Biological Parametric Mapping WITH Robust AND Non-Parametric Statistics
Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.
2011-01-01
Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, regions of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrices. Recently, biological parametric mapping has extended the widely popular statistical parametric mapping approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and non-parametric regression in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provide a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities. PMID:21569856
Biological parametric mapping with robust and non-parametric statistics.
Yang, Xue; Beason-Held, Lori; Resnick, Susan M; Landman, Bennett A
2011-07-15
Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, regions of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrices. Recently, biological parametric mapping has extended the widely popular statistical parametric mapping approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and non-parametric regression in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provide a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities. Copyright © 2011 Elsevier Inc. All rights reserved.
Improvement of Statistical Decisions under Parametric Uncertainty
NASA Astrophysics Data System (ADS)
Nechval, Nicholas A.; Nechval, Konstantin N.; Purgailis, Maris; Berzins, Gundars; Rozevskis, Uldis
2011-10-01
A large number of problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made in the presence of uncertainty. Decision-making under uncertainty is a central problem in statistical inference, and has been formally studied in virtually all approaches to inference. The aim of the present paper is to show how the invariant embedding technique, the idea of which belongs to the authors, may be employed in the particular case of finding the improved statistical decisions under parametric uncertainty. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, an invariant embedding technique is independent of the choice of priors. It allows one to eliminate unknown parameters from the problem and to find the best invariant decision rule, which has smaller risk than any of the well-known decision rules. To illustrate the proposed technique, application examples are given.
Approximately Integrable Linear Statistical Models in Non-Parametric Estimation
1990-08-01
OTIC I EL COPY Lfl 0n Cf) NAPPROXIMATELY INTEGRABLE LINEAR STATISTICAL MODELS IN NON- PARAMETRIC ESTIMATION by B. Ya. Levit University of Maryland...Integrable Linear Statistical Models in Non- Parametric Estimation B. Ya. Levit Sumnmary / The notion of approximately integrable linear statistical models...models related to the study of the "next" order optimality in non- parametric estimation . It appears consistent to keep the exposition at present at the
A Comparison of Parametric versus Nonparametric Statistics.
ERIC Educational Resources Information Center
Royeen, Charlotte Brasic
In order to examine the possible effects of violation of assumptions using parametric procedures, this study is an exploratory investigation into the use of parametric versus nonparametric procedures using a multiple case study design. The case study investigation guidelines outlined by Yin served as the methodology. The following univariate…
Parametric vs. non-parametric statistics of low resolution electromagnetic tomography (LORETA).
Thatcher, R W; North, D; Biver, C
2005-01-01
This study compared the relative statistical sensitivity of non-parametric and parametric statistics of 3-dimensional current sources as estimated by the EEG inverse solution Low Resolution Electromagnetic Tomography (LORETA). One would expect approximately 5% false positives (classification of a normal as abnormal) at the P < .025 level of probability (two tailed test) and approximately 1% false positives at the P < .005 level. EEG digital samples (2 second intervals sampled 128 Hz, 1 to 2 minutes eyes closed) from 43 normal adult subjects were imported into the Key Institute's LORETA program. We then used the Key Institute's cross-spectrum and the Key Institute's LORETA output files (*.lor) as the 2,394 gray matter pixel representation of 3-dimensional currents at different frequencies. The mean and standard deviation *.lor files were computed for each of the 2,394 gray matter pixels for each of the 43 subjects. Tests of Gaussianity and different transforms were computed in order to best approximate a normal distribution for each frequency and gray matter pixel. The relative sensitivity of parametric vs. non-parametric statistics were compared using a "leave-one-out" cross validation method in which individual normal subjects were withdrawn and then statistically classified as being either normal or abnormal based on the remaining subjects. Log10 transforms approximated Gaussian distribution in the range of 95% to 99% accuracy. Parametric Z score tests at P < .05 cross-validation demonstrated an average misclassification rate of approximately 4.25%, and range over the 2,394 gray matter pixels was 27.66% to 0.11%. At P < .01 parametric Z score cross-validation false positives were 0.26% and ranged from 6.65% to 0% false positives. The non-parametric Key Institute's t-max statistic at P < .05 had an average misclassification error rate of 7.64% and ranged from 43.37% to 0.04% false positives. The nonparametric t-max at P < .01 had an average misclassification rate
Application of parametric statistical weights in CAD imaging systems
NASA Astrophysics Data System (ADS)
Galperin, Michael
2005-04-01
PURPOSE: To propose a method for Parametric Statistical Weights (PSW) estimations and analyze its statistical impact in Computer-Aided Diagnosis Imaging Systems based on a Relative Similarity (CADIRS) classification approach. MATERIALS AND METHODS: A Multifactor statistical method was developed and applied for Parametric Statistical Weights calculations in CADIRS. The implemented PSW method was used for statistical estimations of PSW impact when applied to a clinically validated breast ultrasound digital database of 332 patients' cases with biopsy proven findings. The method is based on the assumption that each parameter used in Relative Similarity (RS) classifier contributes to the deviation of the diagnostic prediction proportionally to the normalized value of its coefficient of multiple regression. The calculated by CADIRS Relative Similarity values with and without PSW were statistically estimated, compared and analyzed (on subset of cases) using classic Receiver Operator Characteristic (ROC) analysis methods. RESULTS: When CADIRS classification scheme was augmented with PSW the Relative Similarity the calculated values were 2-5% higher in average. Numeric estimations of PSW allowed decomposition of statistical significance for each component (factor) and its impact on similarity to the diagnostic results (biopsy proven). CONCLUSION: Parametric Statistical Weights in Computer-Aided Diagnosis Imaging Systems based on a Relative Similarity classification approach can be successfully applied in an effort to enhance overall classification (including scoring) outcomes. For the analyzed cohort of 332 cases the application of PSW increased Relative Similarity to the retrieved templates with known findings by 2-5% in average.
