 CFR 303.14 - Products containing unknown fibers.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., secondhand materials, textile by-products, or waste materials of unknown, and for practical purposes... the fiber content disclosure otherwise required by the Act and regulations, indicate that such product is composed of miscellaneous scraps, rags, odd lots, textile by-products, secondhand materials (in...

A fully integrated standalone portable cavity ringdown breath acetone analyzer.

PubMed

Sun, Meixiu; Jiang, Chenyu; Gong, Zhiyong; Zhao, Xiaomeng; Chen, Zhuying; Wang, Zhennan; Kang, Meiling; Li, Yingxin; Wang, Chuji

2015-09-01

Breath analysis is a promising new technique for nonintrusive disease diagnosis and metabolic status monitoring. One challenging issue in using a breath biomarker for potential particular disease screening is to find a quantitative relationship between the concentration of the breath biomarker and clinical diagnostic parameters of the specific disease. In order to address this issue, we need a new instrument that is capable of conducting real-time, online breath analysis with high data throughput, so that a large scale of clinical test (more subjects) can be achieved in a short period of time. In this work, we report a fully integrated, standalone, portable analyzer based on the cavity ringdown spectroscopy technique for near-real time, online breath acetone measurements. The performance of the portable analyzer in measurements of breath acetone was interrogated and validated by using the certificated gas chromatography-mass spectrometry. The results show that this new analyzer is useful for reliable online (online introduction of a breath sample without pre-treatment) breath acetone analysis with high sensitivity (57 ppb) and high data throughput (one data per second). Subsequently, the validated breath analyzer was employed for acetone measurements in 119 human subjects under various situations. The instrument design, packaging, specifications, and future improvements were also described. From an optical ringdown cavity operated by the lab-set electronics reported previously to this fully integrated standalone new instrument, we have enabled a new scientific tool suited for large scales of breath acetone analysis and created an instrument platform that can even be adopted for study of other breath biomarkers by using different lasers and ringdown mirrors covering corresponding spectral fingerprints.

A fully integrated standalone portable cavity ringdown breath acetone analyzer

NASA Astrophysics Data System (ADS)

Sun, Meixiu; Jiang, Chenyu; Gong, Zhiyong; Zhao, Xiaomeng; Chen, Zhuying; Wang, Zhennan; Kang, Meiling; Li, Yingxin; Wang, Chuji

2015-09-01

Breath analysis is a promising new technique for nonintrusive disease diagnosis and metabolic status monitoring. One challenging issue in using a breath biomarker for potential particular disease screening is to find a quantitative relationship between the concentration of the breath biomarker and clinical diagnostic parameters of the specific disease. In order to address this issue, we need a new instrument that is capable of conducting real-time, online breath analysis with high data throughput, so that a large scale of clinical test (more subjects) can be achieved in a short period of time. In this work, we report a fully integrated, standalone, portable analyzer based on the cavity ringdown spectroscopy technique for near-real time, online breath acetone measurements. The performance of the portable analyzer in measurements of breath acetone was interrogated and validated by using the certificated gas chromatography-mass spectrometry. The results show that this new analyzer is useful for reliable online (online introduction of a breath sample without pre-treatment) breath acetone analysis with high sensitivity (57 ppb) and high data throughput (one data per second). Subsequently, the validated breath analyzer was employed for acetone measurements in 119 human subjects under various situations. The instrument design, packaging, specifications, and future improvements were also described. From an optical ringdown cavity operated by the lab-set electronics reported previously to this fully integrated standalone new instrument, we have enabled a new scientific tool suited for large scales of breath acetone analysis and created an instrument platform that can even be adopted for study of other breath biomarkers by using different lasers and ringdown mirrors covering corresponding spectral fingerprints.

Aerodynamic parameter estimation via Fourier modulating function techniques

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1995-01-01

Parameter estimation algorithms are developed in the frequency domain for systems modeled by input/output ordinary differential equations. The approach is based on Shinbrot's method of moment functionals utilizing Fourier based modulating functions. Assuming white measurement noises for linear multivariable system models, an adaptive weighted least squares algorithm is developed which approximates a maximum likelihood estimate and cannot be biased by unknown initial or boundary conditions in the data owing to a special property attending Shinbrot-type modulating functions. Application is made to perturbation equation modeling of the longitudinal and lateral dynamics of a high performance aircraft using flight-test data. Comparative studies are included which demonstrate potential advantages of the algorithm relative to some well established techniques for parameter identification. Deterministic least squares extensions of the approach are made to the frequency transfer function identification problem for linear systems and to the parameter identification problem for a class of nonlinear-time-varying differential system models.

Material parameter estimation with terahertz time-domain spectroscopy.

PubMed

Dorney, T D; Baraniuk, R G; Mittleman, D M

2001-07-01

Imaging systems based on terahertz (THz) time-domain spectroscopy offer a range of unique modalities owing to the broad bandwidth, subpicosecond duration, and phase-sensitive detection of the THz pulses. Furthermore, the possibility exists for combining spectroscopic characterization or identification with imaging because the radiation is broadband in nature. To achieve this, we require novel methods for real-time analysis of THz waveforms. This paper describes a robust algorithm for extracting material parameters from measured THz waveforms. Our algorithm simultaneously obtains both the thickness and the complex refractive index of an unknown sample under certain conditions. In contrast, most spectroscopic transmission measurements require knowledge of the sample's thickness for an accurate determination of its optical parameters. Our approach relies on a model-based estimation, a gradient descent search, and the total variation measure. We explore the limits of this technique and compare the results with literature data for optical parameters of several different materials.

Adaptive Fault-Tolerant Control of Uncertain Nonlinear Large-Scale Systems With Unknown Dead Zone.

PubMed

Chen, Mou; Tao, Gang

2016-08-01

In this paper, an adaptive neural fault-tolerant control scheme is proposed and analyzed for a class of uncertain nonlinear large-scale systems with unknown dead zone and external disturbances. To tackle the unknown nonlinear interaction functions in the large-scale system, the radial basis function neural network (RBFNN) is employed to approximate them. To further handle the unknown approximation errors and the effects of the unknown dead zone and external disturbances, integrated as the compounded disturbances, the corresponding disturbance observers are developed for their estimations. Based on the outputs of the RBFNN and the disturbance observer, the adaptive neural fault-tolerant control scheme is designed for uncertain nonlinear large-scale systems by using a decentralized backstepping technique. The closed-loop stability of the adaptive control system is rigorously proved via Lyapunov analysis and the satisfactory tracking performance is achieved under the integrated effects of unknown dead zone, actuator fault, and unknown external disturbances. Simulation results of a mass-spring-damper system are given to illustrate the effectiveness of the proposed adaptive neural fault-tolerant control scheme for uncertain nonlinear large-scale systems.

Previously unknown species of Aspergillus.

PubMed

Gautier, M; Normand, A-C; Ranque, S

2016-08-01

The use of multi-locus DNA sequence analysis has led to the description of previously unknown 'cryptic' Aspergillus species, whereas classical morphology-based identification of Aspergillus remains limited to the section or species-complex level. The current literature highlights two main features concerning these 'cryptic' Aspergillus species. First, the prevalence of such species in clinical samples is relatively high compared with emergent filamentous fungal taxa such as Mucorales, Scedosporium or Fusarium. Second, it is clearly important to identify these species in the clinical laboratory because of the high frequency of antifungal drug-resistant isolates of such Aspergillus species. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been shown to enable the identification of filamentous fungi with an accuracy similar to that of DNA sequence-based methods. As MALDI-TOF MS is well suited to the routine clinical laboratory workflow, it facilitates the identification of these 'cryptic' Aspergillus species at the routine mycology bench. The rapid establishment of enhanced filamentous fungi identification facilities will lead to a better understanding of the epidemiology and clinical importance of these emerging Aspergillus species. Based on routine MALDI-TOF MS-based identification results, we provide original insights into the key interpretation issues of a positive Aspergillus culture from a clinical sample. Which ubiquitous species that are frequently isolated from air samples are rarely involved in human invasive disease? Can both the species and the type of biological sample indicate Aspergillus carriage, colonization or infection in a patient? Highly accurate routine filamentous fungi identification is central to enhance the understanding of these previously unknown Aspergillus species, with a vital impact on further improved patient care. Copyright © 2016 European Society of Clinical Microbiology and

Prevalence and Impact of Unknown Diabetes in the ICU.

PubMed

Carpenter, David L; Gregg, Sara R; Xu, Kejun; Buchman, Timothy G; Coopersmith, Craig M

2015-12-01

Many patients with diabetes and their care providers are unaware of the presence of the disease. Dysglycemia encompassing hyperglycemia, hypoglycemia, and glucose variability is common in the ICU in patients with and without diabetes. The purpose of this study was to determine the impact of unknown diabetes on glycemic control in the ICU. Prospective observational study. Nine ICUs in an academic, tertiary hospital and a hybrid academic/community hospital. Hemoglobin A1c levels were ordered at all ICU admissions from March 1, 2011 to September 30, 2013. Electronic medical records were examined for a history of antihyperglycemic medications or International Classification of Diseases, 9th Edition diagnosis of diabetes. Patients were categorized as having unknown diabetes (hemoglobin A1c > 6.5%, without history of diabetes), no diabetes (hemoglobin A1c < 6.5%, without history of diabetes), controlled known diabetes (hemoglobin A1c < 6.5%, with documented history of diabetes), and uncontrolled known diabetes (hemoglobin A1c > 6.5%, with documented history of diabetes). None. A total of 15,737 patients had an hemoglobin A1c and medical record evaluable for the history of diabetes, and 5,635 patients had diabetes diagnosed by either medical history or an elevated hemoglobin A1c in the ICU. Of these, 1,460 patients had unknown diabetes, accounting for 26.0% of all patients with diabetes. This represented 41.0% of patients with an hemoglobin A1c > 6.5% and 9.3% of all ICU patients. Compared with patients without diabetes, patients with unknown diabetes had a higher likelihood of requiring an insulin infusion (44.3% vs 29.3%; p < 0.0001), a higher average blood glucose (172 vs 126 mg/dL; p < 0.0001), an increased percentage of hyperglycemia (19.7% vs 7.0%; blood glucose > 180 mg/dL; p < 0.0001) and hypoglycemia (8.9% vs 2.5%; blood glucose < 70 mg/dL; p < 0.0001), higher glycemic variability (55.6 vs 28.8, average of patient SD of glucose; p < 0.0001), and increased

Three-Dimensional Echocardiographic Assessment of Left Heart Chamber Size and Function with Fully Automated Quantification Software in Patients with Atrial Fibrillation.

PubMed

Otani, Kyoko; Nakazono, Akemi; Salgo, Ivan S; Lang, Roberto M; Takeuchi, Masaaki

2016-10-01

Echocardiographic determination of left heart chamber volumetric parameters by using manual tracings during multiple beats is tedious in atrial fibrillation (AF). The aim of this study was to determine the usefulness of fully automated left chamber quantification software with single-beat three-dimensional transthoracic echocardiographic data sets in patients with AF. Single-beat full-volume three-dimensional transthoracic echocardiographic data sets were prospectively acquired during consecutive multiple cardiac beats (≥10 beats) in 88 patients with AF. In protocol 1, left ventricular volumes, left ventricular ejection fraction, and maximal left atrial volume were validated using automated quantification against the manual tracing method in identical beats in 10 patients. In protocol 2, automated quantification-derived averaged values from multiple beats were compared with the corresponding values obtained from the indexed beat in all patients. Excellent correlations of left chamber parameters between automated quantification and the manual method were observed (r = 0.88-0.98) in protocol 1. The time required for the analysis with the automated quantification method (5 min) was significantly less compared with the manual method (27 min) (P < .0001). In protocol 2, there were excellent linear correlations between the averaged left chamber parameters and the corresponding values obtained from the indexed beat (r = 0.94-0.99), and test-retest variability of left chamber parameters was low (3.5%-4.8%). Three-dimensional transthoracic echocardiography with fully automated quantification software is a rapid and reliable way to measure averaged values of left heart chamber parameters during multiple consecutive beats. Thus, it is a potential new approach for left chamber quantification in patients with AF in daily routine practice. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.

Pattern Recognition Algorithm for High-Sensitivity Odorant Detection in Unknown Environments

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2012-01-01

In a realistic odorant detection application environment, the collected sensory data is a mix of unknown chemicals with unknown concentrations and noise. The identification of the odorants among these mixtures is a challenge in data recognition. In addition, deriving their individual concentrations in the mix is also a challenge. A deterministic analytical model was developed to accurately identify odorants and calculate their concentrations in a mixture with noisy data.

Multiple tendon ruptures of unknown etiology.

PubMed

Axibal, Derek P; Anderson, John G

2013-10-01

Tendon ruptures are common findings in foot and ankle practice. The etiology of tendon ruptures tends to be multifactorial-usually due to a combination of trauma, effects of systemic diseases, adverse effects of medications, and obesity. We present an unusual case of right Achilles tendinitis, left Achilles tendon rupture, bilateral peroneus longus tendon rupture, and left peroneus brevis tendon rupture of unknown etiology. This case report highlights the need for research for other possible, lesser known etiologies of tendon pathology. Therapeutic, Level IV, Case Study.

Fever of Unknown Origin in Childhood.

PubMed

Chusid, Michael J

2017-02-01

Childhood fever of unknown origin (FUO) is most often related to an underlying infection but can also be associated with a variety of neoplastic, rheumatologic, and inflammatory conditions. Repeated, focused reviews of patient history and physical examination are often helpful in suggesting a likely diagnosis. Diagnostic workup should be staged, usually leaving invasive testing for last. Advances in molecular genetic techniques have increased the importance of these assays in the diagnosis of FUO in children. Copyright © 2016 Elsevier Inc. All rights reserved.

48 CFR 52.222-49 - Service Contract Act-Place of Performance Unknown.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 2 2010-10-01 2010-10-01 false Service Contract Act-Place... Provisions and Clauses 52.222-49 Service Contract Act—Place of Performance Unknown. As prescribed in 22.1006(f), insert the following clause: Service Contract Act—Place of Performance Unknown (MAY 1989) (a...

Pentaerythritol Tetranitrate (PETN) Surveillance by HPLC-MS: Instrumental Parameters Development

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

Harvey, C A; Meissner, R

Surveillance of PETN Homologs in the stockpile here at LLNL is currently carried out by high performance liquid chromatography (HPLC) with ultra violet (UV) detection. Identification of unknown chromatographic peaks with this detection scheme is severely limited. The design agency is aware of the limitations of this methodology and ordered this study to develop instrumental parameters for the use of a currently owned mass spectrometer (MS) as the detection system. The resulting procedure would be a ''drop-in'' replacement for the current surveillance method (ERD04-524). The addition of quadrupole mass spectrometry provides qualitative identification of PETN and its homologs (Petrin, DiPEHN,more » TriPEON, and TetraPEDN) using a LLNL generated database, while providing mass clues to the identity of unknown chromatographic peaks.« less

The Fully-Functioning University and Its Contribution to Society

ERIC Educational Resources Information Center

Bourner, Tom; Rospigliosi, Asher; Heath, Linda

2017-01-01

This is the concluding article of a series of four articles, which started by introducing the concept of the "fully-functioning university" in 2008. Subsequent articles have looked at the consequences of this concept for the higher education of students and the advancement of knowledge. This article is about the fully-functioning…

Fully implicit moving mesh adaptive algorithm

NASA Astrophysics Data System (ADS)

Serazio, C.; Chacon, L.; Lapenta, G.

2006-10-01

In many problems of interest, the numerical modeler is faced with the challenge of dealing with multiple time and length scales. The former is best dealt with with fully implicit methods, which are able to step over fast frequencies to resolve the dynamical time scale of interest. The latter requires grid adaptivity for efficiency. Moving-mesh grid adaptive methods are attractive because they can be designed to minimize the numerical error for a given resolution. However, the required grid governing equations are typically very nonlinear and stiff, and of considerably difficult numerical treatment. Not surprisingly, fully coupled, implicit approaches where the grid and the physics equations are solved simultaneously are rare in the literature, and circumscribed to 1D geometries. In this study, we present a fully implicit algorithm for moving mesh methods that is feasible for multidimensional geometries. Crucial elements are the development of an effective multilevel treatment of the grid equation, and a robust, rigorous error estimator. For the latter, we explore the effectiveness of a coarse grid correction error estimator, which faithfully reproduces spatial truncation errors for conservative equations. We will show that the moving mesh approach is competitive vs. uniform grids both in accuracy (due to adaptivity) and efficiency. Results for a variety of models 1D and 2D geometries will be presented. L. Chac'on, G. Lapenta, J. Comput. Phys., 212 (2), 703 (2006) G. Lapenta, L. Chac'on, J. Comput. Phys., accepted (2006)

Multisensor Parallel Largest Ellipsoid Distributed Data Fusion with Unknown Cross-Covariances

PubMed Central

Liu, Baoyu; Zhan, Xingqun; Zhu, Zheng H.

2017-01-01

As the largest ellipsoid (LE) data fusion algorithm can only be applied to two-sensor system, in this contribution, parallel fusion structure is proposed to introduce the LE algorithm into a multisensor system with unknown cross-covariances, and three parallel fusion structures based on different estimate pairing methods are presented and analyzed. In order to assess the influence of fusion structure on fusion performance, two fusion performance assessment parameters are defined as Fusion Distance and Fusion Index. Moreover, the formula for calculating the upper bounds of actual fused error covariances of the presented multisensor LE fusers is also provided. Demonstrated with simulation examples, the Fusion Index indicates fuser’s actual fused accuracy and its sensitivity to the sensor orders, as well as its robustness to the accuracy of newly added sensors. Compared to the LE fuser with sequential structure, the LE fusers with proposed parallel structures not only significantly improve their properties in these aspects, but also embrace better performances in consistency and computation efficiency. The presented multisensor LE fusers generally have better accuracies than covariance intersection (CI) fusion algorithm and are consistent when the local estimates are weakly correlated. PMID:28661442

Identifying known unknowns using the US EPA's CompTox Chemistry Dashboard.

PubMed

McEachran, Andrew D; Sobus, Jon R; Williams, Antony J

2017-03-01

Chemical features observed using high-resolution mass spectrometry can be tentatively identified using online chemical reference databases by searching molecular formulae and monoisotopic masses and then rank-ordering of the hits using appropriate relevance criteria. The most likely candidate "known unknowns," which are those chemicals unknown to an investigator but contained within a reference database or literature source, rise to the top of a chemical list when rank-ordered by the number of associated data sources. The U.S. EPA's CompTox Chemistry Dashboard is a curated and freely available resource for chemistry and computational toxicology research, containing more than 720,000 chemicals of relevance to environmental health science. In this research, the performance of the Dashboard for identifying known unknowns was evaluated against that of the online ChemSpider database, one of the primary resources used by mass spectrometrists, using multiple previously studied datasets reported in the peer-reviewed literature totaling 162 chemicals. These chemicals were examined using both applications via molecular formula and monoisotopic mass searches followed by rank-ordering of candidate compounds by associated references or data sources. A greater percentage of chemicals ranked in the top position when using the Dashboard, indicating an advantage of this application over ChemSpider for identifying known unknowns using data source ranking. Additional approaches are being developed for inclusion into a non-targeted analysis workflow as part of the CompTox Chemistry Dashboard. This work shows the potential for use of the Dashboard in exposure assessment and risk decision-making through significant improvements in non-targeted chemical identification. Graphical abstract Identifying known unknowns in the US EPA's CompTox Chemistry Dashboard from molecular formula and monoisotopic mass inputs.

A reverse KAM method to estimate unknown mutual inclinations in exoplanetary systems

NASA Astrophysics Data System (ADS)

Volpi, Mara; Locatelli, Ugo; Sansottera, Marco

2018-05-01

The inclinations of exoplanets detected via radial velocity method are essentially unknown. We aim to provide estimations of the ranges of mutual inclinations that are compatible with the long-term stability of the system. Focusing on the skeleton of an extrasolar system, i.e. considering only the two most massive planets, we study the Hamiltonian of the three-body problem after the reduction of the angular momentum. Such a Hamiltonian is expanded both in Poincaré canonical variables and in the small parameter D_2, which represents the normalised angular momentum deficit. The value of the mutual inclination is deduced from D_2 and, thanks to the use of interval arithmetic, we are able to consider open sets of initial conditions instead of single values. Looking at the convergence radius of the Kolmogorov normal form, we develop a reverse KAM approach in order to estimate the ranges of mutual inclinations that are compatible with the long-term stability in a KAM sense. Our method is successfully applied to the extrasolar systems HD 141399, HD 143761 and HD 40307.

Recovery of Graded Response Model Parameters: A Comparison of Marginal Maximum Likelihood and Markov Chain Monte Carlo Estimation

ERIC Educational Resources Information Center

Kieftenbeld, Vincent; Natesan, Prathiba

2012-01-01

Markov chain Monte Carlo (MCMC) methods enable a fully Bayesian approach to parameter estimation of item response models. In this simulation study, the authors compared the recovery of graded response model parameters using marginal maximum likelihood (MML) and Gibbs sampling (MCMC) under various latent trait distributions, test lengths, and…

Carcinoma of Unknown Primary Treatment (PDQ®)—Patient Version

Cancer.gov

Carcinoma of unknown primary (CUP), treatment can include surgery, radiation therapy, chemotherapy, or hormone therapy. Get detailed information about the diagnosis and treatment of CUP in this expert-reviewed summary.

Unified sensor management in unknown dynamic clutter

NASA Astrophysics Data System (ADS)

Mahler, Ronald; El-Fallah, Adel

2010-04-01

In recent years the first author has developed a unified, computationally tractable approach to multisensor-multitarget sensor management. This approach consists of closed-loop recursion of a PHD or CPHD filter with maximization of a "natural" sensor management objective function called PENT (posterior expected number of targets). In this paper we extend this approach so that it can be used in unknown, dynamic clutter backgrounds.

Fully On-the-Job Training: Experiences and Steps Ahead

ERIC Educational Resources Information Center

Wood, Susanne

2004-01-01

Fully on-the-job training, the majority of which is conducted in the workplace as part of the normal experience of the employee, is perceived to offer benefits to apprentices/ trainees, employers and registered training organisations. This report finds fully on-the-job training is viewed by learners and registered training organisations as a good…

Performance Analysis of Blind Subspace-Based Signature Estimation Algorithms for DS-CDMA Systems with Unknown Correlated Noise

NASA Astrophysics Data System (ADS)

Zarifi, Keyvan; Gershman, Alex B.

2006-12-01

We analyze the performance of two popular blind subspace-based signature waveform estimation techniques proposed by Wang and Poor and Buzzi and Poor for direct-sequence code division multiple-access (DS-CDMA) systems with unknown correlated noise. Using the first-order perturbation theory, analytical expressions for the mean-square error (MSE) of these algorithms are derived. We also obtain simple high SNR approximations of the MSE expressions which explicitly clarify how the performance of these techniques depends on the environmental parameters and how it is related to that of the conventional techniques that are based on the standard white noise assumption. Numerical examples further verify the consistency of the obtained analytical results with simulation results.

Fully automatic characterization and data collection from crystals of biological macromolecules

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

Svensson, Olof; Malbet-Monaco, Stéphanie; Popov, Alexander

A fully automatic system has been developed that performs X-ray centring and characterization of, and data collection from, large numbers of cryocooled crystals without human intervention. Considerable effort is dedicated to evaluating macromolecular crystals at synchrotron sources, even for well established and robust systems. Much of this work is repetitive, and the time spent could be better invested in the interpretation of the results. In order to decrease the need for manual intervention in the most repetitive steps of structural biology projects, initial screening and data collection, a fully automatic system has been developed to mount, locate, centre to themore » optimal diffraction volume, characterize and, if possible, collect data from multiple cryocooled crystals. Using the capabilities of pixel-array detectors, the system is as fast as a human operator, taking an average of 6 min per sample depending on the sample size and the level of characterization required. Using a fast X-ray-based routine, samples are located and centred systematically at the position of highest diffraction signal and important parameters for sample characterization, such as flux, beam size and crystal volume, are automatically taken into account, ensuring the calculation of optimal data-collection strategies. The system is now in operation at the new ESRF beamline MASSIF-1 and has been used by both industrial and academic users for many different sample types, including crystals of less than 20 µm in the smallest dimension. To date, over 8000 samples have been evaluated on MASSIF-1 without any human intervention.« less

Spatiotemporal Bayesian analysis of Lyme disease in New York state, 1990-2000.

PubMed

Chen, Haiyan; Stratton, Howard H; Caraco, Thomas B; White, Dennis J

2006-07-01

Mapping ordinarily increases our understanding of nontrivial spatial and temporal heterogeneities in disease rates. However, the large number of parameters required by the corresponding statistical models often complicates detailed analysis. This study investigates the feasibility of a fully Bayesian hierarchical regression approach to the problem and identifies how it outperforms two more popular methods: crude rate estimates (CRE) and empirical Bayes standardization (EBS). In particular, we apply a fully Bayesian approach to the spatiotemporal analysis of Lyme disease incidence in New York state for the period 1990-2000. These results are compared with those obtained by CRE and EBS in Chen et al. (2005). We show that the fully Bayesian regression model not only gives more reliable estimates of disease rates than the other two approaches but also allows for tractable models that can accommodate more numerous sources of variation and unknown parameters.

Fully-automated identification of fish species based on otolith contour: using short-time Fourier transform and discriminant analysis (STFT-DA).

PubMed

Salimi, Nima; Loh, Kar Hoe; Kaur Dhillon, Sarinder; Chong, Ving Ching

2016-01-01

Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.

Hybrid graphene-copper UWB array sensor for brain tumor detection via scattering parameters in microwave detection system

NASA Astrophysics Data System (ADS)

Jamlos, Mohd Aminudin; Ismail, Abdul Hafiizh; Jamlos, Mohd Faizal; Narbudowicz, Adam

2017-01-01

Hybrid graphene-copper ultra-wideband array sensor applied to microwave imaging technique is successfully used in detecting and visualizing tumor inside human brain. The sensor made of graphene coated film for the patch while copper for both the transmission line and parasitic element. The hybrid sensor performance is better than fully copper sensor. Hybrid sensor recorded wider bandwidth of 2.0-10.1 GHz compared with fully copper sensor operated from 2.5 to 10.1 GHz. Higher gain of 3.8-8.5 dB is presented by hybrid sensor, while fully copper sensor stated lower gain ranging from 2.6 to 6.7 dB. Both sensors recorded excellent total efficiency averaged at 97 and 94%, respectively. The sensor used for both transmits equivalent signal and receives backscattering signal from stratified human head model in detecting tumor. Difference in the data of the scattering parameters recorded from the head model with presence and absence of tumor is used as the main data to be further processed in confocal microwave imaging algorithm in generating image. MATLAB software is utilized to analyze S-parameter signals obtained from measurement. Tumor presence is indicated by lower S-parameter values compared to higher values recorded by tumor absence.

Finite-time master-slave synchronization and parameter identification for uncertain Lurie systems.

PubMed

Wang, Tianbo; Zhao, Shouwei; Zhou, Wuneng; Yu, Weiqin

2014-07-01

This paper investigates the finite-time master-slave synchronization and parameter identification problem for uncertain Lurie systems based on the finite-time stability theory and the adaptive control method. The finite-time master-slave synchronization means that the state of a slave system follows with that of a master system in finite time, which is more reasonable than the asymptotical synchronization in applications. The uncertainties include the unknown parameters and noise disturbances. An adaptive controller and update laws which ensures the synchronization and parameter identification to be realized in finite time are constructed. Finally, two numerical examples are given to show the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Atmospheric turbulence profiling with unknown power spectral density

NASA Astrophysics Data System (ADS)

Helin, Tapio; Kindermann, Stefan; Lehtonen, Jonatan; Ramlau, Ronny

2018-04-01

Adaptive optics (AO) is a technology in modern ground-based optical telescopes to compensate for the wavefront distortions caused by atmospheric turbulence. One method that allows to retrieve information about the atmosphere from telescope data is so-called SLODAR, where the atmospheric turbulence profile is estimated based on correlation data of Shack-Hartmann wavefront measurements. This approach relies on a layered Kolmogorov turbulence model. In this article, we propose a novel extension of the SLODAR concept by including a general non-Kolmogorov turbulence layer close to the ground with an unknown power spectral density. We prove that the joint estimation problem of the turbulence profile above ground simultaneously with the unknown power spectral density at the ground is ill-posed and propose three numerical reconstruction methods. We demonstrate by numerical simulations that our methods lead to substantial improvements in the turbulence profile reconstruction compared to the standard SLODAR-type approach. Also, our methods can accurately locate local perturbations in non-Kolmogorov power spectral densities.

Learned navigation in unknown terrains: A retraction method

NASA Technical Reports Server (NTRS)

Rao, Nageswara S. V.; Stoltzfus, N.; Iyengar, S. Sitharama

1989-01-01

The problem of learned navigation of a circular robot R, of radius delta (is greater than or equal to 0), through a terrain whose model is not a-priori known is considered. Two-dimensional finite-sized terrains populated by an unknown (but, finite) number of simple polygonal obstacles are also considered. The number and locations of the vertices of each obstacle are unknown to R. R is equipped with a sensor system that detects all vertices and edges that are visible from its present location. In this context two problems are covered. In the visit problem, the robot is required to visit a sequence of destination points, and in the terrain model acquisition problem, the robot is required to acquire the complete model of the terrain. An algorithmic framework is presented for solving these two problems using a retraction of the freespace onto the Voronoi diagram of the terrain. Algorithms are then presented to solve the visit problem and the terrain model acquisition problem.

Characteristic Cytokine and Chemokine Profiles in Encephalitis of Infectious, Immune-Mediated, and Unknown Aetiology

PubMed Central

Michael, Benedict D.; Griffiths, Michael J.; Granerod, Julia; Brown, David; Davies, Nicholas W. S.; Borrow, Ray; Solomon, Tom

2016-01-01

Background Encephalitis is parenchymal brain inflammation due to infectious or immune-mediated processes. However, in 15–60% the cause remains unknown. This study aimed to determine if the cytokine/chemokine-mediated host response can distinguish infectious from immune-mediated cases, and whether this may give a clue to aetiology in those of unknown cause. Methods We measured 38 mediators in serum and cerebrospinal fluid (CSF) of patients from the Health Protection Agency Encephalitis Study. Of serum from 78 patients, 38 had infectious, 20 immune-mediated, and 20 unknown aetiology. Of CSF from 37 patients, 20 had infectious, nine immune-mediated and eight unknown aetiology. Results Heat-map analysis of CSF mediator interactions was different for infectious and immune-mediated cases, and that of the unknown aetiology group was similar to the infectious pattern. Higher myeloperoxidase (MPO) concentrations were found in infectious than immune-mediated cases, in serum and CSF (p = 0.01 and p = 0.006). Serum MPO was also higher in unknown than immune-mediated cases (p = 0.03). Multivariate analysis selected serum MPO; classifying 31 (91%) as infectious (p = 0.008) and 17 (85%) as unknown (p = 0.009) as opposed to immune-mediated. CSF data also selected MPO classifying 11 (85%) as infectious as opposed to immune-mediated (p = 0.036). CSF neutrophils were detected in eight (62%) infective and one (14%) immune-mediated cases (p = 0.004); CSF MPO correlated with neutrophils (p<0.0001). Conclusions Mediator profiles of infectious aetiology differed from immune-mediated encephalitis; and those of unknown cause were similar to infectious cases, raising the hypothesis of a possible undiagnosed infectious cause. Particularly, neutrophils and MPO merit further investigation. PMID:26808276

Characteristic Cytokine and Chemokine Profiles in Encephalitis of Infectious, Immune-Mediated, and Unknown Aetiology.

PubMed

Michael, Benedict D; Griffiths, Michael J; Granerod, Julia; Brown, David; Davies, Nicholas W S; Borrow, Ray; Solomon, Tom

2016-01-01

Encephalitis is parenchymal brain inflammation due to infectious or immune-mediated processes. However, in 15-60% the cause remains unknown. This study aimed to determine if the cytokine/chemokine-mediated host response can distinguish infectious from immune-mediated cases, and whether this may give a clue to aetiology in those of unknown cause. We measured 38 mediators in serum and cerebrospinal fluid (CSF) of patients from the Health Protection Agency Encephalitis Study. Of serum from 78 patients, 38 had infectious, 20 immune-mediated, and 20 unknown aetiology. Of CSF from 37 patients, 20 had infectious, nine immune-mediated and eight unknown aetiology. Heat-map analysis of CSF mediator interactions was different for infectious and immune-mediated cases, and that of the unknown aetiology group was similar to the infectious pattern. Higher myeloperoxidase (MPO) concentrations were found in infectious than immune-mediated cases, in serum and CSF (p = 0.01 and p = 0.006). Serum MPO was also higher in unknown than immune-mediated cases (p = 0.03). Multivariate analysis selected serum MPO; classifying 31 (91%) as infectious (p = 0.008) and 17 (85%) as unknown (p = 0.009) as opposed to immune-mediated. CSF data also selected MPO classifying 11 (85%) as infectious as opposed to immune-mediated (p = 0.036). CSF neutrophils were detected in eight (62%) infective and one (14%) immune-mediated cases (p = 0.004); CSF MPO correlated with neutrophils (p<0.0001). Mediator profiles of infectious aetiology differed from immune-mediated encephalitis; and those of unknown cause were similar to infectious cases, raising the hypothesis of a possible undiagnosed infectious cause. Particularly, neutrophils and MPO merit further investigation.

Neurological Autoantibody Prevalence in Epilepsy of Unknown Etiology.

PubMed

Dubey, Divyanshu; Alqallaf, Abdulradha; Hays, Ryan; Freeman, Matthew; Chen, Kevin; Ding, Kan; Agostini, Mark; Vernino, Steven

2017-04-01

Autoimmune epilepsy is an underrecognized condition, and its true incidence is unknown. Identifying patients with an underlying autoimmune origin is critical because these patients' condition may remain refractory to conventional antiseizure medications but may respond to immunotherapy. To determine the prevalence of neurological autoantibodies (Abs) among adult patients with epilepsy of unknown etiology. Consecutive patients presenting to neurology services with new-onset epilepsy or established epilepsy of unknown etiology were identified. Serum samples were tested for autoimmune encephalitis Abs as well as thyroperoxidase (TPO) and glutamic acid decarboxylase 65 (GAD65) Abs. An antibody prevalence in epilepsy (APE) score based on clinical characteristics was assigned prospectively. Data were collected from June 1, 2015, to June 1, 2016. Presence of neurological Abs. A score based on clinical characteristics was assigned to estimate the probability of seropositivity prior to antibody test results. Good seizure outcome was estimated on the basis of significant reduction of seizure frequency at the first follow-up or seizure freedom. Of the 127 patients (68 males and 59 females) enrolled in the study, 15 were subsequently excluded after identification of an alternative diagnosis. Serum Abs suggesting a potential autoimmune etiology were detected in 39 (34.8%) cases. More than 1 Ab was detected in 7 patients (6.3%): 3 (2.7%) had TPO-Ab and voltage-gated potassium channel complex (VGKCc) Ab, 2 (1.8%) had GAD65-Ab and VGKCc-Ab, 1 had TPO-Ab and GAD65-Ab, and 1 had anti-Hu Ab and GAD65-Ab. Thirty-two patients (28.6%) had a single Ab marker. Among 112 patients included in the study, 15 (13.4%) had TPO-Ab, 14 (12.5%) had GAD65-Ab, 12 (10.7%) had VGKCc (4 of whom were positive for leucine-rich glioma-inactivated protein 1 [LGI1] Ab), and 4 (3.6%) had N-methyl-D-aspartate receptor (NMDAR) Ab. Even after excluding TPO-Ab and low-titer GAD65-Ab, Abs strongly suggesting an

Influence of multiple categories on the prediction of unknown properties

PubMed Central

Verde, Michael F.; Murphy, Gregory L.; Ross, Brian H.

2006-01-01

Knowing an item's category helps us predict its unknown properties. Previous studies suggest that when asked to evaluate the probability of an unknown property, people tend to consider only an item's most likely category, ignoring alternative categories. In the present study, property prediction took the form of either a probability rating or a speeded, binary-choice judgment. Consistent with past findings, subjects ignored alternative categories in their probability ratings. However, their binary-choice judgments were influenced by alternative categories. This novel finding suggests that the way category knowledge is used in prediction depends critically on the form of the prediction. PMID:16156183

Dealing with Unknown Variables in Policy/Program Evaluation.

ERIC Educational Resources Information Center

Nagel, Stuart S.

1983-01-01

Threshold analysis (TA) is introduced as an evaluation model. TA converts unknown variables into questions as to whether a given benefit, cost, or success probability is more or less than a threshold, above which the proposed project would be profitable, and below which it would be unprofitable. (Author/PN)

Identifying known unknowns using the US EPA's CompTox ...