Two-parametric fractional statistics models for anyons
NASA Astrophysics Data System (ADS)
Rovenchak, Andrij
2014-08-01
In the paper, two-parametric models of fractional statistics are proposed in order to determine the functional form of the distribution function of free anyons. From the expressions of the second and third virial coefficients, an approximate correspondence is shown to hold for three models, namely, the nonadditive Polychronakos statistics and both the incomplete and the nonadditive modifications of the Haldane-Wu statistics. The difference occurs only in the fourth virial coefficient leading to a small correction in the equation of state. For the two generalizations of the Haldane-Wu statistics, the solutions for the statistics parameters g, q exist in the whole domain of the anyonic parameter α ∈ [0; 1], unlike the nonadditive Polychronakos statistics. It is suggested that the search for the expression of the anyonic distribution function should be made within some modifications of the Haldane-Wu statistics.
Quantum statistics of optical parametric processes with squeezed reservoirs
NASA Astrophysics Data System (ADS)
Peřina, Jan; Křepelka, Jaromír
2013-11-01
Quantum statistics including joint photon-number and integrated-intensity probability distributions are derived in time evolution of general optical parametric process involving processes of frequency conversion, parametric amplification and subharmonic generation taking into account losses and noise described by squeezed reservoirs. Using these tools quantum entanglement of modes is considered and the other nonclassical properties of the process under discussion are demonstrated by means of conditional probability distributions and their Fano factors, difference-number probability distributions, quantum oscillations, squeezing of vacuum fluctuations and negative values of the joint and difference wave probability quasidistributions. Nonclassical properties are illustrated for spontaneous process as well as stimulated process by means of chaotic light and squeezed vacuum field. Multimode processes are investigated in the spirit of the Mandel-Rice photocount formula.
Reading a research article part II: parametric and nonparametric statistics.
Oliver, Dana; Mahon, Suzanne M
2005-04-01
Researchers often try to use a randomization technique in an attempt to reduce bias and ensure that treatment and control groups are as similar as possible. This article has provided an overview of how researchers might use parametric and nonparametric statistics when analyzing data and looking for differences between groups. Researchers must consider the types of data and choose the tests that are appropriate for the variable types to draw appropriate conclusions. The next article in this series will address comparison of more than two groups and repeated measures and other design issues.
One-dimensional statistical parametric mapping in Python.
Pataky, Todd C
2012-01-01
Statistical parametric mapping (SPM) is a topological methodology for detecting field changes in smooth n-dimensional continua. Many classes of biomechanical data are smooth and contained within discrete bounds and as such are well suited to SPM analyses. The current paper accompanies release of 'SPM1D', a free and open-source Python package for conducting SPM analyses on a set of registered 1D curves. Three example applications are presented: (i) kinematics, (ii) ground reaction forces and (iii) contact pressure distribution in probabilistic finite element modelling. In addition to offering a high-level interface to a variety of common statistical tests like t tests, regression and ANOVA, SPM1D also emphasises fundamental concepts of SPM theory through stand-alone example scripts. Source code and documentation are available at: www.tpataky.net/spm1d/.
Aversi-Ferreira, Roqueline A. G. M. F.; Nishijo, Hisao; Aversi-Ferreira, Tales Alexandre
2015-01-01
Various statistical methods have been published for comparative anatomy. However, few studies compared parametric and nonparametric statistical methods. Moreover, some previous studies using statistical method for comparative anatomy (SMCA) proposed the formula for comparison of groups of anatomical structures (multiple structures) among different species. The present paper described the usage of SMCA and compared the results by SMCA with those by parametric test (t-test) and nonparametric analyses (cladistics) of anatomical data. In conclusion, the SMCA can offer a more exact and precise way to compare single and multiple anatomical structures across different species, which requires analyses of nominal features in comparative anatomy. PMID:26413553
Aversi-Ferreira, Roqueline A G M F; Nishijo, Hisao; Aversi-Ferreira, Tales Alexandre
2015-01-01
Various statistical methods have been published for comparative anatomy. However, few studies compared parametric and nonparametric statistical methods. Moreover, some previous studies using statistical method for comparative anatomy (SMCA) proposed the formula for comparison of groups of anatomical structures (multiple structures) among different species. The present paper described the usage of SMCA and compared the results by SMCA with those by parametric test (t-test) and nonparametric analyses (cladistics) of anatomical data. In conclusion, the SMCA can offer a more exact and precise way to compare single and multiple anatomical structures across different species, which requires analyses of nominal features in comparative anatomy.
A Parametric Cumulative Sum Statistic for Person Fit
ERIC Educational Resources Information Center
Armstrong, Ronald D.; Shi, Min
2009-01-01
This article develops a new cumulative sum (CUSUM) statistic to detect aberrant item response behavior. Shifts in behavior are modeled with quadratic functions and a series of likelihood ratio tests are used to detect aberrancy. The new CUSUM statistic is compared against another CUSUM approach as well as traditional person-fit statistics. A…
A Parametric Cumulative Sum Statistic for Person Fit
ERIC Educational Resources Information Center
Armstrong, Ronald D.; Shi, Min
2009-01-01
This article develops a new cumulative sum (CUSUM) statistic to detect aberrant item response behavior. Shifts in behavior are modeled with quadratic functions and a series of likelihood ratio tests are used to detect aberrancy. The new CUSUM statistic is compared against another CUSUM approach as well as traditional person-fit statistics. A…
Statistical properties of light from optical parametric oscillators
Vyas, Reeta; Singh, Surendra
2009-12-15
Coherence properties of light beams generated by optical parametric oscillators (OPOs) are discussed in the region of threshold. Analytic expressions, that are valid throughout the threshold region, for experimentally measurable quantities such as the mean and variance of photon number fluctuations, squeezing of field quadratures, and photon counting distributions are derived. These expressions describe non-Gaussian fluctuations of light in the region of threshold and reproduce Gaussian fluctuations below and above threshold, thus providing a bridge between below and above threshold regimes of operation. They are used to study the transformation of fluctuation properties of light as the OPOs make a transition from below to above threshold. The results for the OPOs are compared to those for the single-mode and two-mode lasers and their similarities and differences are discussed.
Simulation Validation Using a Non-Parametric Statistical Method
2006-12-01
information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and...paradox of sorts: the simulation is supposed to alleviate the need to conduct costly live tests, but the live tests are the best indication that the...event population is statistically similar to the hypothetical (or computed) simulation population. Like the simulation output populations, the live
Thermal hydraulic limits analysis using statistical propagation of parametric uncertainties
Chiang, K. Y.; Hu, L. W.; Forget, B.
2012-07-01
The MIT Research Reactor (MITR) is evaluating the conversion from highly enriched uranium (HEU) to low enrichment uranium (LEU) fuel. In addition to the fuel element re-design, a reactor power upgraded from 6 MW to 7 MW is proposed in order to maintain the same reactor performance of the HEU core. Previous approach in analyzing the impact of engineering uncertainties on thermal hydraulic limits via the use of engineering hot channel factors (EHCFs) was unable to explicitly quantify the uncertainty and confidence level in reactor parameters. The objective of this study is to develop a methodology for MITR thermal hydraulic limits analysis by statistically combining engineering uncertainties with an aim to eliminate unnecessary conservatism inherent in traditional analyses. This method was employed to analyze the Limiting Safety System Settings (LSSS) for the MITR, which is the avoidance of the onset of nucleate boiling (ONB). Key parameters, such as coolant channel tolerances and heat transfer coefficients, were considered as normal distributions using Oracle Crystal Ball to calculate ONB. The LSSS power is determined with 99.7% confidence level. The LSSS power calculated using this new methodology is 9.1 MW, based on core outlet coolant temperature of 60 deg. C, and primary coolant flow rate of 1800 gpm, compared to 8.3 MW obtained from the analytical method using the EHCFs with same operating conditions. The same methodology was also used to calculate the safety limit (SL) for the MITR, conservatively determined using onset of flow instability (OFI) as the criterion, to verify that adequate safety margin exists between LSSS and SL. The calculated SL is 10.6 MW, which is 1.5 MW higher than LSSS. (authors)
Shiraishi, Hideaki; Stufflebeam, Steven M; Knake, Susanne; Ahlfors, Seppo P; Sudo, Akira; Asahina, Naoko; Egawa, Kiyoshi; Hatanaka, Keisaku; Kohsaka, Shinobu; Saitoh, Shinji; Grant, P Ellen; Dale, Anders M; Halgren, Eric
2005-04-01
Our current purpose is to evaluate the applicability of dynamic statistical parametric mapping, a novel method for localizing epileptiform activity recorded with magnetoencephalography in patients with epilepsy. We report four pediatric patients with focal epilepsies. Magnetoencephalographic data were collected with a 306-channel whole-head helmet-shaped sensor array. We calculated equivalent current dipoles and dynamic statistical parametric mapping movies of the interictal epileptiform discharges that were based in the minimum-L2 norm estimate, minimizing the square sum of the dipole element amplitudes. The dynamic statistical parametric mapping analysis of interictal epileptiform discharges can demonstrate the rapid change and propagation of interical epileptiform discharges. According to these findings, specific epileptogenic lesion-focal cortical dysplasia could be found and patients could be operated on successfully. The presurgical analysis of interictal epileptiform discharges using dynamic statistical parametric mapping seems to be promising in patients with a possible underlying focal cortical dysplasia and might help to guide the placement of invasive electrodes.