EPA Pesticide Factsheets

Chemical features observed using high-resolution mass spectrometry can be tentatively identified using online chemical reference databases by searching molecular formulae and monoisotopic masses and then rank-ordering of the hits using appropriate relevance criteria. The most likely candidate “known unknowns,” which are those chemicals unknown to an investigator but contained within a reference database or literature source, rise to the top of a chemical list when rank-ordered by the number of associated data sources. The U.S. EPA’s CompTox Chemistry Dashboard is a curated and freely available resource for chemistry and computational toxicology research, containing more than 720,000 chemicals of relevance to environmental health science. In this research, the performance of the Dashboard for identifying “known unknowns” was evaluated against that of the online ChemSpider database, one of the primary resources used by mass spectrometrists, using multiple previously studied datasets reported in the peer-reviewed literature totaling 162 chemicals. These chemicals were examined using both applications via molecular formula and monoisotopic mass searches followed by rank-ordering of candidate compounds by associated references or data sources. A greater percentage of chemicals ranked in the top position when using the Dashboard, indicating an advantage of this application over ChemSpider for identifying known unknowns using data source ranking. Addition

Water channel experiments of a novel fully-passive flapping-foil turbine

NASA Astrophysics Data System (ADS)

Boudreau, Matthieu; Dumas, Guy; Rahimpour, Mostafa; Oshkai, Peter

2016-11-01

Experiments have been conducted to assess the performances of a fully-passive flapping-foil hydrokinetic turbine for which the blade's motions are stemming from the interaction between the blade's elastic supports (springs and dampers) and the flow field. Previous numerical studies conducted by Peng & Zhu (2009) and Zhu (2012) have proved that a simplified version of such a turbine can extract a substantial amount of energy from the flow while offering the potential to greatly simplify the complex mechanical apparatus needed to constrain and link the blade's pitching and heaving motions in the case of the more classical flapping-foil turbine (e.g., Kinsey et al., 2011). Based on the promising numerical investigations of Veilleux (2014) and Veilleux & Dumas (2016), who proposed a more general version of this novel concept, a prototype has been built and tested in a water channel at a chord Reynolds number of 17,000. Periodic motions of large amplitudes have been observed leading to interesting energy harvesting efficiencies reaching 25% for some specific sets of structural parameters. The sensitivity of the turbine's dynamics to each of the seven structural parameters appearing in the equations of motion has been experimentally evaluated around a case close to the optimal one. Financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC) is gratefully acknowledged by the authors.

A Hybrid Search Algorithm for Swarm Robots Searching in an Unknown Environment

PubMed Central

Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

2014-01-01

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency. PMID:25386855

A hybrid search algorithm for swarm robots searching in an unknown environment.

PubMed

Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

2014-01-01

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.

CMOS serial link for fully duplexed data communication

NASA Astrophysics Data System (ADS)

Lee, Kyeongho; Kim, Sungjoon; Ahn, Gijung; Jeong, Deog-Kyoon

1995-04-01

This paper describes a CMOS serial link allowing fully duplexed 500 Mbaud serial data communication. The CMOS serial link is a robust and low-cost solution to high data rate requirements. A central charge pump PLL for generating multiphase clocks for oversampling is shared by several serial link channels. Fully duplexed serial data communication is realized in the bidirectional bridge by separating incoming data from the mixed signal on the cable end. The digital PLL accomplishes process-independent data recovery by using a low-ratio oversampling, a majority voting, and a parallel data recovery scheme. Mostly, digital approach could extend its bandwidth further with scaled CMOS technology. A single channel serial link and a charge pump PLL are integrated in a test chip using 1.2 micron CMOS process technology. The test chip confirms upto 500 Mbaud unidirectional mode operation and 320 Mbaud fully duplexed mode operation with pseudo random data patterns.

Fully kinetic simulations of dense plasma focus Z-pinch devices.

PubMed

Schmidt, A; Tang, V; Welch, D

2012-11-16

Dense plasma focus Z-pinch devices are sources of copious high energy electrons and ions, x rays, and neutrons. The mechanisms through which these physically simple devices generate such high-energy beams in a relatively short distance are not fully understood. We now have, for the first time, demonstrated a capability to model these plasmas fully kinetically, allowing us to simulate the pinch process at the particle scale. We present here the results of the initial kinetic simulations, which reproduce experimental neutron yields (~10(7)) and high-energy (MeV) beams for the first time. We compare our fluid, hybrid (kinetic ions and fluid electrons), and fully kinetic simulations. Fluid simulations predict no neutrons and do not allow for nonthermal ions, while hybrid simulations underpredict neutron yield by ~100x and exhibit an ion tail that does not exceed 200 keV. Only fully kinetic simulations predict MeV-energy ions and experimental neutron yields. A frequency analysis in a fully kinetic simulation shows plasma fluctuations near the lower hybrid frequency, possibly implicating lower hybrid drift instability as a contributor to anomalous resistivity in the plasma.

Genetics Experts Unite to I.D. Unknown Katrina Victims

MedlinePlus

... News From NIH Genetics Experts Unite to I.D. Unknown Katrina Victims Past Issues / Summer 2006 Table ... and genetics," says team member Stephen Sherry, Ph.D., of NLM's National Center for Biotechnology Information, "is ...

Microbial Community Composition of Polyhydroxyalkanoate-Accumulating Organisms in Full-Scale Wastewater Treatment Plants Operated in Fully Aerobic Mode

PubMed Central

Oshiki, Mamoru; Onuki, Motoharu; Satoh, Hiroyasu; Mino, Takashi

2013-01-01

The removal of biodegradable organic matter is one of the most important objectives in biological wastewater treatments. Polyhydroxyalkanoate (PHA)-accumulating organisms (PHAAOs) significantly contribute to the removal of biodegradable organic matter; however, their microbial community composition is mostly unknown. In the present study, the microbial community composition of PHAAOs was investigated at 8 full-scale wastewater treatment plants (WWTPs), operated in fully aerobic mode, by fluorescence in situ hybridization (FISH) analysis and post-FISH Nile blue A (NBA) staining techniques. Our results demonstrated that 1) PHAAOs were in the range of 11–18% in the total number of cells, and 2) the microbial community composition of PHAAOs was similar at the bacterial domain/phylum/class/order level among the 8 full-scale WWTPs, and dominant PHAAOs were members of the class Alphaproteobacteria and Betaproteobacteria. The microbial community composition of α- and β-proteobacterial PHAAOs was examined by 16S rRNA gene clone library analysis and further by applying a set of newly designed oligonucleotide probes targeting 16S rRNA gene sequences of α- or β-proteobacterial PHAAOs. The results demonstrated that the microbial community composition of PHAAOs differed in the class Alphaproteobacteria and Betaproteobacteria, which possibly resulted in a different PHA accumulation capacity among the WWTPs (8.5–38.2 mg-C g-VSS−1 h−1). The present study extended the knowledge of the microbial diversity of PHAAOs in full-scale WWTPs operated in fully aerobic mode. PMID:23257912

Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process

NASA Astrophysics Data System (ADS)

Nakanishi, W.; Fuse, T.; Ishikawa, T.

2015-05-01

This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.

PV systems photoelectric parameters determining for field conditions and real operation conditions

NASA Astrophysics Data System (ADS)

Shepovalova, Olga V.

2018-05-01

In this work, research experience and reference documentation have been generalized related to PV systems photoelectric parameters (PV array output parameters) determining. The basic method has been presented that makes it possible to determine photoelectric parameters with the state-of-the-art reliability and repeatability. This method provides an effective tool for PV systems comparison and evaluation of PV system parameters that the end-user will have in the course of its real operation for compliance with those stipulated in reference documentation. The method takes in consideration all parameters that may possibly affect photoelectric performance and that are supported by sufficiently valid procedures for their values testing. Test conditions, requirements for equipment subject to tests and test preparations have been established and the test procedure for fully equipped PV system in field tests and in real operation conditions has been described.

Changes of Pain Perception, Autonomic Function, and Endocrine Parameters during Treatment of Anorectic Adolescents

ERIC Educational Resources Information Center

Bar, Karl-Jurgen; Boettger, Silke; Wagner, Gerd; Wilsdorf, Christine; Gerhard, Uwe Jens; Boettger, Michael K.; Blanz, Bernhard; Sauer, Heinrich

2006-01-01

Objectives: The underlying mechanisms of reduced pain perception in anorexia nervosa (AN) are unknown. To gain more insight into the pathology, the authors investigated pain perception, autonomic function, and endocrine parameters before and during successful treatment of adolescent AN patients. Method: Heat pain perception was assessed in 15…

A fully-stochasticized, age-structured population model for population viability analysis of fish: Lower Missouri River endangered pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Albers, Janice; Green, Nicholas; Moran, Edward H.

2017-01-01

We develop a fully-stochasticized, age-structured population model suitable for population viability analysis (PVA) of fish and demonstrate its use with the endangered pallid sturgeon (Scaphirhynchus albus) of the Lower Missouri River as an example. The model incorporates three levels of variance: parameter variance (uncertainty about the value of a parameter itself) applied at the iteration level, temporal variance (uncertainty caused by random environmental fluctuations over time) applied at the time-step level, and implicit individual variance (uncertainty caused by differences between individuals) applied within the time-step level. We found that population dynamics were most sensitive to survival rates, particularly age-2+ survival, and to fecundity-at-length. The inclusion of variance (unpartitioned or partitioned), stocking, or both generally decreased the influence of individual parameters on population growth rate. The partitioning of variance into parameter and temporal components had a strong influence on the importance of individual parameters, uncertainty of model predictions, and quasiextinction risk (i.e., pallid sturgeon population size falling below 50 age-1+ individuals). Our findings show that appropriately applying variance in PVA is important when evaluating the relative importance of parameters, and reinforce the need for better and more precise estimates of crucial life-history parameters for pallid sturgeon.

Control of polarization rotation in nonlinear propagation of fully structured light

NASA Astrophysics Data System (ADS)

Gibson, Christopher J.; Bevington, Patrick; Oppo, Gian-Luca; Yao, Alison M.

2018-03-01

Knowing and controlling the spatial polarization distribution of a beam is of importance in applications such as optical tweezing, imaging, material processing, and communications. Here we show how the polarization distribution is affected by both linear and nonlinear (self-focusing) propagation. We derive an analytical expression for the polarization rotation of fully structured light (FSL) beams during linear propagation and show that the observed rotation is due entirely to the difference in Gouy phase between the two eigenmodes comprising the FSL beams, in excellent agreement with numerical simulations. We also explore the effect of cross-phase modulation due to a self-focusing (Kerr) nonlinearity and show that polarization rotation can be controlled by changing the eigenmodes of the superposition, and physical parameters such as the beam size, the amount of Kerr nonlinearity, and the input power. Finally, we show that by biasing cylindrical vector beams to have elliptical polarization, we can vary the polarization state from radial through spiral to azimuthal using nonlinear propagation.

Conduction in fully ionized liquid metals

NASA Technical Reports Server (NTRS)

Stevenson, D. J.; Ashcroft, N. W.

1973-01-01

Electron transport is considered in high density fully ionized liquid metals. Ionic structure is described in terms of hard-sphere correlation functions and the scattering is determined from self-consistently screened point ions. Applications to the physical properties of the deep interior of Jupiter are briefly considered.

Metastatic Neuroendocrine Carcinoma of Unknown Origin Arising in the Femoral Nerve Sheath.

PubMed

Candy, Nicholas; Young, Adam; Allinson, Kieren; Carr, Oliver; McMillen, Jason; Trivedi, Rikin

2017-08-01

Metastatic neuroendocrine carcinoma of unknown origin is a rare condition, usually presenting with lesions in the liver and/or lung. We present the first reported case of a metastatic neuroendocrine carcinoma of unknown origin arising in the femoral nerve sheath. Magnetic resonance imaging demonstrated what was thought to be a schwannoma in the left femoral nerve sheath in the proximal femoral triangle, immediately inferior to the anterior inferior iliac spine. At the time of operation, the tumor capsule was invading surrounding tissue, as well as three trunks of the femoral nerve. The patient underwent a subtotal resection, preserving the integrity of the residual functioning femoral nerve trunks. Histologic evaluation determined that the tumor had features consistent with a metastatic neuroendocrine carcinoma of unknown primary origin. The patient recovered well postoperatively, and subsequent radiologic evaluation failed to demonstrate a potential primary site. Unfortunately, the patient re-presented with disease progression and was subsequently referred to palliative care. We recommend that there is a definite role for surgery in the management of solitary neuroendocrine carcinoma of unknown origin. Copyright © 2017 Elsevier Inc. All rights reserved.

Fully CMOS-compatible titanium nitride nanoantennas

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

Briggs, Justin A., E-mail: jabriggs@stanford.edu; Department of Materials Science and Engineering, Stanford University, 496 Lomita Mall, Stanford, California 94305; Naik, Gururaj V.

CMOS-compatible fabrication of plasmonic materials and devices will accelerate the development of integrated nanophotonics for information processing applications. Using low-temperature plasma-enhanced atomic layer deposition (PEALD), we develop a recipe for fully CMOS-compatible titanium nitride (TiN) that is plasmonic in the visible and near infrared. Films are grown on silicon, silicon dioxide, and epitaxially on magnesium oxide substrates. By optimizing the plasma exposure per growth cycle during PEALD, carbon and oxygen contamination are reduced, lowering undesirable loss. We use electron beam lithography to pattern TiN nanopillars with varying diameters on silicon in large-area arrays. In the first reported single-particle measurements onmore » plasmonic TiN, we demonstrate size-tunable darkfield scattering spectroscopy in the visible and near infrared regimes. The optical properties of this CMOS-compatible material, combined with its high melting temperature and mechanical durability, comprise a step towards fully CMOS-integrated nanophotonic information processing.« less

Type Ia Supernova Intrinsic Magnitude Dispersion and the Fitting of Cosmological Parameters

NASA Astrophysics Data System (ADS)

Kim, A. G.

2011-02-01

I present an analysis for fitting cosmological parameters from a Hubble diagram of a standard candle with unknown intrinsic magnitude dispersion. The dispersion is determined from the data, simultaneously with the cosmological parameters. This contrasts with the strategies used to date. The advantages of the presented analysis are that it is done in a single fit (it is not iterative), it provides a statistically founded and unbiased estimate of the intrinsic dispersion, and its cosmological-parameter uncertainties account for the intrinsic-dispersion uncertainty. Applied to Type Ia supernovae, my strategy provides a statistical measure to test for subtypes and assess the significance of any magnitude corrections applied to the calibrated candle. Parameter bias and differences between likelihood distributions produced by the presented and currently used fitters are negligibly small for existing and projected supernova data sets.

Systematic parameter inference in stochastic mesoscopic modeling

NASA Astrophysics Data System (ADS)

Lei, Huan; Yang, Xiu; Li, Zhen; Karniadakis, George Em

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are "sparse". The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

Systematic parameter inference in stochastic mesoscopic modeling

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

Lei, Huan; Yang, Xiu; Li, Zhen

2017-02-01

We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the priormore » knowledge that the coefficients are “sparse”. The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.« less

Macro controlling of copper oxide deposition processes and spray mode by using home-made fully computerized spray pyrolysis system

NASA Astrophysics Data System (ADS)

Essa, Mohammed Sh.; Chiad, Bahaa T.; Shafeeq, Omer Sh.

2017-09-01

Thin Films of Copper Oxide (CuO) absorption layer have been deposited using home-made Fully Computerized Spray Pyrolysis Deposition system FCSPD on glass substrates, at the nozzle to substrate distance equal to 20,35 cm, and computerized spray mode (continues spray, macro-control spray). The substrate temperature has been kept at 450 °c with the optional user can enter temperature tolerance values ± 5 °C. Also that fixed molar concentration of 0.1 M, and 2D platform speed or deposition platform speed of 4mm/s. more than 1000 instruction program code, and specific design of graphical user interface GUI to fully control the deposition process and real-time monitoring and controlling the deposition temperature at every 200 ms. The changing in the temperature has been recorded during deposition processes, in addition to all deposition parameters. The films have been characterized to evaluate the thermal distribution over the X, Y movable hot plate, the structure and optical energy gap, thermal and temperature distribution exhibited a good and uniform distribution over 20 cm2 hot plate area, X-ray diffraction (XRD) measurement revealed that the films are polycrystalline in nature and can be assigned to monoclinic CuO structure. Optical band gap varies from 1.5-1.66 eV depending on deposition parameter.

Fully probabilistic control design in an adaptive critic framework.

PubMed

Herzallah, Randa; Kárný, Miroslav

2011-12-01

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem; in particular, very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic control algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this paper. Copyright © 2011 Elsevier Ltd. All rights reserved.

Impact of Accurate 30-Day Status on Operative Mortality: Wanted Dead or Alive, Not Unknown.

PubMed

Ring, W Steves; Edgerton, James R; Herbert, Morley; Prince, Syma; Knoff, Cathy; Jenkins, Kristin M; Jessen, Michael E; Hamman, Baron L

2017-12-01

Risk-adjusted operative mortality is the most important quality metric in cardiac surgery for determining The Society of Thoracic Surgeons (STS) Composite Score for star ratings. Accurate 30-day status is required to determine STS operative mortality. The goal of this study was to determine the effect of unknown or missing 30-day status on risk-adjusted operative mortality in a regional STS Adult Cardiac Surgery Database cooperative and demonstrate the ability to correct these deficiencies by matching with an administrative database. STS Adult Cardiac Surgery Database data were submitted by 27 hospitals from five hospital systems to the Texas Quality Initiative (TQI), a regional quality collaborative. TQI data were matched with a regional hospital claims database to resolve unknown 30-day status. The risk-adjusted operative mortality observed-to-expected (O/E) ratio was determined before and after matching to determine the effect of unknown status on the operative mortality O/E. TQI found an excessive (22%) unknown 30-day status for STS isolated coronary artery bypass grafting cases. Matching the TQI data to the administrative claims database reduced the unknowns to 7%. The STS process of imputing unknown 30-day status as alive underestimates the true operative mortality O/E (1.27 before vs 1.30 after match), while excluding unknowns overestimates the operative mortality O/E (1.57 before vs 1.37 after match) for isolated coronary artery bypass grafting. The current STS algorithm of imputing unknown 30-day status as alive and a strategy of excluding cases with unknown 30-day status both result in erroneous calculation of operative mortality and operative mortality O/E. However, external validation by matching with an administrative database can improve the accuracy of clinical databases such as the STS Adult Cardiac Surgery Database. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Red Pine Pocket Mortality - Unknown Cause (Pest Alert)

Treesearch

USDA Forest Service

1985-01-01

Continuing mortality of red pine from an unknown cause has been observed in 30 to 40 year old plantations in southern and west central Wisconsin. A single tree or small group of trees die, followed by mortality of adjacent trees. These circular pockets of dead trees expand up to 0.3 acre per year.