Robinson, Mark A; Vanrenterghem, Jos; Pataky, Todd C
2015-02-01
Multi-muscle EMG time-series are highly correlated and time dependent yet traditional statistical analysis of scalars from an EMG time-series fails to account for such dependencies. This paper promotes the use of SPM vector-field analysis for the generalised analysis of EMG time-series. We reanalysed a publicly available dataset of Young versus Adult EMG gait data to contrast scalar and SPM vector-field analysis. Independent scalar analyses of EMG data between 35% and 45% stance phase showed no statistical differences between the Young and Adult groups. SPM vector-field analysis did however identify statistical differences within this time period. As scalar analysis failed to consider the multi-muscle and time dependence of the EMG time-series it exhibited Type II error. SPM vector-field analysis on the other hand accounts for both dependencies whilst tightly controlling for Type I and Type II error making it highly applicable to EMG data analysis. Additionally SPM vector-field analysis is generalizable to linear and non-linear parametric and non-parametric statistical models, allowing its use under constraints that are common to electromyography and kinesiology.
Parametric analysis of the statistical model of the stick-slip process
NASA Astrophysics Data System (ADS)
Lima, Roberta; Sampaio, Rubens
2017-06-01
In this paper it is performed a parametric analysis of the statistical model of the response of a dry-friction oscillator. The oscillator is a spring-mass system which moves over a base with a rough surface. Due to this roughness, the mass is subject to a dry-frictional force modeled as a Coulomb friction. The system is stochastically excited by an imposed bang-bang base motion. The base velocity is modeled by a Poisson process for which a probabilistic model is fully specified. The excitation induces in the system stochastic stick-slip oscillations. The system response is composed by a random sequence alternating stick and slip-modes. With realizations of the system, a statistical model is constructed for this sequence. In this statistical model, the variables of interest of the sequence are modeled as random variables, as for example, the number of time intervals in which stick or slip occur, the instants at which they begin, and their duration. Samples of the system response are computed by integration of the dynamic equation of the system using independent samples of the base motion. Statistics and histograms of the random variables which characterize the stick-slip process are estimated for the generated samples. The objective of the paper is to analyze how these estimated statistics and histograms vary with the system parameters, i.e., to make a parametric analysis of the statistical model of the stick-slip process.
Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation
NASA Astrophysics Data System (ADS)
Karakatsanis, Nicolas A.; Lodge, Martin A.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman
2013-10-01
In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (˜15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study
Dynamic whole body PET parametric imaging: II. Task-oriented statistical estimation
Karakatsanis, Nicolas A.; Lodge, Martin A.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman
2013-01-01
In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15–20cm) of a single bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study
Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation.
Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman
2013-10-21
In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study
Castro, Marcelo P; Pataky, Todd C; Sole, Gisela; Vilas-Boas, Joao Paulo
2015-07-16
Ground reaction force (GRF) data from men and women are commonly pooled for analyses. However, it may not be justifiable to pool sexes on the basis of discrete parameters extracted from continuous GRF gait waveforms because this can miss continuous effects. Forty healthy participants (20 men and 20 women) walked at a cadence of 100 steps per minute across two force plates, recording GRFs. Two statistical methods were used to test the null hypothesis of no mean GRF differences between sexes: (i) Statistical Parametric Mapping-using the entire three-component GRF waveform; and (ii) traditional approach-using the first and second vertical GRF peaks. Statistical Parametric Mapping results suggested large sex differences, which post-hoc analyses suggested were due predominantly to higher anterior-posterior and vertical GRFs in early stance in women compared to men. Statistically significant differences were observed for the first GRF peak and similar values for the second GRF peak. These contrasting results emphasise that different parts of the waveform have different signal strengths and thus that one may use the traditional approach to choose arbitrary metrics and make arbitrary conclusions. We suggest that researchers and clinicians consider both the entire gait waveforms and sex-specificity when analysing GRF data. Copyright © 2015 Elsevier Ltd. All rights reserved.
Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis
Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.
2006-01-01
In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709
Statistical structuring theory in parametrically excitable dynamical systems with a Gaussian pump
NASA Astrophysics Data System (ADS)
Klyatskin, V. I.; Koshel, K. V.
2016-03-01
Based on the idea of the statistical topography, we analyze the problem of emergence of stochastic structure formation in linear and quasilinear problems described by first-order partial differential equations. The appearance of a parametric excitation on the background of a Gaussian pump is a specific feature of these problems. We obtain equations for the probability density of the solutions of these equations, whence it follows that the stochastic structure formation emerges with probability one, i.e., for almost every realization of the random parameters of the medium.
Tanaka, Naoaki; Cole, Andrew J.; von Pechmann, Deidre; Wakeman, Daniel G.; Hämäläinen, Matti S.; Liu, Hesheng; Madsen, Joseph R.; Bourgeois, Blaise F.; Stufflebeam, Steven M.
2009-01-01
The purpose of this study is to assess the clinical value of spatiotemporal source analysis for analyzing ictal magnetoencephalography (MEG). Ictal MEG and simultaneous scalp EEG was recorded in five patients with medically intractable frontal lobe epilepsy. Dynamic statistical parametric maps (dSPMs) were calculated at the peak of early ictal spikes for the purpose of estimating the spatiotemporal cortical source distribution. DSPM solutions were mapped onto a cortical surface, which was derived from each patient's MRI. Equivalent current dipoles (ECDs) were calculated using a single-dipole model for comparison with dSPMs. In all patients, dSPMs tended to have a localized activation, consistent with the clinically-determined ictal onset zone, whereas most ECDs were considered to be inappropriate sources according to their goodness-of-fit values. Analyzing ictal MEG spikes by using dSPMs may provide useful information in presurgical evaluation of epilepsy. PMID:19394198
Tanaka, Naoaki; Cole, Andrew J; von Pechmann, Deidre; Wakeman, Daniel G; Hämäläinen, Matti S; Liu, Hesheng; Madsen, Joseph R; Bourgeois, Blaise F; Stufflebeam, Steven M
2009-08-01
The purpose of this study is to assess the clinical value of spatiotemporal source analysis for analyzing ictal magnetoencephalography (MEG). Ictal MEG and simultaneous scalp EEG was recorded in five patients with medically intractable frontal lobe epilepsy. Dynamic statistical parametric maps (dSPMs) were calculated at the peak of early ictal spikes for the purpose of estimating the spatiotemporal cortical source distribution. DSPM solutions were mapped onto a cortical surface, which was derived from each patient's MRI. Equivalent current dipoles (ECDs) were calculated using a single-dipole model for comparison with dSPMs. In all patients, dSPMs tended to have a localized activation, consistent with the clinically determined ictal onset zone, whereas most ECDs were considered to be inappropriate sources according to their goodness-of-fit values. Analyzing ictal MEG spikes by using dSPMs may provide useful information in presurgical evaluation of epilepsy.
Packham, B; Barnes, G; Dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D
2016-06-01
Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p < 0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.
Porter, W R; Trager, W F
1977-01-01
The theoretical basis for the direct linear plot [Eisenthal & Cornish-Bowden (1974) Biochem. J. 139, 715-720], a non-parametric statistical method for the analysis of data-fitting the Michaelis-Menten equation, was reinvestigated in order to accommodate additional experimental designs and to provide estimates of precision more directly comparable with those obtained by parametric statistical methods. Methods are given for calculating upper and lower confidence limits for the estimated parameters, for accommodating replicate measurements and for comparing the results of two separate experiments. Factors that influence the proper design of experiments are discussed. PMID:849264
Brown, D Andrew; Lazar, Nicole A; Datta, Gauri S; Jang, Woncheol; McDowell, Jennifer E
2014-01-01
The analysis of functional neuroimaging data often involves the simultaneous testing for activation at thousands of voxels, leading to a massive multiple testing problem. This is true whether the data analyzed are time courses observed at each voxel or a collection of summary statistics such as statistical parametric maps (SPMs). It is known that classical multiplicity corrections become strongly conservative in the presence of a massive number of tests. Some more popular approaches for thresholding imaging data, such as the Benjamini-Hochberg step-up procedure for false discovery rate control, tend to lose precision or power when the assumption of independence of the data does not hold. Bayesian approaches to large scale simultaneous inference also often rely on the assumption of independence. We introduce a spatial dependence structure into a Bayesian testing model for the analysis of SPMs. By using SPMs rather than the voxel time courses, much of the computational burden of Bayesian analysis is mitigated. Increased power is demonstrated by using the dependence model to draw inference on a real dataset collected in a fMRI study of cognitive control. The model also is shown to lead to improved identification of neural activation patterns known to be associated with eye movement tasks. © 2013.