Application of incremental unknowns to the Burgers equation

NASA Technical Reports Server (NTRS)

Choi, Haecheon; Temam, Roger

1993-01-01

In this article, we make a few remarks on the role that attractors and inertial manifolds play in fluid mechanics problems. We then describe the role of incremental unknowns for approximating attractors and inertial manifolds when finite difference multigrid discretizations are used. The relation with direct numerical simulation and large eddy simulation is also mentioned.

Identifying mechanical property parameters of planetary soil using in-situ data obtained from exploration rovers

NASA Astrophysics Data System (ADS)

Ding, Liang; Gao, Haibo; Liu, Zhen; Deng, Zongquan; Liu, Guangjun

2015-12-01

Identifying the mechanical property parameters of planetary soil based on terramechanics models using in-situ data obtained from autonomous planetary exploration rovers is both an important scientific goal and essential for control strategy optimization and high-fidelity simulations of rovers. However, identifying all the terrain parameters is a challenging task because of the nonlinear and coupling nature of the involved functions. Three parameter identification methods are presented in this paper to serve different purposes based on an improved terramechanics model that takes into account the effects of slip, wheel lugs, etc. Parameter sensitivity and coupling of the equations are analyzed, and the parameters are grouped according to their sensitivity to the normal force, resistance moment and drawbar pull. An iterative identification method using the original integral model is developed first. In order to realize real-time identification, the model is then simplified by linearizing the normal and shearing stresses to derive decoupled closed-form analytical equations. Each equation contains one or two groups of soil parameters, making step-by-step identification of all the unknowns feasible. Experiments were performed using six different types of single-wheels as well as a four-wheeled rover moving on planetary soil simulant. All the unknown model parameters were identified using the measured data and compared with the values obtained by conventional experiments. It is verified that the proposed iterative identification method provides improved accuracy, making it suitable for scientific studies of soil properties, whereas the step-by-step identification methods based on simplified models require less calculation time, making them more suitable for real-time applications. The models have less than 10% margin of error comparing with the measured results when predicting the interaction forces and moments using the corresponding identified parameters.

Intrathecal immunoglobulin synthesis in patients with symptomatic epilepsy and epilepsy of unknown etiology ('cryptogenic').

PubMed

Fauser, S; Soellner, C; Bien, C G; Tumani, H

2017-09-01

To compare the frequency of intrathecal immunoglobulin (Ig) synthesis in patients with symptomatic epilepsy and epilepsy of unknown etiology ('cryptogenic'). Patients with epileptic (n = 301) and non-epileptic (n = 10) seizures were retrospectively screened for autochthonous intrathecal Ig synthesis and oligoclonal bands (OCBs) in the cerebrospinal fluid. Intrathecal IgG/OCBs were detected in 8% of patients with epilepsies of unknown etiology, 5% of patients with first seizures of unknown cause and 0-4% of patients with epilepsy due to brain tumors, cerebrovascular disease or other etiologies. Intrathecal IgG/OCBs were not seen in patients with psychogenic seizures. Identical OCBs in serum and cerebrospinal fluid were more common in all patient groups (10-40% depending on underlying etiology). Intrathecal IgG synthesis/OCBs were observed slightly more frequently in patients with 'cryptogenic' epilepsy and with first seizures of unknown etiology than in other patient groups. However, this remained an infrequent finding and thus we could not confirm humoral immunity as a leading disease mechanism in patients with epilepsy in general or with unknown etiology in particular. © 2017 EAN.

Optimal estimation of parameters and states in stochastic time-varying systems with time delay

NASA Astrophysics Data System (ADS)

Torkamani, Shahab; Butcher, Eric A.

2013-08-01

In this study estimation of parameters and states in stochastic linear and nonlinear delay differential systems with time-varying coefficients and constant delay is explored. The approach consists of first employing a continuous time approximation to approximate the stochastic delay differential equation with a set of stochastic ordinary differential equations. Then the problem of parameter estimation in the resulting stochastic differential system is represented as an optimal filtering problem using a state augmentation technique. By adapting the extended Kalman-Bucy filter to the resulting system, the unknown parameters of the time-delayed system are estimated from noise-corrupted, possibly incomplete measurements of the states.

Fully Burdened Cost of Fuel Using Input-Output Analysis

DTIC Science & Technology

2011-12-01

Distribution Model could be used to replace the current seven-step Fully Burdened Cost of Fuel process with a single step, allowing for less complex and...wide extension of the Bulk Fuels Distribution Model could be used to replace the current seven-step Fully Burdened Cost of Fuel process with a single...ABBREVIATIONS AEM Atlantic, Europe, and the Mediterranean AOAs Analysis of Alternatives DAG Defense Acquisition Guidebook DAU Defense Acquisition University

Distributed Time-Varying Formation Robust Tracking for General Linear Multiagent Systems With Parameter Uncertainties and External Disturbances.

PubMed

Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang

2017-05-18

This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.

Fully Implantable Deep Brain Stimulation System with Wireless Power Transmission for Long-term Use in Rodent Models of Parkinson's Disease.

PubMed

Heo, Man Seung; Moon, Hyun Seok; Kim, Hee Chan; Park, Hyung Woo; Lim, Young Hoon; Paek, Sun Ha

2015-03-01

The purpose of this study to develop new deep-brain stimulation system for long-term use in animals, in order to develop a variety of neural prostheses. Our system has two distinguished features, which are the fully implanted system having wearable wireless power transfer and ability to change the parameter of stimulus parameter. It is useful for obtaining a variety of data from a long-term experiment. To validate our system, we performed pre-clinical test in Parkinson's disease-rat models for 4 weeks. Through the in vivo test, we observed the possibility of not only long-term implantation and stability, but also free movement of animals. We confirmed that the electrical stimulation neither caused any side effect nor damaged the electrodes. We proved possibility of our system to conduct the long-term pre-clinical test in variety of parameter, which is available for development of neural prostheses.

The Unknowns and Possible Implications of Mandatory Labeling.

PubMed

McFadden, Brandon R

2017-01-01

The National Bioengineered Food Disclosure Standard requires a mandatory label for genetically modified (GM) food. Currently, some aspects of the bill are unknown, including what constitutes a food to be considered GM. The costs associated with this legislation will depend on how actors in the food value chain respond. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dual ant colony operational modal analysis parameter estimation method

NASA Astrophysics Data System (ADS)

Sitarz, Piotr; Powałka, Bartosz

2018-01-01

Operational Modal Analysis (OMA) is a common technique used to examine the dynamic properties of a system. Contrary to experimental modal analysis, the input signal is generated in object ambient environment. Operational modal analysis mainly aims at determining the number of pole pairs and at estimating modal parameters. Many methods are used for parameter identification. Some methods operate in time while others in frequency domain. The former use correlation functions, the latter - spectral density functions. However, while some methods require the user to select poles from a stabilisation diagram, others try to automate the selection process. Dual ant colony operational modal analysis parameter estimation method (DAC-OMA) presents a new approach to the problem, avoiding issues involved in the stabilisation diagram. The presented algorithm is fully automated. It uses deterministic methods to define the interval of estimated parameters, thus reducing the problem to optimisation task which is conducted with dedicated software based on ant colony optimisation algorithm. The combination of deterministic methods restricting parameter intervals and artificial intelligence yields very good results, also for closely spaced modes and significantly varied mode shapes within one measurement point.

New results on finite-time parameter identification and synchronization of uncertain complex dynamical networks with perturbation

NASA Astrophysics Data System (ADS)

Zhao, Hui; Zheng, Mingwen; Li, Shudong; Wang, Weiping

2018-03-01

Some existing papers focused on finite-time parameter identification and synchronization, but provided incomplete theoretical analyses. Such works incorporated conflicting constraints for parameter identification, therefore, the practical significance could not be fully demonstrated. To overcome such limitations, the underlying paper presents new results of parameter identification and synchronization for uncertain complex dynamical networks with impulsive effect and stochastic perturbation based on finite-time stability theory. Novel results of parameter identification and synchronization control criteria are obtained in a finite time by utilizing Lyapunov function and linear matrix inequality respectively. Finally, numerical examples are presented to illustrate the effectiveness of our theoretical results.

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…

Fast, Nonlinear, Fully Probabilistic Inversion of Large Geophysical Problems

NASA Astrophysics Data System (ADS)

Curtis, A.; Shahraeeni, M.; Trampert, J.; Meier, U.; Cho, G.

2010-12-01

Almost all Geophysical inverse problems are in reality nonlinear. Fully nonlinear inversion including non-approximated physics, and solving for probability distribution functions (pdf’s) that describe the solution uncertainty, generally requires sampling-based Monte-Carlo style methods that are computationally intractable in most large problems. In order to solve such problems, physical relationships are usually linearized leading to efficiently-solved, (possibly iterated) linear inverse problems. However, it is well known that linearization can lead to erroneous solutions, and in particular to overly optimistic uncertainty estimates. What is needed across many Geophysical disciplines is a method to invert large inverse problems (or potentially tens of thousands of small inverse problems) fully probabilistically and without linearization. This talk shows how very large nonlinear inverse problems can be solved fully probabilistically and incorporating any available prior information using mixture density networks (driven by neural network banks), provided the problem can be decomposed into many small inverse problems. In this talk I will explain the methodology, compare multi-dimensional pdf inversion results to full Monte Carlo solutions, and illustrate the method with two applications: first, inverting surface wave group and phase velocities for a fully-probabilistic global tomography model of the Earth’s crust and mantle, and second inverting industrial 3D seismic data for petrophysical properties throughout and around a subsurface hydrocarbon reservoir. The latter problem is typically decomposed into 104 to 105 individual inverse problems, each solved fully probabilistically and without linearization. The results in both cases are sufficiently close to the Monte Carlo solution to exhibit realistic uncertainty, multimodality and bias. This provides far greater confidence in the results, and in decisions made on their basis.

Competing magnetic and spin-gapless semiconducting behavior in fully compensated ferrimagnetic CrVTiAl: Theory and experiment

NASA Astrophysics Data System (ADS)

Venkateswara, Y.; Gupta, Sachin; Samatham, S. Shanmukharao; Varma, Manoj Raama; Enamullah, Suresh, K. G.; Alam, Aftab

2018-02-01

We report the structural, magnetic, and transport properties of the polycrystalline CrVTiAl alloy along with first-principles calculations. The alloy crystallizes in a LiMgPdSn-type structure with a lattice parameter of 6.14 Å at room temperature. The absence of the (111) peak along with the presence of a weak (200) peak indicates the antisite disorder of Al with Cr and V atoms, which is different from the pure DO3 type. Magnetization measurements reveal a magnetic transition near 710 K, a coercive field of ˜100 Oe at 3 K, and a moment of ˜10-3μB/f .u . These observations are indicative of fully compensated ferrimagnetism in the alloy, which is confirmed by theoretical modeling. The temperature coefficient of resistivity is found to be negative, signaling the semiconducting nature. However, the absence of exponential dependence indicates the semiconducting nature with gapless/spin-gapless behavior. Electronic and magnetic properties of CrVTiAl for all three possible crystallographic configurations are studied theoretically. All the configurations are found to be different forms of semiconductors. The ground-state configuration is a fully compensated ferrimagnet with band gaps of 0.58 and 0.30 eV for the spin-up and -down bands, respectively. The next-higher-energy configuration is also fully compensated ferrimagnetic but has a spin-gapless semiconducting nature. The highest-energy configuration corresponds to a nonmagnetic, gapless semiconductor. The energy differences among these configurations are quite small (<1 mRy /atom ), which hints that, at finite temperatures, the alloy exists in a disordered phase, which is a mixture of the three configurations. By taking into account the theoretical and experimental findings, we conclude that CrVTiAl is a fully compensated ferrimagnet with a predominantly spin-gapless semiconducting nature.

Fully synthetic taped insulation cables

DOEpatents

Forsyth, Eric B.; Muller, Albert C.

1984-01-01

A high voltage oil-impregnated electrical cable with fully polymer taped insulation operable to 765 kV. Biaxially oriented, specially processed, polyethylene, polybutene or polypropylene tape with an embossed pattern is wound in multiple layers over a conductive core with a permeable screen around the insulation. Conventional oil which closely matches the dielectric constant of the tape is used, and the cable can be impregnated after field installation because of its excellent impregnation characteristics.

A Modified Cramer-von Mises and Anderson-Darling Test for the Weibull Distribution with Unknown Location and Scale Parameters.

DTIC Science & Technology

1981-12-01

preventing the generation of 16 6 negative location estimators. Because of the invariant pro- perty of the EDF statistics, this transformation will...likelihood. If the parameter estimation method developed by Harter and Moore is used, care must be taken to prevent the location estimators from being...vs A 2 Critical Values, Level-.Ol, n-30 128 , 0 6N m m • w - APPENDIX E Computer Prgrams 129 Program to Calculate the Cramer-von Mises Critical Values

Data pieces-based parameter identification for lithium-ion battery

NASA Astrophysics Data System (ADS)

Gao, Wei; Zou, Yuan; Sun, Fengchun; Hu, Xiaosong; Yu, Yang; Feng, Sen

2016-10-01

Battery characteristics vary with temperature and aging, it is necessary to identify battery parameters periodically for electric vehicles to ensure reliable State-of-Charge (SoC) estimation, battery equalization and safe operation. Aiming for on-board applications, this paper proposes a data pieces-based parameter identification (DPPI) method to identify comprehensive battery parameters including capacity, OCV (open circuit voltage)-Ah relationship and impedance-Ah relationship simultaneously only based on battery operation data. First a vehicle field test was conducted and battery operation data was recorded, then the DPPI method is elaborated based on vehicle test data, parameters of all 97 cells of the battery package are identified and compared. To evaluate the adaptability of the proposed DPPI method, it is used to identify battery parameters of different aging levels and different temperatures based on battery aging experiment data. Then a concept of ;OCV-Ah aging database; is proposed, based on which battery capacity can be identified even though the battery was never fully charged or discharged. Finally, to further examine the effectiveness of the identified battery parameters, they are used to perform SoC estimation for the test vehicle with adaptive extended Kalman filter (AEKF). The result shows good accuracy and reliability.

Sequential Feedback Scheme Outperforms the Parallel Scheme for Hamiltonian Parameter Estimation.

PubMed

Yuan, Haidong

2016-10-14

Measurement and estimation of parameters are essential for science and engineering, where the main quest is to find the highest achievable precision with the given resources and design schemes to attain it. Two schemes, the sequential feedback scheme and the parallel scheme, are usually studied in the quantum parameter estimation. While the sequential feedback scheme represents the most general scheme, it remains unknown whether it can outperform the parallel scheme for any quantum estimation tasks. In this Letter, we show that the sequential feedback scheme has a threefold improvement over the parallel scheme for Hamiltonian parameter estimations on two-dimensional systems, and an order of O(d+1) improvement for Hamiltonian parameter estimation on d-dimensional systems. We also show that, contrary to the conventional belief, it is possible to simultaneously achieve the highest precision for estimating all three components of a magnetic field, which sets a benchmark on the local precision limit for the estimation of a magnetic field.

A modified Leslie-Gower predator-prey interaction model and parameter identifiability

NASA Astrophysics Data System (ADS)

Tripathi, Jai Prakash; Meghwani, Suraj S.; Thakur, Manoj; Abbas, Syed

2018-01-01

In this work, bifurcation and a systematic approach for estimation of identifiable parameters of a modified Leslie-Gower predator-prey system with Crowley-Martin functional response and prey refuge is discussed. Global asymptotic stability is discussed by applying fluctuation lemma. The system undergoes into Hopf bifurcation with respect to parameters intrinsic growth rate of predators (s) and prey reserve (m). The stability of Hopf bifurcation is also discussed by calculating Lyapunov number. The sensitivity analysis of the considered model system with respect to all variables is performed which also supports our theoretical study. To estimate the unknown parameter from the data, an optimization procedure (pseudo-random search algorithm) is adopted. System responses and phase plots for estimated parameters are also compared with true noise free data. It is found that the system dynamics with true set of parametric values is similar to the estimated parametric values. Numerical simulations are presented to substantiate the analytical findings.

Obtaining short-fiber orientation model parameters using non-lubricated squeeze flow

NASA Astrophysics Data System (ADS)

Lambert, Gregory; Wapperom, Peter; Baird, Donald

2017-12-01

Accurate models of fiber orientation dynamics during the processing of polymer-fiber composites are needed for the design work behind important automobile parts. All of the existing models utilize empirical parameters, but a standard method for obtaining them independent of processing does not exist. This study considers non-lubricated squeeze flow through a rectangular channel as a solution. A two-dimensional finite element method simulation of the kinematics and fiber orientation evolution along the centerline of a sample is developed as a first step toward a fully three-dimensional simulation. The model is used to fit to orientation data in a short-fiber-reinforced polymer composite after squeezing. Fiber orientation model parameters obtained in this study do not agree well with those obtained for the same material during startup of simple shear. This is attributed to the vastly different rates at which fibers orient during shearing and extensional flows. A stress model is also used to try to fit to experimental closure force data. Although the model can be tuned to the correct magnitude of the closure force, it does not fully recreate the transient behavior, which is attributed to the lack of any consideration for fiber-fiber interactions.

Body shape changes in the elderly and the influence of density assumptions on segment inertia parameters

NASA Astrophysics Data System (ADS)

Jensen, Robert K.; Fletcher, P.; Abraham, C.

1991-04-01

The segment mass mass proportions and moments of inertia of a sample of twelve females and seven males with mean ages of 67. 4 and 69. 5 years were estimated using textbook proportions based on cadaver studies. These were then compared with the parameters calculated using a mathematical model the zone method. The methodology of the model was fully evaluated for accuracy and precision and judged to be adequate. The results of the comparisons show that for some segments female parameters are quite different from male parameters and inadequately predicted by the cadaver proportions. The largest discrepancies were for the thigh and the trunk. The cadaver predictions were generally less than satisfactory although the common variance for some segments was moderately high. The use ofnon-linear regression and segment anthropometry was illustrated for the thigh moments of inertia and appears to be appropriate. However the predictions from cadaver data need to be examined fully. These results are dependent on the changes in mass and density distribution which occur with aging and the changes which occur with cadaver samples prior to and following death.