Zoffoli, Luca; Ditroilo, Massimiliano; Federici, Ario; Lucertini, Francesco
2017-09-09
This study used surface electromyography (EMG) to investigate the regions and patterns of activity of the external oblique (EO), erector spinae longissimus (ES), multifidus (MU) and rectus abdominis (RA) muscles during walking (W) and pole walking (PW) performed at different speeds and grades. Eighteen healthy adults undertook W and PW on a motorized treadmill at 60% and 100% of their walk-to-run preferred transition speed at 0% and 7% treadmill grade. The Teager-Kaiser energy operator was employed to improve the muscle activity detection and statistical non-parametric mapping based on paired t-tests was used to highlight statistical differences in the EMG patterns corresponding to different trials. The activation amplitude of all trunk muscles increased at high speed, while no differences were recorded at 7% treadmill grade. ES and MU appeared to support the upper body at the heel-strike during both W and PW, with the latter resulting in elevated recruitment of EO and RA as required to control for the longer stride and the push of the pole. Accordingly, the greater activity of the abdominal muscles and the comparable intervention of the spine extensors supports the use of poles by walkers seeking higher engagement of the lower trunk region. Copyright © 2017 Elsevier Ltd. All rights reserved.
Computational meta-analysis of statistical parametric maps in major depression.
Arnone, Danilo; Job, Dominic; Selvaraj, Sudhakar; Abe, Osamu; Amico, Francesco; Cheng, Yuqi; Colloby, Sean J; O'Brien, John T; Frodl, Thomas; Gotlib, Ian H; Ham, Byung-Joo; Kim, M Justin; Koolschijn, P Cédric M P; Périco, Cintia A-M; Salvadore, Giacomo; Thomas, Alan J; Van Tol, Marie-José; van der Wee, Nic J A; Veltman, Dick J; Wagner, Gerd; McIntosh, Andrew M
2016-04-01
Several neuroimaging meta-analyses have summarized structural brain changes in major depression using coordinate-based methods. These methods might be biased toward brain regions where significant differences were found in the original studies. In this study, a novel voxel-based technique is implemented that estimates and meta-analyses between-group differences in grey matter from individual MRI studies, which are then applied to the study of major depression. A systematic review and meta-analysis of voxel-based morphometry studies were conducted comparing participants with major depression and healthy controls by using statistical parametric maps. Summary effect sizes were computed correcting for multiple comparisons at the voxel level. Publication bias and heterogeneity were also estimated and the excess of heterogeneity was investigated with metaregression analyses. Patients with major depression were characterized by diffuse bilateral grey matter loss in ventrolateral and ventromedial frontal systems extending into temporal gyri compared to healthy controls. Grey matter reduction was also detected in the right parahippocampal and fusiform gyri, hippocampus, and bilateral thalamus. Other areas included parietal lobes and cerebellum. There was no evidence of statistically significant publication bias or heterogeneity. The novel computational meta-analytic approach used in this study identified extensive grey matter loss in key brain regions implicated in emotion generation and regulation. Results are not biased toward the findings of the original studies because they include all available imaging data, irrespective of statistically significant regions, resulting in enhanced detection of additional areas of grey matter loss. © 2016 Wiley Periodicals, Inc.
Klein, Katelyn F; Hu, Jingwen; Reed, Matthew P; Hoff, Carrie N; Rupp, Jonathan D
2015-10-01
Statistical models were developed that predict male and female femur geometry as functions of age, body mass index (BMI), and femur length as part of an effort to develop lower-extremity finite element models with geometries that are parametric with subject characteristics. The process for developing these models involved extracting femur geometry from clinical CT scans of 62 men and 36 women, fitting a template finite element femur mesh to the surface geometry of each patient, and then programmatically determining thickness at each nodal location. Principal component analysis was then performed on the thickness and geometry nodal coordinates, and linear regression models were developed to predict principal component scores as functions of age, BMI, and femur length. The average absolute errors in male and female external surface geometry model predictions were 4.57 and 4.23 mm, and the average absolute errors in male and female thickness model predictions were 1.67 and 1.74 mm. The average error in midshaft cortical bone areas between the predicted geometries and the patient geometries was 4.4%. The average error in cortical bone area between the predicted geometries and a validation set of cadaver femur geometries across 5 shaft locations was 2.9%.
NASA Astrophysics Data System (ADS)
Lee, Jae-Seung; Im, In-Chul; Kang, Su-Man; Goo, Eun-Hoe; Kwak, Byung-Joon
2013-07-01
This study aimed to quantitatively analyze data from diffusion tensor imaging (DTI) using statistical parametric mapping (SPM) in patients with brain disorders and to assess its potential utility for analyzing brain function. DTI was obtained by performing 3.0-T magnetic resonance imaging for patients with Alzheimer's disease (AD) and vascular dementia (VD), and the data were analyzed using Matlab-based SPM software. The two-sample t-test was used for error analysis of the location of the activated pixels. We compared regions of white matter where the fractional anisotropy (FA) values were low and the apparent diffusion coefficients (ADCs) were increased. In the AD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right sub-lobar insula, and right occipital lingual gyrus whereas the ADCs were significantly increased in the right inferior frontal gyrus and right middle frontal gyrus. In the VD group, the FA values were low in the right superior temporal gyrus, right inferior temporal gyrus, right limbic cingulate gyrus, and right sub-lobar caudate tail whereas the ADCs were significantly increased in the left lateral globus pallidus and left medial globus pallidus. In conclusion by using DTI and SPM analysis, we were able to not only determine the structural state of the regions affected by brain disorders but also quantitatively analyze and assess brain function.
Frepoli, Cesare; Oriani, Luca
2006-07-01
In recent years, non-parametric or order statistics methods have been widely used to assess the impact of the uncertainties within Best-Estimate LOCA evaluation models. The bounding of the uncertainties is achieved with a direct Monte Carlo sampling of the uncertainty attributes, with the minimum trial number selected to 'stabilize' the estimation of the critical output values (peak cladding temperature (PCT), local maximum oxidation (LMO), and core-wide oxidation (CWO A non-parametric order statistics uncertainty analysis was recently implemented within the Westinghouse Realistic Large Break LOCA evaluation model, also referred to as 'Automated Statistical Treatment of Uncertainty Method' (ASTRUM). The implementation or interpretation of order statistics in safety analysis is not fully consistent within the industry. This has led to an extensive public debate among regulators and researchers which can be found in the open literature. The USNRC-approved Westinghouse method follows a rigorous implementation of the order statistics theory, which leads to the execution of 124 simulations within a Large Break LOCA analysis. This is a solid approach which guarantees that a bounding value (at 95% probability) of the 95{sup th} percentile for each of the three 10 CFR 50.46 ECCS design acceptance criteria (PCT, LMO and CWO) is obtained. The objective of this paper is to provide additional insights on the ASTRUM statistical approach, with a more in-depth analysis of pros and cons of the order statistics and of the Westinghouse approach in the implementation of this statistical methodology. (authors)
NASA Technical Reports Server (NTRS)
Lua, Yuan J.; Liu, Wing K.; Belytschko, Ted
1992-01-01
A stochastic damage model for predicting the rupture of a brittle multiphase material is developed, based on the microcrack-macrocrack interaction. The model, which incorporates uncertainties in locations, orientations, and numbers of microcracks, characterizes damage by microcracking and fracture by macrocracking. A parametric study is carried out to investigate the change of the stress intensity at the macrocrack tip by the configuration of microcracks. The inherent statistical distribution of the fracture toughness arising from the intrinsic random nature of microcracks is explored using a statistical approach. For this purpose, a computer simulation model is introduced, which incorporates a statistical characterization of geometrical parameters of a random microcrack array.
Statistical properties of squeezed beams of light generated in parametric interactions
NASA Technical Reports Server (NTRS)
Vyas, Reeta
1992-01-01
Fluctuation properties of squeezed photon beams generated in three wave mixing processes such as second harmonic generation, degenerate and nondegenerate parametric oscillations, and homodyne detection are studied in terms of photon sequences recorded by a photodetector.
Zhu, Haitao; Zhu, Jinlong; Bao, Forrest Sheng; Liu, Hongyi; Zhu, Xuchuang; Wu, Ting; Yang, Lu; Zou, Yuanjie; Zhang, Rui; Zheng, Gang
2016-01-01
Frontal lobe epilepsy is a common epileptic disorder and is characterized by recurring seizures that arise in the frontal lobes. The purpose of this study is to identify the epileptogenic regions and other abnormal regions in patients with left frontal lobe epilepsy (LFLE) based on the magnetoencephalogram (MEG), and to understand the effects of clinical variables on brain activities in patients with LFLE. Fifteen patients with LFLE (23.20 ± 8.68 years, 6 female and 9 male) and 16 healthy controls (23.13 ± 7.66 years, 6 female and 10 male) were included in resting-stage MEG examinations. Epileptogenic regions of LFLE patients were confirmed by surgery. Regional brain activations were quantified using statistical parametric mapping (SPM). The correlation between the activations of the abnormal brain regions and the clinical seizure parameters were computed for LFLE patients. Brain activations of LFLE patients were significantly elevated in left superior/middle/inferior frontal gyri, postcentral gyrus, inferior temporal gyrus, insula, parahippocampal gyrus and amygdala, including the epileptogenic regions. Remarkable decreased activations were found mainly in the left parietal gyrus and precuneus. There is a positive correlation between the duration of the epilepsy (in month) and activations of the abnormal regions, while no relation was found between age of seizure onset (year), seizure frequency and the regions of the abnormal activity of the epileptic patients. Our findings suggest that the aberrant brain activities of LFLE patients were not restricted to the epileptogenic zones. Long duration of epilepsy might induce further functional damage in patients with LFLE. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.