Bell nonlocality and fully entangled fraction measured in an entanglement-swapping device without quantum state tomography

NASA Astrophysics Data System (ADS)

Bartkiewicz, Karol; Lemr, Karel; Černoch, Antonín; Miranowicz, Adam

2017-03-01

We propose and experimentally implement an efficient procedure based on entanglement swapping to determine the Bell nonlocality measure of Horodecki et al. [Phys. Lett. A 200, 340 (1995), 10.1016/0375-9601(95)00214-N] and the fully entangled fraction of Bennett et al. [Phys. Rev. A 54, 3824 (1996), 10.1103/PhysRevA.54.3824] of an arbitrary two-qubit polarization-encoded state. The nonlocality measure corresponds to the amount of the violation of the Clauser-Horne-Shimony-Holt (CHSH) optimized over all measurement settings. By using simultaneously two copies of a given state, we measure directly only six parameters. This is an experimental determination of these quantities without quantum state tomography or continuous monitoring of all measurement bases in the usual CHSH inequality tests. We analyze how well the measured degrees of Bell nonlocality and other entanglement witnesses (including the fully entangled fraction and a nonlinear entropic witness) of an arbitrary two-qubit state can estimate its entanglement. In particular, we measure these witnesses and estimate the negativity of various two-qubit Werner states. Our approach could especially be useful for quantum communication protocols based on entanglement swapping.

43. Photographer unknown September 1967 VISITOR INFORMATION KIOSK, LOCATED NEAR ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

43. Photographer unknown September 1967 VISITOR INFORMATION KIOSK, LOCATED NEAR THE POWDER MILL ROAD INTERCHANGE. (NPS/NCR (cn) 9995-C) - Baltimore-Washington Parkway, Greenbelt, Prince George's County, MD

27. photographer unknown 10 July 1938 SHIP LOCK DEDICATION CEREMONIES. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

27. photographer unknown 10 July 1938 SHIP LOCK DEDICATION CEREMONIES. - Bonneville Project, Navigation Lock No. 1, Oregon shore of Columbia River near first Powerhouse, Bonneville, Multnomah County, OR

61. photographer unknown undated FIRST CONCRETE BEING POURED IN DRAFT ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

61. photographer unknown undated FIRST CONCRETE BEING POURED IN DRAFT TUBE FLOOR SLAB. - Bonneville Project, Powerhouse No.1, Spanning Bradford Slough, from Bradford Island, Bonneville, Multnomah County, OR

A fully reconfigurable photonic integrated signal processor

NASA Astrophysics Data System (ADS)

Liu, Weilin; Li, Ming; Guzzon, Robert S.; Norberg, Erik J.; Parker, John S.; Lu, Mingzhi; Coldren, Larry A.; Yao, Jianping

2016-03-01

Photonic signal processing has been considered a solution to overcome the inherent electronic speed limitations. Over the past few years, an impressive range of photonic integrated signal processors have been proposed, but they usually offer limited reconfigurability, a feature highly needed for the implementation of large-scale general-purpose photonic signal processors. Here, we report and experimentally demonstrate a fully reconfigurable photonic integrated signal processor based on an InP-InGaAsP material system. The proposed photonic signal processor is capable of performing reconfigurable signal processing functions including temporal integration, temporal differentiation and Hilbert transformation. The reconfigurability is achieved by controlling the injection currents to the active components of the signal processor. Our demonstration suggests great potential for chip-scale fully programmable all-optical signal processing.

34. photographer unknown September 1937 ROOSEVELT ARRIVING FOR DEDICATION OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

34. photographer unknown September 1937 ROOSEVELT ARRIVING FOR DEDICATION OF BONNEVILLE DAM. - Bonneville Project, Columbia River, 1 mile Northeast of Exit 40, off Interstate 84, Bonneville, Multnomah County, OR

72. photographer unknown 22 November 1935 PLACING CONCRETE FORM FOR ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

72. photographer unknown 22 November 1935 PLACING CONCRETE FORM FOR STATION SERVICE DRAFT TUBES. - Bonneville Project, Powerhouse No.1, Spanning Bradford Slough, from Bradford Island, Bonneville, Multnomah County, OR

NWP model forecast skill optimization via closure parameter variations

NASA Astrophysics Data System (ADS)

Järvinen, H.; Ollinaho, P.; Laine, M.; Solonen, A.; Haario, H.

2012-04-01

We present results of a novel approach to tune predictive skill of numerical weather prediction (NWP) models. These models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. The current practice is to specify manually the numerical parameter values, based on expert knowledge. We developed recently a concept and method (QJRMS 2011) for on-line estimation of the NWP model parameters via closure parameter variations. The method called EPPES ("Ensemble prediction and parameter estimation system") utilizes ensemble prediction infra-structure for parameter estimation in a very cost-effective way: practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating an ensemble of predictions so that each member uses different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In this presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an ensemble prediction system emulator, based on the ECHAM5 atmospheric GCM show that the model tuning capability of EPPES scales up to realistic models and ensemble prediction systems. Finally, preliminary results of EPPES in the context of ECMWF forecasting system are presented.

Fully Polarimetric Passive W-band Millimeter Wave Imager for Wide Area Search

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

Tedeschi, Jonathan R.; Bernacki, Bruce E.; Sheen, David M.

2013-09-27

We describe the design and phenomenology imaging results of a fully polarimetric W-band millimeter wave (MMW) radiometer developed by Pacific Northwest National Laboratory for wide-area search. Operating from 92 - 94 GHz, the W-band radiometer employs a Dicke switching heterodyne design isolating the horizontal and vertical mm-wave components with 40 dB of polarization isolation. Design results are presented for both infinite conjugate off-axis parabolic and finite conjugate off-axis elliptical fore-optics using optical ray tracing and diffraction calculations. The received linear polarizations are down-converted to a microwave frequency band and recombined in a phase-shifting network to produce all six orthogonal polarizationmore » states of light simultaneously, which are used to calculate the Stokes parameters for display and analysis. The resulting system performance produces a heterodyne receiver noise equivalent delta temperature (NEDT) of less than 150m Kelvin. The radiometer provides novel imaging capability by producing all four of the Stokes parameters of light, which are used to create imagery based on the polarization states associated with unique scattering geometries and their interaction with the down welling MMW energy. The polarization states can be exploited in such a way that man-made objects can be located and highlighted in a cluttered scene using methods such as image comparison, color encoding of Stokes parameters, multivariate image analysis, and image fusion with visible and infrared imagery. We also present initial results using a differential imaging approach used to highlight polarization features and reduce common-mode noise. Persistent monitoring of a scene using the polarimetric passive mm-wave technique shows great promise for anomaly detection caused by human activity.« less

Structure and interactions of fully hydrated dioleoylphosphatidylcholine bilayers.

PubMed Central

Tristram-Nagle, S; Petrache, H I; Nagle, J F

1998-01-01

This study focuses on dioleoylphosphatidylcholine (DOPC) bilayers near full hydration. Volumetric data and high-resolution synchrotron x-ray data are used in a method that compares DOPC with well determined gel phase dipalmitoylphosphatidylcholine (DPPC). The key structural quantity obtained is fully hydrated area/lipid A0 = 72.2 +/- 1.1 A2 at 30 degrees C, from which other quantities such as thickness of the bilayer are obtained. Data for samples over osmotic pressures from 0 to 56 atmospheres give an estimate for the area compressibility of KA = 188 dyn/cm. Obtaining the continuous scattering transform and electron density profiles requires correction for liquid crystal fluctuations. Quantitation of these fluctuations opens an experimental window on the fluctuation pressure, the primary repulsive interaction near full hydration. The fluctuation pressure decays exponentially with water spacing, in agreement with analytical results for soft confinement. However, the ratio of decay length lambda(fl) = 5.8 A to hydration pressure decay length lambda = 2.2 A is significantly larger than the value of 2 predicted by analytical theory and close to the ratio obtained in recent simulations. We also obtain the traditional osmotic pressure versus water spacing data. Our analysis of these data shows that estimates of the Hamaker parameter H and the bending modulus Kc are strongly coupled. PMID:9675192

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

PubMed

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

PubMed Central

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

Simulation-based Extraction of Key Material Parameters from Atomic Force Microscopy

NASA Astrophysics Data System (ADS)

Alsafi, Huseen; Peninngton, Gray

Models for the atomic force microscopy (AFM) tip and sample interaction contain numerous material parameters that are often poorly known. This is especially true when dealing with novel material systems or when imaging samples that are exposed to complicated interactions with the local environment. In this work we use Monte Carlo methods to extract sample material parameters from the experimental AFM analysis of a test sample. The parameterized theoretical model that we use is based on the Virtual Environment for Dynamic AFM (VEDA) [1]. The extracted material parameters are then compared with the accepted values for our test sample. Using this procedure, we suggest a method that can be used to successfully determine unknown material properties in novel and complicated material systems. We acknowledge Fisher Endowment Grant support from the Jess and Mildred Fisher College of Science and Mathematics,Towson University.

A Fully Associative, Non-Linear Kinematic, Unified Viscoplastic Model for Titanium Based Matrices

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Castelli, M. G.

1994-01-01

Specific forms for both the Gibb's and complementary dissipation potentials are chosen such that a complete (i.e., fully associative) potential based multiaxial unified viscoplastic model is obtained. This model possesses one tensorial internal state variable that is associated with dislocation substructure, with an evolutionary law that has nonlinear kinematic hardening and both thermal and strain induced recovery mechanisms. A unique aspect of the present model is the inclusion of non-linear hardening through the use of a compliance operator, derived from the Gibb's potential, in the evolution law for the back stress. This non-linear tensorial operator is significant in that it allows both the flow and evolutionary laws to be fully associative (and therefore easily integrated) and greatly influences the multiaxial response under non-proportional loading paths. In addition to this nonlinear compliance operator, a new consistent, potential preserving, internal strain unloading criterion has been introduced to prevent abnormalities in the predicted stress-strain curves, which are present with nonlinear hardening formulations, during unloading and reversed loading of the external variables. Specification of an experimental program for the complete determination of the material functions and parameters for characterizing a metallic matrix, e.g., TIMETAL 21S, is given. The experiments utilized are tensile, creep, and step creep tests. Finally, a comparison of this model and a commonly used Bodner-Partom model is made on the basis of predictive accuracy and numerical efficiency.

Impact of robotic surgery on sexual and urinary functions after fully robotic nerve-sparing total mesorectal excision for rectal cancer.

PubMed

Luca, Fabrizio; Valvo, Manuela; Ghezzi, Tiago Leal; Zuccaro, Massimiliano; Cenciarelli, Sabina; Trovato, Cristina; Sonzogni, Angelica; Biffi, Roberto

2013-04-01

Urinary and sexual dysfunctions are recognized complications of rectal cancer surgery. Their incidence after robotic surgery is as yet unknown. The aim of this study was to prospectively evaluate the impact of robotic surgery for rectal cancer on sexual and urinary functions in male and female patients. From April 2008 to December 2010, 74 patients undergoing fully robotic resection for rectal cancer were prospectively included in the study. Urinary and sexual dysfunctions affecting quality of life were assessed with specific self-administered questionnaires in all patients undergoing robotic total mesorectal excision (RTME). Results were calculated with validated scoring systems and statistically analyzed. The analyses of the questionnaires completed by the 74 patients who underwent RTME showed that sexual function and general sexual satisfaction decreased significantly 1 month after intervention: 19.1 ± 8.7 versus 11.9 ± 10.2 (P < 0.05) for erectile function and 6.9 ± 2.4 versus 5.3 ± 2.5 (P < 0.05) for general satisfaction in men; 2.6 ± 3.3 versus 0.8 ± 1.4 (P < 0.05) and 2.4 ± 2.5 versus 0.7 ± 1.6 (P < 0.05) for arousal and general satisfaction, respectively, in women. Subsequently, both parameters increased progressively, and 1 year after surgery, the values were comparable to those measured before surgery. Concerning urinary function, the grade of incontinence measured 1 year after the intervention was unchanged for both sexes. RTME allows for preservation of urinary and sexual functions. This is probably due to the superior movements of the wristed instruments that facilitate fine dissection, coupled with a stable and magnified view that helps in recognizing the inferior hypogastric plexus.

Fully Decomposable Split Graphs

NASA Astrophysics Data System (ADS)

Broersma, Hajo; Kratsch, Dieter; Woeginger, Gerhard J.

We discuss various questions around partitioning a split graph into connected parts. Our main result is a polynomial time algorithm that decides whether a given split graph is fully decomposable, i.e., whether it can be partitioned into connected parts of order α 1,α 2,...,α k for every α 1,α 2,...,α k summing up to the order of the graph. In contrast, we show that the decision problem whether a given split graph can be partitioned into connected parts of order α 1,α 2,...,α k for a given partition α 1,α 2,...,α k of the order of the graph, is NP-hard.

2. Photocopy of photograph (from Reading Co. Archives) Photographer unknown ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. Photocopy of photograph (from Reading Co. Archives) Photographer unknown ca. 1937 NORTHEAST FRONT AND SOUTHEAST SIDE - Philadelphia & Reading Railroad, Terminal Station, 1115-1141 Market Street, Philadelphia, Philadelphia County, PA

62. photographer unknown undated ERECTING FORMS, PLACING REINFORCING STEEL, AND ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

62. photographer unknown undated ERECTING FORMS, PLACING REINFORCING STEEL, AND CONCRETING DRAFT PIER OF POWERHOUSE. - Bonneville Project, Powerhouse No.1, Spanning Bradford Slough, from Bradford Island, Bonneville, Multnomah County, OR

73. photographer unknown 9 January 1936 TOP OF DRAFT TUBE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

73. photographer unknown 9 January 1936 TOP OF DRAFT TUBE LINER AND SPEED RING PIERS. - Bonneville Project, Powerhouse No.1, Spanning Bradford Slough, from Bradford Island, Bonneville, Multnomah County, OR

60. photographer unknown undated CONCRETE BEING POURED ON CENTER PORTION ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

60. photographer unknown undated CONCRETE BEING POURED ON CENTER PORTION OF DRAFT TUBE FLOOR SLAB. - Bonneville Project, Powerhouse No.1, Spanning Bradford Slough, from Bradford Island, Bonneville, Multnomah County, OR

80. photographer unknown 7 June 1937 PLACING MAIN THRUST BEARING ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

80. photographer unknown 7 June 1937 PLACING MAIN THRUST BEARING ASSEMBLY IN UNIT NO 2. - Bonneville Project, Powerhouse No.1, Spanning Bradford Slough, from Bradford Island, Bonneville, Multnomah County, OR

6. FORSYTHIA WALK AFTER WIDENING Photocopy of photograph, date unknown ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

6. FORSYTHIA WALK AFTER WIDENING Photocopy of photograph, date unknown National Park Service, National Capital Region files - Dumbarton Oaks Park, Thirty-second & R Streets Northwest, Washington, District of Columbia, DC

22. Photographer unknown, 1956 AERIAL VIEW, LOOKING SOUTHSOUTHEAST, BUILDING 20 ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

22. Photographer unknown, 1956 AERIAL VIEW, LOOKING SOUTH-SOUTHEAST, BUILDING 20 AT LEFT. DARK AREAS ARE LANDSCAPED. - U. S. Veterans Administration Medical Center, 2100 Ridgecrest Southeast, Albuquerque, Bernalillo County, NM

Laissez-Faire : Fully Asymmetric Backscatter Communication

PubMed Central

Hu, Pan; Zhang, Pengyu; Ganesan, Deepak

2016-01-01

Backscatter provides dual-benefits of energy harvesting and low-power communication, making it attractive to a broad class of wireless sensors. But the design of a protocol that enables extremely power-efficient radios for harvesting-based sensors as well as high-rate data transfer for data-rich sensors presents a conundrum. In this paper, we present a new fully asymmetric backscatter communication protocol where nodes blindly transmit data as and when they sense. This model enables fully flexible node designs, from extraordinarily power-efficient backscatter radios that consume barely a few micro-watts to high-throughput radios that can stream at hundreds of Kbps while consuming a paltry tens of micro-watts. The challenge, however, lies in decoding concurrent streams at the reader, which we achieve using a novel combination of time-domain separation of interleaved signal edges, and phase-domain separation of colliding transmissions. We provide an implementation of our protocol, LF-Backscatter, and show that it can achieve an order of magnitude or more improvement in throughput, latency and power over state-of-art alternatives. PMID:28286885

Failure probability under parameter uncertainty.

PubMed

Gerrard, R; Tsanakas, A

2011-05-01

In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.

Making an unknown unknown a known unknown: Missing data in longitudinal neuroimaging studies.

PubMed

Matta, Tyler H; Flournoy, John C; Byrne, Michelle L

2017-10-28

The analysis of longitudinal neuroimaging data within the massively univariate framework provides the opportunity to study empirical questions about neurodevelopment. Missing outcome data are an all-to-common feature of any longitudinal study, a feature that, if handled improperly, can reduce statistical power and lead to biased parameter estimates. The goal of this paper is to provide conceptual clarity of the issues and non-issues that arise from analyzing incomplete data in longitudinal studies with particular focus on neuroimaging data. This paper begins with a review of the hierarchy of missing data mechanisms and their relationship to likelihood-based methods, a review that is necessary not just for likelihood-based methods, but also for multiple-imputation methods. Next, the paper provides a series of simulation studies with designs common in longitudinal neuroimaging studies to help illustrate missing data concepts regardless of interpretation. Finally, two applied examples are used to demonstrate the sensitivity of inferences under different missing data assumptions and how this may change the substantive interpretation. The paper concludes with a set of guidelines for analyzing incomplete longitudinal data that can improve the validity of research findings in developmental neuroimaging research. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Novel prescribed performance neural control of a flexible air-breathing hypersonic vehicle with unknown initial errors.

PubMed

Bu, Xiangwei; Wu, Xiaoyan; Zhu, Fujing; Huang, Jiaqi; Ma, Zhen; Zhang, Rui

2015-11-01

A novel prescribed performance neural controller with unknown initial errors is addressed for the longitudinal dynamic model of a flexible air-breathing hypersonic vehicle (FAHV) subject to parametric uncertainties. Different from traditional prescribed performance control (PPC) requiring that the initial errors have to be known accurately, this paper investigates the tracking control without accurate initial errors via exploiting a new performance function. A combined neural back-stepping and minimal learning parameter (MLP) technology is employed for exploring a prescribed performance controller that provides robust tracking of velocity and altitude reference trajectories. The highlight is that the transient performance of velocity and altitude tracking errors is satisfactory and the computational load of neural approximation is low. Finally, numerical simulation results from a nonlinear FAHV model demonstrate the efficacy of the proposed strategy. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Fully-kinetic Ion Simulation of Global Electrostatic Turbulent Transport in C-2U

NASA Astrophysics Data System (ADS)

Fulton, Daniel; Lau, Calvin; Bao, Jian; Lin, Zhihong; Tajima, Toshiki; TAE Team

2017-10-01

Understanding the nature of particle and energy transport in field-reversed configuration (FRC) plasmas is a crucial step towards an FRC-based fusion reactor. The C-2U device at Tri Alpha Energy (TAE) achieved macroscopically stable plasmas and electron energy confinement time which scaled favorably with electron temperature. This success led to experimental and theoretical investigation of turbulence in C-2U, including gyrokinetic ion simulations with the Gyrokinetic Toroidal Code (GTC). A primary objective of TAE's new C-2W device is to explore transport scaling in an extended parameter regime. In concert with the C-2W experimental campaign, numerical efforts have also been extended in A New Code (ANC) to use fully-kinetic (FK) ions and a Vlasov-Poisson field solver. Global FK ion simulations are presented. Future code development is also discussed.

38. Historic photograph, photographer unknown, c. 1944. VIEW SHOWING BURROS ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

38. Historic photograph, photographer unknown, c. 1944. VIEW SHOWING BURROS (OR MULES) CROSSING BRIDGE, LOOKING NORTHEAST. - Verde River Sheep Bridge, Spanning Verde River (Tonto National Forest), Cave Creek, Maricopa County, AZ

81. photographer unknown 11 June 1937 WORKMEN ON TURBINE BLADES ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

81. photographer unknown 11 June 1937 WORKMEN ON TURBINE BLADES BEFORE LOWERING INTO DRAFT TUBE LINER. - Bonneville Project, Powerhouse No.1, Spanning Bradford Slough, from Bradford Island, Bonneville, Multnomah County, OR

4. VIEW OF BORING MILL IN OPERATION, operator unknown (note ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. VIEW OF BORING MILL IN OPERATION, operator unknown (note console in background). - Juniata Shops, Erecting Shop & Machine Shop, East of Fourth Avenue, between Fourth & Fifth Streets, Altoona, Blair County, PA

3. VIEW OF BORING MILL IN OPERATION, operator unknown (note ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. VIEW OF BORING MILL IN OPERATION, operator unknown (note console in background). - Juniata Shops, Erecting Shop & Machine Shop, East of Fourth Avenue, between Fourth & Fifth Streets, Altoona, Blair County, PA

7. Photographic copy of photograph (date unknown, original print in ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

7. Photographic copy of photograph (date unknown, original print in the possession of the Wisconsin Veterans Museums). LAKE IN FOREGROUND, COTTAGES IN BACK. - Wisconsin Home for Veterans, King, Waupaca County, WI

Reactive Transport Modeling of Induced Calcite Precipitation Reaction Fronts in Porous Media Using A Parallel, Fully Coupled, Fully Implicit Approach

NASA Astrophysics Data System (ADS)

Guo, L.; Huang, H.; Gaston, D.; Redden, G. D.; Fox, D. T.; Fujita, Y.

2010-12-01

Inducing mineral precipitation in the subsurface is one potential strategy for immobilizing trace metal and radionuclide contaminants. Generating mineral precipitates in situ can be achieved by manipulating chemical conditions, typically through injection or in situ generation of reactants. How these reactants transport, mix and react within the medium controls the spatial distribution and composition of the resulting mineral phases. Multiple processes, including fluid flow, dispersive/diffusive transport of reactants, biogeochemical reactions and changes in porosity-permeability, are tightly coupled over a number of scales. Numerical modeling can be used to investigate the nonlinear coupling effects of these processes which are quite challenging to explore experimentally. Many subsurface reactive transport simulators employ a de-coupled or operator-splitting approach where transport equations and batch chemistry reactions are solved sequentially. However, such an approach has limited applicability for biogeochemical systems with fast kinetics and strong coupling between chemical reactions and medium properties. A massively parallel, fully coupled, fully implicit Reactive Transport simulator (referred to as “RAT”) based on a parallel multi-physics object-oriented simulation framework (MOOSE) has been developed at the Idaho National Laboratory. Within this simulator, systems of transport and reaction equations can be solved simultaneously in a fully coupled, fully implicit manner using the Jacobian Free Newton-Krylov (JFNK) method with additional advanced computing capabilities such as (1) physics-based preconditioning for solution convergence acceleration, (2) massively parallel computing and scalability, and (3) adaptive mesh refinements for 2D and 3D structured and unstructured mesh. The simulator was first tested against analytical solutions, then applied to simulating induced calcium carbonate mineral precipitation in 1D columns and 2D flow cells as analogs

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.

Eosinophilic pustular folliculitis: a sterile folliculitis of unknown cause?

PubMed

Brenner, S; Wolf, R; Ophir, J

1994-08-01

Eosinophilic pustular folliculitis (EPF) was initially defined as a sterile folliculitis of unknown cause. Because attempts to demonstrate bacterial organisms have been unsuccessful, and antibiotic therapy is usually ineffective, a bacterial infection is not considered a plausible causative factor for this disease. Our purpose was to describe five patients with the clinical and histologic characteristics of EPF and to report the results of bacterial cultures. Biopsy specimens were examined and pustules were cultured. In three of the five patients, Pseudomonas infection of the hair follicle was the cause of the disease as proven by repeated cultures and the response to specific therapy. Three patients had a systemic disorder known to cause immunologic alteration: AIDS in one and a myeloproliferative disorder in two. Although EPF was initially defined as a sterile folliculitis of unknown origin, three of our patients had an identifiable and treatable cause. We believe that these cases warrant the diagnosis of EPF.

Quadrotor Control in the Presence of Unknown Mass Properties

NASA Astrophysics Data System (ADS)

Duivenvoorden, Rikky Ricardo Petrus Rufino

Quadrotor UAVs are popular due to their mechanical simplicity, as well as their capability to hover and vertically take-off and land. As applications diversify, quadrotors are increasingly required to operate under unknown mass properties, for example as a multirole sensor platform or for package delivery operations. The work presented here consists of the derivation of a generalized quadrotor dynamic model without the typical simplifying assumptions on the first and second moments of mass. The maximum payload capacity of a quadrotor in hover, and the observability of the unknown mass properties are discussed. A brief introduction of L1 adaptive control is provided, and three different L 1 adaptive controllers were designed for the Parrot AR.Drone quadrotor. Their tracking and disturbance rejection performance was compared to the baseline nonlinear controller in experiments. Finally, the results of the combination of L1 adaptive control with iterative learning control are presented, showing high performance trajectory tracking under uncertainty.

19. Photocopy of photograph Photographer unknown, ca. 1895 GENERAL VIEW ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

19. Photocopy of photograph Photographer unknown, ca. 1895 GENERAL VIEW OF KEY WEST WITH FORT TAYLOR IN THE BACKGROUND LOOKING WEST SOUTHWEST - Fort Taylor, Whitehead Spit Vicinity, Key West, Monroe County, FL

15. Photocopy of photograph (original in WACC), photographer unknown, c. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

15. Photocopy of photograph (original in WACC), photographer unknown, c. 1917 BEN ERICKSON IN WWI UNIFORM STANDING IN FRONT OF SOUTH LIVING ROOM WINDOW (ADOBE WALLS) - Faraway Ranch, Willcox, Cochise County, AZ

71. photographer unknown 9 September 1935 DOWNSTREAM SIDE OF POWERHOUSE ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

71. photographer unknown 9 September 1935 DOWNSTREAM SIDE OF POWERHOUSE SUBSTRUCTURE, SHOWING FISHWAY AND DRAFT TUBE OUTLETS. - Bonneville Project, Powerhouse No.1, Spanning Bradford Slough, from Bradford Island, Bonneville, Multnomah County, OR

41. Upstream end of emergency spillway excavation. Photographer unknown, 1929. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

41. Upstream end of emergency spillway excavation. Photographer unknown, 1929. Source: Arizona Department of Water Resources (ADWR). - Waddell Dam, On Agua Fria River, 35 miles northwest of Phoenix, Phoenix, Maricopa County, AZ

35. Photocopy of drawing (from Library of Congress) Artist unknown ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

35. Photocopy of drawing (from Library of Congress) Artist unknown 1891 SOUTH FRONT FROM THE SOUTHWEST - Patent Office Building, Bounded by Seventh, Ninth, F & G Streets, Northwest, Washington, District of Columbia, DC

3. Photocopy of photograph (location of original unknown) Mary Mather, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

3. Photocopy of photograph (location of original unknown) Mary Mather, photographer, ca. 1920 PARTIAL EAST ELEVATION, OBSCURED BY FOLIAGE - Bagatelle Plantation, East River Road (moved to Iberville Parish), Donaldsonville, Ascension Parish, LA

51. BOILER ROOM. SMALL BOILER ON LEFT OF UNKNOWN MANUFACTURE, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

51. BOILER ROOM. SMALL BOILER ON LEFT OF UNKNOWN MANUFACTURE, WITH INDUCTION MOTORS. HARTLEY BOILER, MONTGOMERY, ALABAMA, ON RIGHT. - Prattville Manufacturing Company, Number One, 242 South Court Street, Prattville, Autauga County, AL

Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

NASA Astrophysics Data System (ADS)

Seko, Atsuto; Hayashi, Hiroyuki; Kashima, Hisashi; Tanaka, Isao

2018-01-01

Chemically relevant compositions (CRCs) and atomic arrangements of inorganic compounds have been collected as inorganic crystal structure databases. Machine learning is a unique approach to search for currently unknown CRCs from vast candidates. Herein we propose matrix- and tensor-based recommender system approaches to predict currently unknown CRCs from database entries of CRCs. Firstly, the performance of the recommender system approaches to discover currently unknown CRCs is examined. A Tucker decomposition recommender system shows the best discovery rate of CRCs as the majority of the top 100 recommended ternary and quaternary compositions correspond to CRCs. Secondly, systematic density functional theory (DFT) calculations are performed to investigate the phase stability of the recommended compositions. The phase stability of the 27 compositions reveals that 23 currently unknown compounds are newly found to be stable. These results indicate that the recommender system has great potential to accelerate the discovery of new compounds.

Fully automated urban traffic system

NASA Technical Reports Server (NTRS)

Dobrotin, B. M.; Hansen, G. R.; Peng, T. K. C.; Rennels, D. A.

1977-01-01

The replacement of the driver with an automatic system which could perform the functions of guiding and routing a vehicle with a human's capability of responding to changing traffic demands was discussed. The problem was divided into four technological areas; guidance, routing, computing, and communications. It was determined that the latter three areas being developed independent of any need for fully automated urban traffic. A guidance system that would meet system requirements was not being developed but was technically feasible.

Identification of Unknown Contaminants in Water Samples from ISS Employing Liquid Chromatography/Mass Spectrometry/Mass Spectrometry

NASA Technical Reports Server (NTRS)

Rutz, Jeffrey A.; Schultz, John R.

2008-01-01

Mass Spectrometry/Mass Spectrometry (MS/MS) is a powerful technique for identifying unknown organic compounds. For non-volatile or thermally unstable unknowns dissolved in liquids, liquid chromatography/mass spectrometry/mass spectrometry (LC/MS/MS) is often the variety of MS/MS used for the identification. One type of LC/MS/MS that is rapidly becoming popular is time-of-flight (TOF) mass spectrometry. This technique is now in use at the Johnson Space Center for identification of unknown nonvolatile organics in water samples from the space program. An example of the successful identification of one unknown is reviewed in detail in this paper. The advantages of time-of-flight instrumentation are demonstrated through this example as well as the strategy employed in using time-of-flight data to identify unknowns.

A new method for parameter estimation in nonlinear dynamical equations

NASA Astrophysics Data System (ADS)

Wang, Liu; He, Wen-Ping; Liao, Le-Jian; Wan, Shi-Quan; He, Tao

2015-01-01

Parameter estimation is an important scientific problem in various fields such as chaos control, chaos synchronization and other mathematical models. In this paper, a new method for parameter estimation in nonlinear dynamical equations is proposed based on evolutionary modelling (EM). This will be achieved by utilizing the following characteristics of EM which includes self-organizing, adaptive and self-learning features which are inspired by biological natural selection, and mutation and genetic inheritance. The performance of the new method is demonstrated by using various numerical tests on the classic chaos model—Lorenz equation (Lorenz 1963). The results indicate that the new method can be used for fast and effective parameter estimation irrespective of whether partial parameters or all parameters are unknown in the Lorenz equation. Moreover, the new method has a good convergence rate. Noises are inevitable in observational data. The influence of observational noises on the performance of the presented method has been investigated. The results indicate that the strong noises, such as signal noise ratio (SNR) of 10 dB, have a larger influence on parameter estimation than the relatively weak noises. However, it is found that the precision of the parameter estimation remains acceptable for the relatively weak noises, e.g. SNR is 20 or 30 dB. It indicates that the presented method also has some anti-noise performance.

Heterojunction fully depleted SOI-TFET with oxide/source overlap

NASA Astrophysics Data System (ADS)

Chander, Sweta; Bhowmick, B.; Baishya, S.

2015-10-01

In this work, a hetero-junction fully depleted (FD) Silicon-on-Insulator (SOI) Tunnel Field Effect Transistor (TFET) nanostructure with oxide overlap on the Germanium-source region is proposed. Investigations using Synopsys Technology Computer Aided Design (TCAD) simulation tools reveal that the simple oxide overlap on the Germanium-source region increases the tunneling area as well as the tunneling current without degrading the band-to-band tunneling (BTBT) and improves the device performance. More importantly, the improvement is independent of gate overlap. Simulation study shows improvement in ON current, subthreshold swing (SS), OFF current, ION/IOFF ration, threshold voltage and transconductance. The proposed device with hafnium oxide (HfO2)/Aluminium Nitride (AlN) stack dielectric material offers an average subthreshold swing of 22 mV/decade and high ION/IOFF ratio (∼1010) at VDS = 0.4 V. Compared to conventional TFET, the Miller capacitance of the device shows the enhanced performance. The impact of the drain voltage variation on different parameters such as threshold voltage, subthreshold swing, transconductance, and ION/IOFF ration are also found to be satisfactory. From fabrication point of view also it is easy to utilize the existing CMOS process flows to fabricate the proposed device.

47. Photocopy of postcard (Pentran file), photographer unknown. Hampton's Old ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

47. Photocopy of postcard (Pentran file), photographer unknown. Hampton's Old Point Comfort electric trolley in 1921. - Newport News & Old Point Railway & Electric Company, Trolley Barn & Administration Building, 3400 Victoria Boulevard, Hampton, Hampton, VA

21 CFR 866.1645 - Fully automated short-term incubation cycle antimicrobial susceptibility system.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Fully automated short-term incubation cycle... Diagnostic Devices § 866.1645 Fully automated short-term incubation cycle antimicrobial susceptibility system. (a) Identification. A fully automated short-term incubation cycle antimicrobial susceptibility system...

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.

Analysis of Fully Polarimetric Laboratory Measurements Performed with the WISDOM Radar

NASA Astrophysics Data System (ADS)

Plettemeier, D.; Ciarletti, V.; Cais, P.; Benedix, W.-S.; Zhang, H.; Hamran, S.-E.; Clifford, S.

2012-04-01

algorithms were applied to reduce the interference from radiation coupling and cross-talk between transmitting and receiving antenna. The analysis of the laboratory measurement will show features of the fully polarimetric radar system and quantify most of the important performance parameters. Synthetic aperture processing is implemented to increase the azimuth resolution of radar. The three dimensional reconstruction of the positioning of an arrangement of discrete objects will be shown.

44. Reinforcement construction to Pleasant Dam. Photographer unknown, 1935. Source: ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

44. Reinforcement construction to Pleasant Dam. Photographer unknown, 1935. Source: Huber Collection, University of California, Berkeley, Water Resources Library. - Waddell Dam, On Agua Fria River, 35 miles northwest of Phoenix, Phoenix, Maricopa County, AZ

47. Photocopy of plans. Draftsman unknown, 1916 ADDITION TO CAR ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

47. Photocopy of plans. Draftsman unknown, 1916 ADDITION TO CAR BARN. LONGITUDINAL AND CROSS SECTIONS. VIEWS TO SOUTH AND WEST. - Milwaukee Light, Heat & Traction Company, 8336 West Lapham Street, West Allis, Milwaukee County, WI

Kurtosis parameter K of arbitrary electromagnetic beams propagating through non-Kolmogorov turbulence

NASA Astrophysics Data System (ADS)

Xu, Yonggen; Dan, Youquan; Yu, Jiayi; Cai, Yangjian

2017-10-01

General analytical formulae for the kurtosis parameters K (K parameters) of the arbitrary electromagnetic (AE) beams propagating through non-Kolmogorov turbulence are derived, and according to the unified theory of polarization and coherence, the effect of degree of polarization (DOP) of an electromagnetic beam on the K parameter is studied. The analytical formulae can be given by the second-order moments and fourth-order moments of the Wigner distribution function for AE beams at source plane, the two turbulence quantities relating to the spatial power spectrum, and the propagation distance. Our results can also be extended to the arbitrary beams and the arbitrary spatial power spectra of Kolmogorov turbulence or non-Kolmogorov turbulence. Taking the stochastic electromagnetic Gaussian Schell-model (SEGSM) beam as an example, the numerical examples indicate that the K parameters of a SEGSM beam in non-Kolmogorov turbulence depend on propagation distance, the beam parameters and turbulence parameters. The K parameter of a SEGM beam is more sensitive to effect of turbulence with smaller inner scale and generalized exponent parameter. A non-polarized light has the strongest ability of resisting turbulence (ART), however, a fully polarized SEGSM beam has the poorest ART.

The fully actuated traffic control problem solved by global optimization and complementarity

NASA Astrophysics Data System (ADS)

Ribeiro, Isabel M.; de Lurdes de Oliveira Simões, Maria

2016-02-01

Global optimization and complementarity are used to determine the signal timing for fully actuated traffic control, regarding effective green and red times on each cycle. The average values of these parameters can be used to estimate the control delay of vehicles. In this article, a two-phase queuing system for a signalized intersection is outlined, based on the principle of minimization of the total waiting time for the vehicles. The underlying model results in a linear program with linear complementarity constraints, solved by a sequential complementarity algorithm. Departure rates of vehicles during green and yellow periods were treated as deterministic, while arrival rates of vehicles were assumed to follow a Poisson distribution. Several traffic scenarios were created and solved. The numerical results reveal that it is possible to use global optimization and complementarity over a reasonable number of cycles and determine with efficiency effective green and red times for a signalized intersection.

Hybrid fully nonlinear BEM-LBM numerical wave tank with applications in naval hydrodynamics

NASA Astrophysics Data System (ADS)

Mivehchi, Amin; Grilli, Stephan T.; Dahl, Jason M.; O'Reilly, Chris M.; Harris, Jeffrey C.; Kuznetsov, Konstantin; Janssen, Christian F.

2017-11-01

simulation of the complex dynamics response of ships in waves is typically modeled by nonlinear potential flow theory, usually solved with a higher order BEM. In some cases, the viscous/turbulent effects around a structure and in its wake need to be accurately modeled to capture the salient physics of the problem. Here, we present a fully 3D model based on a hybrid perturbation method. In this method, the velocity and pressure are decomposed as the sum of an inviscid flow and viscous perturbation. The inviscid part is solved over the whole domain using a BEM based on cubic spline element. These inviscid results are then used to force a near-field perturbation solution on a smaller domain size, which is solved with a NS model based on LBM-LES, and implemented on GPUs. The BEM solution for large grids is greatly accelerated by using a parallelized FMM, which is efficiently implemented on large and small clusters, yielding an almost linear scaling with the number of unknowns. A new representation of corners and edges is implemented, which improves the global accuracy of the BEM solver, particularly for moving boundaries. We present model results and the recent improvements of the BEM, alongside results of the hybrid model, for applications to problems. Office of Naval Research Grants N000141310687 and N000141612970.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis.

PubMed

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-08-08

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis

PubMed Central

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-01-01

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases. PMID:28786947

Biochemical acclimation, stomatal limitation and precipitation patterns underlie decreases in photosynthetic stimulation of Soybean (Glycine max) at elevated [CO2] and temperatures under fully open air field conditions

USDA-ARS?s Scientific Manuscript database

The net effect of elevated [CO2] and temperature on photosynthetic acclimation and plant productivity is poorly resolved. We assessed the effects of canopy warming and fully open air [CO2] enrichment on 1) the acclimation of two biochemical parameters that frequently limit photosynthesis (A), the ma...

Identification of "Known Unknowns" Utilizing Accurate Mass Data and ChemSpider

NASA Astrophysics Data System (ADS)

Little, James L.; Williams, Antony J.; Pshenichnov, Alexey; Tkachenko, Valery

2012-01-01

In many cases, an unknown to an investigator is actually known in the chemical literature, a reference database, or an internet resource. We refer to these types of compounds as "known unknowns." ChemSpider is a very valuable internet database of known compounds useful in the identification of these types of compounds in commercial, environmental, forensic, and natural product samples. The database contains over 26 million entries from hundreds of data sources and is provided as a free resource to the community. Accurate mass mass spectrometry data is used to query the database by either elemental composition or a monoisotopic mass. Searching by elemental composition is the preferred approach. However, it is often difficult to determine a unique elemental composition for compounds with molecular weights greater than 600 Da. In these cases, searching by the monoisotopic mass is advantageous. In either case, the search results are refined by sorting the number of references associated with each compound in descending order. This raises the most useful candidates to the top of the list for further evaluation. These approaches were shown to be successful in identifying "known unknowns" noted in our laboratory and for compounds of interest to others.

A multiwave range test for obstacle reconstructions with unknown physical properties

NASA Astrophysics Data System (ADS)

Potthast, Roland; Schulz, Jochen

2007-08-01

We develop a new multiwave version of the range test for shape reconstruction in inverse scattering theory. The range test [R. Potthast, et al., A `range test' for determining scatterers with unknown physical properties, Inverse Problems 19(3) (2003) 533-547] has originally been proposed to obtain knowledge about an unknown scatterer when the far field pattern for only one plane wave is given. Here, we extend the method to the case of multiple waves and show that the full shape of the unknown scatterer can be reconstructed. We further will clarify the relation between the range test methods, the potential method [A. Kirsch, R. Kress, On an integral equation of the first kind in inverse acoustic scattering, in: Inverse Problems (Oberwolfach, 1986), Internationale Schriftenreihe zur Numerischen Mathematik, vol. 77, Birkhauser, Basel, 1986, pp. 93-102] and the singular sources method [R. Potthast, Point sources and multipoles in inverse scattering theory, Habilitation Thesis, Gottingen, 1999]. In particular, we propose a new version of the Kirsch-Kress method using the range test and a new approach to the singular sources method based on the range test and potential method. Numerical examples of reconstructions for all four methods are provided.

Infectious causes of fever of unknown origin.

PubMed

McGregor, Alastair C; Moore, David A

2015-06-01

The causes of fever of unknown origin (FUO) are changing because advances in clinical practice and diagnostics have facilitated the identification of some infections. A variety of bacterial infections can cause FUO, and these can be divided into those that are easy to identify using culture and those that require serological or molecular tests for identification. A number of viral, parasitic and fungal infections can also cause prolonged fever. This article summarises the clinical features and diagnostic strategy of these infections. © Royal College of Physicians 2015. All rights reserved.

A novel algorithm for fast grasping of unknown objects using C-shape configuration

NASA Astrophysics Data System (ADS)

Lei, Qujiang; Chen, Guangming; Meijer, Jonathan; Wisse, Martijn

2018-02-01

Increasing grasping efficiency is very important for the robots to grasp unknown objects especially subjected to unfamiliar environments. To achieve this, a new algorithm is proposed based on the C-shape configuration. Specifically, the geometric model of the used under-actuated gripper is approximated as a C-shape. To obtain an appropriate graspable position, this C-shape configuration is applied to fit geometric model of an unknown object. The geometric model of unknown object is constructed by using a single-view partial point cloud. To examine the algorithm using simulations, a comparison of the commonly used motion planners is made. The motion planner with the highest number of solved runs, lowest computing time and the shortest path length is chosen to execute grasps found by this grasping algorithm. The simulation results demonstrate that excellent grasping efficiency is achieved by adopting our algorithm. To validate this algorithm, experiment tests are carried out using a UR5 robot arm and an under-actuated gripper. The experimental results show that steady grasping actions are obtained. Hence, this research provides a novel algorithm for fast grasping of unknown objects.

Fully Printed Memristors from Cu-SiO2 Core-Shell Nanowire Composites

NASA Astrophysics Data System (ADS)

Catenacci, Matthew J.; Flowers, Patrick F.; Cao, Changyong; Andrews, Joseph B.; Franklin, Aaron D.; Wiley, Benjamin J.

2017-07-01

This article describes a fully printed memory in which a composite of Cu-SiO2 nanowires dispersed in ethylcellulose acts as a resistive switch between printed Cu and Au electrodes. A 16-cell crossbar array of these memristors was printed with an aerosol jet. The memristors exhibited moderate operating voltages (˜3 V), no degradation over 104 switching cycles, write speeds of 3 μs, and extrapolated retention times of 10 years. The low operating voltage enabled the programming of a fully printed 4-bit memristor array with an Arduino. The excellent performance of these fully printed memristors could help enable the creation of fully printed RFID tags and sensors with integrated data storage.

A 40 GHz fully integrated circuit with a vector network analyzer and a coplanar-line-based detection area for circulating tumor cell analysis using 65 nm CMOS technology

NASA Astrophysics Data System (ADS)

Nakanishi, Taiki; Matsunaga, Maya; Kobayashi, Atsuki; Nakazato, Kazuo; Niitsu, Kiichi

2018-03-01

A 40-GHz fully integrated CMOS-based circuit for circulating tumor cells (CTC) analysis, consisting of an on-chip vector network analyzer (VNA) and a highly sensitive coplanar-line-based detection area is presented in this paper. In this work, we introduce a fully integrated architecture that eliminates unwanted parasitic effects. The proposed analyzer was designed using 65 nm CMOS technology, and SPICE and MWS simulations were used to validate its operation. The simulation confirmed that the proposed circuit can measure S-parameter shifts resulting from the addition of various types of tumor cells to the detection area, the data of which are provided in a previous study: the |S 21| values for HepG2, A549, and HEC-1-A cells are -0.683, -0.580, and -0.623 dB, respectively. Additionally, the measurement demonstrated an S-parameters reduction of -25.7% when a silicone resin was put on the circuit. Hence, the proposed system is expected to contribute to cancer diagnosis.

Recurrence formulas for fully exponentially correlated four-body wave functions

NASA Astrophysics Data System (ADS)

Harris, Frank E.

2009-03-01

Formulas are presented for the recursive generation of four-body integrals in which the integrand consists of arbitrary integer powers (≥-1) of all the interparticle distances rij , multiplied by an exponential containing an arbitrary linear combination of all the rij . These integrals are generalizations of those encountered using Hylleraas basis functions and include all that are needed to make energy computations on the Li atom and other four-body systems with a fully exponentially correlated Slater-type basis of arbitrary quantum numbers. The only quantities needed to start the recursion are the basic four-body integral first evaluated by Fromm and Hill plus some easily evaluated three-body “boundary” integrals. The computational labor in constructing integral sets for practical computations is less than when the integrals are generated using explicit formulas obtained by differentiating the basic integral with respect to its parameters. Computations are facilitated by using a symbolic algebra program (MAPLE) to compute array index pointers and present syntactically correct FORTRAN source code as output; in this way it is possible to obtain error-free high-speed evaluations with minimal effort. The work can be checked by verifying sum rules the integrals must satisfy.

25. Photocopy of photograph (Source unknown, c. 19231925) EXTERIOR, CLOSEUP ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

25. Photocopy of photograph (Source unknown, c. 1923-1925) EXTERIOR, CLOSE-UP OF SOUTH FRONT OF MISSION AFTER RESTORATION, C. 1923-1925 - Mission San Francisco Solano de Sonoma, First & Spain Streets, Sonoma, Sonoma County, CA

43. Photocopy of photograph (Pentran file), photographer and date unknown ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

43. Photocopy of photograph (Pentran file), photographer and date unknown (circa 1960). VIEW WEST, EAST SIDE ADMINISTRATION BUILDING - Newport News & Old Point Railway & Electric Company, Trolley Barn & Administration Building, 3400 Victoria Boulevard, Hampton, Hampton, VA

View of an unknown industrial building in the Dolphin Jute ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

View of an unknown industrial building in the Dolphin Jute Mill Complex, looking southwest. Note Garret Mountain at upper left and historic Dexter-Lambert smokestack. - Dolphin Manufacturing Company, Spruce & Barbour Streets, Paterson, Passaic County, NJ

Unknown Gases: Student-Designed Experiments in the Introductory Laboratory.

ERIC Educational Resources Information Center

Hanson, John; Hoyt, Tim

2002-01-01

Introductory students design and carry-out experimental procedures to determine the identity of three unknown gases from a list of eight possibilities: air, nitrogen, oxygen, argon, carbon dioxide, helium, methane, and hydrogen. Students are excited and motivated by the opportunity to come up with their own experimental approach to solving a…

Stochastic parameter estimation in nonlinear time-delayed vibratory systems with distributed delay

NASA Astrophysics Data System (ADS)

Torkamani, Shahab; Butcher, Eric A.

2013-07-01

The stochastic estimation of parameters and states in linear and nonlinear time-delayed vibratory systems with distributed delay is explored. The approach consists of first employing a continuous time approximation to approximate the delayed integro-differential system with a large set of ordinary differential equations having stochastic excitations. Then the problem of state and parameter estimation in the resulting stochastic ordinary differential system is represented as an optimal filtering problem using a state augmentation technique. By adapting the extended Kalman-Bucy filter to the augmented filtering problem, the unknown parameters of the time-delayed system are estimated from noise-corrupted, possibly incomplete measurements of the states. Similarly, the upper bound of the distributed delay can also be estimated by the proposed technique. As an illustrative example to a practical problem in vibrations, the parameter, delay upper bound, and state estimation from noise-corrupted measurements in a distributed force model widely used for modeling machine tool vibrations in the turning operation is investigated.

Spread-Spectrum Carrier Estimation With Unknown Doppler Shift

NASA Technical Reports Server (NTRS)

DeLeon, Phillip L.; Scaife, Bradley J.

1998-01-01

We present a method for the frequency estimation of a BPSK modulated, spread-spectrum carrier with unknown Doppler shift. The approach relies on a classic periodogram in conjunction with a spectral matched filter. Simulation results indicate accurate carrier estimation with processing gains near 40. A DSP-based prototype has been implemented for real-time carrier estimation for use in New Mexico State University's proposal for NASA's Demand Assignment Multiple Access service.

Persistent Surveillance of Transient Events with Unknown Statistics

DTIC Science & Technology

2016-12-18

different bird species by a documentary maker is shown in Fig. 1. Additional examples of scenarios following this setting include robots patrolling the...persistent monitoring application in which a documentary maker would like to monitor three different species of birds appearing in three discrete, species...specific locations. Bird sightings at each location follow a stochastic process with a rate that is initially unknown to the documentary maker and must

Magnetic resonance appearance of monoclonal gammopathies of unknown significance and multiple myeloma. The GRI Study Group.

PubMed

Bellaïche, L; Laredo, J D; Lioté, F; Koeger, A C; Hamze, B; Ziza, J M; Pertuiset, E; Bardin, T; Tubiana, J M

1997-11-01

A prospective multicenter study. To evaluate the use of magnetic resonance imaging, in the differentiation between monoclonal gammopathies of unknown significance and multiple myeloma. Although multiple myeloma has been studied extensively with magnetic resonance imaging, to the authors' knowledge, no study has evaluated the clinical interest of magnetic resonance imaging in the differentiation between monoclonal gammopathies of unknown significance and multiple myeloma. The magnetic resonance examinations of the thoracolumbar spine in 24 patients with newly diagnosed monoclonal gammopathies of unknown significance were compared with those performed in 44 patients with newly diagnosed nontreated multiple myeloma. All findings on magnetic resonance examination performed in patients with monoclonal gammopathies of unknown significance were normal, whereas findings on 38 (86%) of the 44 magnetic resonance examinations performed in patients with multiple myeloma were abnormal. Magnetic resonance imaging can be considered as an additional diagnostic tool in differentiating between monoclonal gammopathies of unknown significance and multiple myeloma, which may be helpful when routine criteria are not sufficient. An abnormal finding on magnetic resonance examination in a patient with monoclonal gammopathies of unknown significance should suggest the diagnosis of multiple myeloma after other causes of marrow signal abnormalities are excluded. Magnetic resonance imaging also may be proposed in the long-term follow-up of monoclonal gammopathies of unknown significance when a new biologic or clinical event suggests the diagnosis of malignant monoclonal gammopathy.

Impacts of Different Types of Measurements on Estimating Unsaturatedflow Parameters

NASA Astrophysics Data System (ADS)

Shi, L.

2015-12-01

This study evaluates the value of different types of measurements for estimating soil hydraulic parameters. A numerical method based on ensemble Kalman filter (EnKF) is presented to solely or jointly assimilate point-scale soil water head data, point-scale soil water content data, surface soil water content data and groundwater level data. This study investigates the performance of EnKF under different types of data, the potential worth contained in these data, and the factors that may affect estimation accuracy. Results show that for all types of data, smaller measurements errors lead to faster convergence to the true values. Higher accuracy measurements are required to improve the parameter estimation if a large number of unknown parameters need to be identified simultaneously. The data worth implied by the surface soil water content data and groundwater level data is prone to corruption by a deviated initial guess. Surface soil moisture data are capable of identifying soil hydraulic parameters for the top layers, but exert less or no influence on deeper layers especially when estimating multiple parameters simultaneously. Groundwater level is one type of valuable information to infer the soil hydraulic parameters. However, based on the approach used in this study, the estimates from groundwater level data may suffer severe degradation if a large number of parameters must be identified. Combined use of two or more types of data is helpful to improve the parameter estimation.

43. Photocopy of photograph, photographer unknown, ca January 1929 (original ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

43. Photocopy of photograph, photographer unknown, ca January 1929 (original print located at Arizona Department of Transportation, Phoenix AZ). COMPLETED BRIDGE. - Navajo Bridge, Spanning Colorado River at U.S. Highway 89 Alternate, Page, Coconino County, AZ

356. Delineator Unknown March 1946 STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

356. Delineator Unknown March 1946 STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; SAN FRANCISCO - OAKLAND BAY BRIDGE; GENERAL DATA; PLAT III - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

6. Photographic copy of photograph (date unknown, original print in ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

6. Photographic copy of photograph (date unknown, original print in the possession of the Wisconsin Veterans Museums). COTTAGES, INCLUDING 'J.P. McPHERSON POST NO. 27 CAFE GENEVA'. - Wisconsin Home for Veterans, King, Waupaca County, WI

Soft Ultrathin Electronics Innervated Adaptive Fully Soft Robots.

PubMed

Wang, Chengjun; Sim, Kyoseung; Chen, Jin; Kim, Hojin; Rao, Zhoulyu; Li, Yuhang; Chen, Weiqiu; Song, Jizhou; Verduzco, Rafael; Yu, Cunjiang

2018-03-01

Soft robots outperform the conventional hard robots on significantly enhanced safety, adaptability, and complex motions. The development of fully soft robots, especially fully from smart soft materials to mimic soft animals, is still nascent. In addition, to date, existing soft robots cannot adapt themselves to the surrounding environment, i.e., sensing and adaptive motion or response, like animals. Here, compliant ultrathin sensing and actuating electronics innervated fully soft robots that can sense the environment and perform soft bodied crawling adaptively, mimicking an inchworm, are reported. The soft robots are constructed with actuators of open-mesh shaped ultrathin deformable heaters, sensors of single-crystal Si optoelectronic photodetectors, and thermally responsive artificial muscle of carbon-black-doped liquid-crystal elastomer (LCE-CB) nanocomposite. The results demonstrate that adaptive crawling locomotion can be realized through the conjugation of sensing and actuation, where the sensors sense the environment and actuators respond correspondingly to control the locomotion autonomously through regulating the deformation of LCE-CB bimorphs and the locomotion of the robots. The strategy of innervating soft sensing and actuating electronics with artificial muscles paves the way for the development of smart autonomous soft robots. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fully developed turbulence in slugs of pipe flows

NASA Astrophysics Data System (ADS)

Cerbus, Rory; Liu, Chien-Chia; Sakakibara, Jun; Gioia, Gustavo; Chakraborty, Pinaki

2015-11-01

Despite over a century of research, transition to turbulence in pipe flows remains a mystery. In theory the flow remains laminar for arbitrarily large Reynolds number, Re. In practice, however, the flow transitions to turbulence at a finite Re whose value depends on the disturbance, natural or artificial, in the experimental setup. The flow remains in the transition state for a range of Re ~ 0 (1000) ; for larger Re the flow becomes fully developed. The transition state for Re > 3000 consists of axially segregated regions of laminar and turbulent patches. These turbulent patches, known as slugs, grow as they move downstream. Their lengths span anywhere between a few pipe diameters to the whole length of the pipe. Here we report Stereo Particle Image Velocimetry measurements in the cross-section of the slugs. Notwithstanding the continuous growth of the slugs, we find that the mean velocity and stress profiles in the slugs are indistinguishable from that of statistically-stationary fully-developed turbulent flows. Our results are independent of the length of the slugs. We contrast our results with the well-known work of Wygnanski & Champagne (1973), whose measurements, we argue, are insufficient to draw a clear conclusion regarding fully developed turbulence in slugs.

Bayesian parameter estimation in spectral quantitative photoacoustic tomography

NASA Astrophysics Data System (ADS)

Pulkkinen, Aki; Cox, Ben T.; Arridge, Simon R.; Kaipio, Jari P.; Tarvainen, Tanja

2016-03-01

Photoacoustic tomography (PAT) is an imaging technique combining strong contrast of optical imaging to high spatial resolution of ultrasound imaging. These strengths are achieved via photoacoustic effect, where a spatial absorption of light pulse is converted into a measurable propagating ultrasound wave. The method is seen as a potential tool for small animal imaging, pre-clinical investigations, study of blood vessels and vasculature, as well as for cancer imaging. The goal in PAT is to form an image of the absorbed optical energy density field via acoustic inverse problem approaches from the measured ultrasound data. Quantitative PAT (QPAT) proceeds from these images and forms quantitative estimates of the optical properties of the target. This optical inverse problem of QPAT is illposed. To alleviate the issue, spectral QPAT (SQPAT) utilizes PAT data formed at multiple optical wavelengths simultaneously with optical parameter models of tissue to form quantitative estimates of the parameters of interest. In this work, the inverse problem of SQPAT is investigated. Light propagation is modelled using the diffusion equation. Optical absorption is described with chromophore concentration weighted sum of known chromophore absorption spectra. Scattering is described by Mie scattering theory with an exponential power law. In the inverse problem, the spatially varying unknown parameters of interest are the chromophore concentrations, the Mie scattering parameters (power law factor and the exponent), and Gruneisen parameter. The inverse problem is approached with a Bayesian method. It is numerically demonstrated, that estimation of all parameters of interest is possible with the approach.

MUSIC-type imaging of small perfectly conducting cracks with an unknown frequency

NASA Astrophysics Data System (ADS)

Park, Won-Kwang

2015-09-01

MUltiple SIgnal Classification (MUSIC) is a famous non-iterative detection algorithm in inverse scattering problems. However, when the applied frequency is unknown, inaccurate locations are identified via MUSIC. This fact has been confirmed through numerical simulations. However, the reason behind this phenomenon has not been investigated theoretically. Motivated by this fact, we identify the structure of MUSIC-type imaging functionals with unknown frequency, by establishing a relationship with Bessel functions of order zero of the first kind. Through this, we can explain why inaccurate results appear.

Automatic estimation of elasticity parameters in breast tissue

NASA Astrophysics Data System (ADS)

Skerl, Katrin; Cochran, Sandy; Evans, Andrew

2014-03-01

Shear wave elastography (SWE), a novel ultrasound imaging technique, can provide unique information about cancerous tissue. To estimate elasticity parameters, a region of interest (ROI) is manually positioned over the stiffest part of the shear wave image (SWI). The aim of this work is to estimate the elasticity parameters i.e. mean elasticity, maximal elasticity and standard deviation, fully automatically. Ultrasonic SWI of a breast elastography phantom and breast tissue in vivo were acquired using the Aixplorer system (SuperSonic Imagine, Aix-en-Provence, France). First, the SWI within the ultrasonic B-mode image was detected using MATLAB then the elasticity values were extracted. The ROI was automatically positioned over the stiffest part of the SWI and the elasticity parameters were calculated. Finally all values were saved in a spreadsheet which also contains the patient's study ID. This spreadsheet is easily available for physicians and clinical staff for further evaluation and so increase efficiency. Therewith the efficiency is increased. This algorithm simplifies the handling, especially for the performance and evaluation of clinical trials. The SWE processing method allows physicians easy access to the elasticity parameters of the examinations from their own and other institutions. This reduces clinical time and effort and simplifies evaluation of data in clinical trials. Furthermore, reproducibility will be improved.

A Fully Implantable, NFC Enabled, Continuous Interstitial Glucose Monitor

PubMed Central

Anabtawi, Nijad; Freeman, Sabrina; Ferzli, Rony

2017-01-01

This work presents an integrated system-on-chip (SoC) that forms the core of a long-term, fully implantable, battery assisted, passive continuous glucose monitor. It integrates an amperometric glucose sensor interface, a near field communication (NFC) wireless front-end and a fully digital switched mode power management unit for supply regulation and on board battery charging. It uses 13.56 MHz (ISM) band to harvest energy and backscatter data to an NFC reader. System was implemented in 14nm CMOS technology and validated with post layout simulations. PMID:28702512

A Fully Implantable, NFC Enabled, Continuous Interstitial Glucose Monitor.

PubMed

Anabtawi, Nijad; Freeman, Sabrina; Ferzli, Rony

2016-02-01

This work presents an integrated system-on-chip (SoC) that forms the core of a long-term, fully implantable, battery assisted, passive continuous glucose monitor. It integrates an amperometric glucose sensor interface, a near field communication (NFC) wireless front-end and a fully digital switched mode power management unit for supply regulation and on board battery charging. It uses 13.56 MHz (ISM) band to harvest energy and backscatter data to an NFC reader. System was implemented in 14nm CMOS technology and validated with post layout simulations.

Fully differential cross sections for Li2+-impact ionization of Li(2s) and Li(2p)

NASA Astrophysics Data System (ADS)

Ghorbani, Omid; Ghanbari-Adivi, Ebrahim; Fabian Ciappina, Marcelo

2018-05-01

A semiclassical impact parameter version of the continuum distorted wave-Eikonal initial state theory is developed to study the differential ionization of Li atoms in collisions with Li2+ ions. Both post and prior forms of the transition amplitude are considered. The fully differential cross sections are calculated for the lithium targets in their ground and their first excited states and for the projectile ions at 16 MeV impact energy. The role of the inter-nuclear interaction as well as the significance of the post-prior discrepancy in the ejected electron spectra are investigated. The obtained results for ejection of the electron into the azimuthal plane are compared with the recent measurements and with their corresponding values obtained using a fully quantum mechanical version of the theory. In most of the cases, the consistency of the present approach with the experimental and the quantum theoretical data is reasonable. However, for 2p-state ionization, in the cases where no experimental data exist, there is a considerable difference between the two theoretical approaches. This difference is questionable and further experiments are needed to judge which theory makes a more accurate description of the collision dynamics.

System parameter identification from projection of inverse analysis

NASA Astrophysics Data System (ADS)

Liu, K.; Law, S. S.; Zhu, X. Q.

2017-05-01

The output of a system due to a change of its parameters is often approximated with the sensitivity matrix from the first order Taylor series. The system output can be measured in practice, but the perturbation in the system parameters is usually not available. Inverse sensitivity analysis can be adopted to estimate the unknown system parameter perturbation from the difference between the observation output data and corresponding analytical output data calculated from the original system model. The inverse sensitivity analysis is re-visited in this paper with improvements based on the Principal Component Analysis on the analytical data calculated from the known system model. The identification equation is projected into a subspace of principal components of the system output, and the sensitivity of the inverse analysis is improved with an iterative model updating procedure. The proposed method is numerical validated with a planar truss structure and dynamic experiments with a seven-storey planar steel frame. Results show that it is robust to measurement noise, and the location and extent of stiffness perturbation can be identified with better accuracy compared with the conventional response sensitivity-based method.

12. Photocopy of lithograph (source unknown) The Armor Lithograph Company, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

12. Photocopy of lithograph (source unknown) The Armor Lithograph Company, Ltd., Pittsburgh, Pennsylvania, ca. 1888 COURTHOUSE AND JAIL, FROM THE WEST - Allegheny County Courthouse & Jail, 436 Grant Street (Courthouse), 420 Ross Street (Jail), Pittsburgh, Allegheny County, PA

11. Photocopy of photograph (from St. Paul's Church) Photographer unknown ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

11. Photocopy of photograph (from St. Paul's Church) Photographer unknown 1886 'EPISCOPAL CHURCH, CORNER OF 1ST AND J ST. BENICIA' WEST AND SOUTH SIDES - St. Paul's Episcopal Church, 120 East J Street, Benicia, Solano County, CA

[Focal myositis: An unknown disease].

PubMed

Gallay, L; Streichenberger, N; Benveniste, O; Allenbach, Y

2017-10-01

Focal myositis are inflammatory muscle diseases of unknown origin. At the opposite from the other idiopathic inflammatory myopathies, they are restricted to a single muscle or to a muscle group. They are not associated with extramuscular manifestations, and they have a good prognosis without any treatment. They are characterized by a localized swelling affecting mostly lower limbs. The pseudo-tumor can be painful, but is not associated with a muscle weakness. Creatine kinase level is normal. Muscle MRI shows an inflammation restricted to a muscle or a muscle group. Muscle biopsy and pathological analysis remain necessary for the diagnosis, showing inflammatory infiltrates composed by macrophages and lymphocytes without any specific distribution within the muscle. Focal overexpression of HLA-1 by the muscle fibers is frequently observed. The muscle biopsy permits to rule out differential diagnosis such a malignancy (sarcoma). Spontaneous remission occurs within weeks or months after the first symptoms, relapse is unusual. Copyright © 2017. Published by Elsevier SAS.

Navigation through unknown and dynamic open spaces using topological notions

NASA Astrophysics Data System (ADS)

Miguel-Tomé, Sergio

2018-04-01

Until now, most algorithms used for navigation have had the purpose of directing system towards one point in space. However, humans communicate tasks by specifying spatial relations among elements or places. In addition, the environments in which humans develop their activities are extremely dynamic. The only option that allows for successful navigation in dynamic and unknown environments is making real-time decisions. Therefore, robots capable of collaborating closely with human beings must be able to make decisions based on the local information registered by the sensors and interpret and express spatial relations. Furthermore, when one person is asked to perform a task in an environment, this task is communicated given a category of goals so the person does not need to be supervised. Thus, two problems appear when one wants to create multifunctional robots: how to navigate in dynamic and unknown environments using spatial relations and how to accomplish this without supervision. In this article, a new architecture to address the two cited problems is presented, called the topological qualitative navigation architecture. In previous works, a qualitative heuristic called the heuristic of topological qualitative semantics (HTQS) has been developed to establish and identify spatial relations. However, that heuristic only allows for establishing one spatial relation with a specific object. In contrast, navigation requires a temporal sequence of goals with different objects. The new architecture attains continuous generation of goals and resolves them using HTQS. Thus, the new architecture achieves autonomous navigation in dynamic or unknown open environments.

Bearing fault diagnosis under unknown variable speed via gear noise cancellation and rotational order sideband identification

NASA Astrophysics Data System (ADS)

Wang, Tianyang; Liang, Ming; Li, Jianyong; Cheng, Weidong; Li, Chuan

2015-10-01

The interfering vibration signals of a gearbox often represent a challenging issue in rolling bearing fault detection and diagnosis, particularly under unknown variable rotational speed conditions. Though some methods have been proposed to remove the gearbox interfering signals based on their discrete frequency nature, such methods may not work well under unknown variable speed conditions. As such, we propose a new approach to address this issue. The new approach consists of three main steps: (a) adaptive gear interference removal, (b) fault characteristic order (FCO) based fault detection, and (c) rotational-order-sideband (ROS) based fault type identification. For gear interference removal, an enhanced adaptive noise cancellation (ANC) algorithm has been developed in this study. The new ANC algorithm does not require an additional accelerometer to provide reference input. Instead, the reference signal is adaptively constructed from signal maxima and instantaneous dominant meshing multiple (IDMM) trend. Key ANC parameters such as filter length and step size have also been tailored to suit the variable speed conditions, The main advantage of using ROS for fault type diagnosis is that it is insusceptible to confusion caused by the co-existence of bearing and gear rotational frequency peaks in the identification of the bearing fault characteristic frequency in the FCO sub-order region. The effectiveness of the proposed method has been demonstrated using both simulation and experimental data. Our experimental study also indicates that the proposed method is applicable regardless whether the bearing and gear rotational speeds are proportional to each other or not.

2. Photocopy of photograph (location of original unknown) Mary Mather, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

2. Photocopy of photograph (location of original unknown) Mary Mather, photographer, ca. 1920 GENERAL VIEW OF WEST (LEFT) AND SOUTH (RIGHT) FACADES, TAKEN FROM LEVEE - Bagatelle Plantation, East River Road (moved to Iberville Parish), Donaldsonville, Ascension Parish, LA

A linked simulation-optimization model for solving the unknown groundwater pollution source identification problems.

PubMed

Ayvaz, M Tamer

2010-09-20

This study proposes a linked simulation-optimization model for solving the unknown groundwater pollution source identification problems. In the proposed model, MODFLOW and MT3DMS packages are used to simulate the flow and transport processes in the groundwater system. These models are then integrated with an optimization model which is based on the heuristic harmony search (HS) algorithm. In the proposed simulation-optimization model, the locations and release histories of the pollution sources are treated as the explicit decision variables and determined through the optimization model. Also, an implicit solution procedure is proposed to determine the optimum number of pollution sources which is an advantage of this model. The performance of the proposed model is evaluated on two hypothetical examples for simple and complex aquifer geometries, measurement error conditions, and different HS solution parameter sets. Identified results indicated that the proposed simulation-optimization model is an effective way and may be used to solve the inverse pollution source identification problems. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Preparation and Identification of Benzoic Acids and Benzamides: An Organic "Unknown" Lab

NASA Astrophysics Data System (ADS)

Taber, Douglass F.; Nelson, Jade D.; Northrop, John P.

1999-06-01

The reaction of an unknown substituted benzene derivative (illustrated by toluene) with oxalyl chloride and aluminum chloride gives the acid chloride. Hydrolysis of the acid chloride gives the acid, and reaction of the acid with concentrated aqueous ammonia gives the benzamide.

Neurological autoantibodies in drug-resistant epilepsy of unknown cause.

PubMed

Tecellioglu, Mehmet; Kamisli, Ozden; Kamisli, Suat; Yucel, Fatma Ebru; Ozcan, Cemal

2018-03-09

Autoimmune epilepsy is a rarely diagnosed condition. Recognition of the underlying autoimmune condition is important, as these patients can be resistant to antiepileptic drugs. To determine the autoimmune and oncological antibodies in adult drug-resistant epilepsy of unknown cause and identify the clinical, radiological, and EEG findings associated with these antibodies according to data in the literature. Eighty-two patients with drug-resistant epilepsy of unknown cause were prospectively identified. Clinical features were recorded. The levels of anti-voltage-gated potassium channel complex (anti-VGKCc), anti-thyroid peroxidase (anti-TPO), anti-nuclear antibody (ANA), anti-glutamic acid decarboxylase (anti-GAD), anti-phospholipid IgG and IgM, anti-cardiolipin IgG and IgM, and onconeural antibodies were determined. Serum antibody positivity suggesting the potential role of autoimmunity in the aetiology was present in 17 patients with resistant epilepsy (22.0%). Multiple antibodies were found in two patients (2.6%). One of these patients (1.3%) had anti-VGKCc and ANA, whereas another (1.3%) had anti-VGKCc and anti-TPO. A single antibody was present in 15 patients (19.5%). Of the 77 patients finally included in the study, 4 had anti-TPO (5.2%), 1 had anti-GAD (1.3%), 4 had anti-VGKCc (5.2%) 8 had ANA (10.3%), and 2 had onconeural antibodies (2.6%) (1 patient had anti-Yo and 1 had anti-MA2/TA). The other antibodies investigated were not detected. EEG abnormality (focal), focal seizure incidence, and frequent seizures were more common in antibody-positive patients. Autoimmune factors may be aetiologically relevant in patients with drug-resistant epilepsy of unknown cause, especially if focal seizures are present together with focal EEG abnormality and frequent seizures.

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 1. Theory

USGS Publications Warehouse

Cooley, Richard L.

1982-01-01

Prior information on the parameters of a groundwater flow model can be used to improve parameter estimates obtained from nonlinear regression solution of a modeling problem. Two scales of prior information can be available: (1) prior information having known reliability (that is, bias and random error structure) and (2) prior information consisting of best available estimates of unknown reliability. A regression method that incorporates the second scale of prior information assumes the prior information to be fixed for any particular analysis to produce improved, although biased, parameter estimates. Approximate optimization of two auxiliary parameters of the formulation is used to help minimize the bias, which is almost always much smaller than that resulting from standard ridge regression. It is shown that if both scales of prior information are available, then a combined regression analysis may be made.

Numerical simulation of cavitation and atomization using a fully compressible three-phase model

NASA Astrophysics Data System (ADS)

Mithun, Murali-Girija; Koukouvinis, Phoevos; Gavaises, Manolis

2018-06-01

The aim of this paper is to present a fully compressible three-phase (liquid, vapor, and air) model and its application to the simulation of in-nozzle cavitation effects on liquid atomization. The model employs a combination of the homogeneous equilibrium barotropic cavitation model with an implicit sharp interface capturing volume of fluid (VOF) approximation. The numerical predictions are validated against the experimental results obtained for injection of water into the air from a step nozzle, which is designed to produce asymmetric cavitation along its two sides. Simulations are performed for three injection pressures, corresponding to three different cavitation regimes, referred to as cavitation inception, developing cavitation, and hydraulic flip. Model validation is achieved by qualitative comparison of the cavitation, spray pattern, and spray cone angles. The flow turbulence in this study is resolved using the large-eddy simulation approach. The simulation results indicate that the major parameters that influence the primary atomization are cavitation, liquid turbulence, and, to a smaller extent, the Rayleigh-Taylor and Kelvin-Helmholtz aerodynamic instabilities developing on the liquid-air interface. Moreover, the simulations performed indicate that periodic entrainment of air into the nozzle occurs at intermediate cavitation numbers, corresponding to developing cavitation (as opposed to incipient and fully developed cavitation regimes); this transient effect causes a periodic shedding of the cavitation and air clouds and contributes to improved primary atomization. Finally, the cone angle of the spray is found to increase with increased injection pressure but drops drastically when hydraulic flip occurs, in agreement with the relevant experiments.