Howard, Réka; Carriquiry, Alicia L.; Beavis, William D.
2014-01-01
Parametric and nonparametric methods have been developed for purposes of predicting phenotypes. These methods are based on retrospective analyses of empirical data consisting of genotypic and phenotypic scores. Recent reports have indicated that parametric methods are unable to predict phenotypes of traits with known epistatic genetic architectures. Herein, we review parametric methods including least squares regression, ridge regression, Bayesian ridge regression, least absolute shrinkage and selection operator (LASSO), Bayesian LASSO, best linear unbiased prediction (BLUP), Bayes A, Bayes B, Bayes C, and Bayes Cπ. We also review nonparametric methods including Nadaraya-Watson estimator, reproducing kernel Hilbert space, support vector machine regression, and neural networks. We assess the relative merits of these 14 methods in terms of accuracy and mean squared error (MSE) using simulated genetic architectures consisting of completely additive or two-way epistatic interactions in an F2 population derived from crosses of inbred lines. Each simulated genetic architecture explained either 30% or 70% of the phenotypic variability. The greatest impact on estimates of accuracy and MSE was due to genetic architecture. Parametric methods were unable to predict phenotypic values when the underlying genetic architecture was based entirely on epistasis. Parametric methods were slightly better than nonparametric methods for additive genetic architectures. Distinctions among parametric methods for additive genetic architectures were incremental. Heritability, i.e., proportion of phenotypic variability, had the second greatest impact on estimates of accuracy and MSE. PMID:24727289
Spatial-Temporal Change Detection in NDVI Data Through Statistical Parametric Mapping
NASA Astrophysics Data System (ADS)
McKenna, S. A.; Yadav, V.; Gutierrez, K.
2011-12-01
Detection of significant changes in vegetation patterns provides a quantitative means of defining phenological response to changing climate. These changes may be indicative of long-term trends or shorter-duration conditions. In either case, quantifying the significance of the change patterns is critical in order to better understand the underlying processes. Spatial and temporal correlation within imaged data sets complicates change detection and must be taken into account. We apply a novel approach, Statistical Parametric Mapping (SPM), to change detection in Normalized Difference Vegetation Index (NDVI) data. SPM has been developed for identification of regions of anomalous activation in human brain imaging given functional magnetic resonance imaging (fMRI) data. Here, we adapt SPM to work on identifying anomalous regions of vegetation density within 30 years of weekly NDVI imagery. Significant change in any given image pixel is defined as a deviation from the expected value. Expected values are calculated using sinusoidal regression models fit to previous data at that location. The amount of deviation of an observation from the expected value is calculated using a modified t-test that accounts for temporal correlation in the regression data. The t-tests are applied independently to each pixel to create a t-statistic map for every time step. For a given time step, the probability that the maximum t-value exceeds a given threshold can be calculated to determine times with significant deviations, but standard techniques are not applicable due to the large number of pixels searched to find the maximum. SPM takes into account the spatial correlation of the t-statistic map to determine the significance of the maximum observed t-value. Theory developed for truncated Gaussian fields as part of SPM provides the expected number and size of regions within the t-statistic map that exceed a given threshold. The significance of the excursion regions can be assessed and then
Chaibub Neto, Elias
2015-01-01
In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965
Chaibub Neto, Elias
2015-01-01
In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson's sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling.
Ginestet, Cedric E; Simmons, Andrew
2011-03-15
Network analysis has become a tool of choice for the study of functional and structural Magnetic Resonance Imaging (MRI) data. Little research, however, has investigated connectivity dynamics in relation to varying cognitive load. In fMRI, correlations among slow (<0.1 Hz) fluctuations of blood oxygen level dependent (BOLD) signal can be used to construct functional connectivity networks. Using an anatomical parcellation scheme, we produced undirected weighted graphs linking 90 regions of the brain representing major cortical gyri and subcortical nuclei, in a population of healthy adults (n=43). Topological changes in these networks were investigated under different conditions of a classical working memory task - the N-back paradigm. A mass-univariate approach was adopted to construct statistical parametric networks (SPNs) that reflect significant modifications in functional connectivity between N-back conditions. Our proposed method allowed the extraction of 'lost' and 'gained' functional networks, providing concise graphical summaries of whole-brain network topological changes. Robust estimates of functional networks are obtained by pooling information about edges and vertices over subjects. Graph thresholding is therefore here supplanted by inference. The analysis proceeds by firstly considering changes in weighted cost (i.e. mean between-region correlation) over the different N-back conditions and secondly comparing small-world topological measures integrated over network cost, thereby controlling for differences in mean correlation between conditions. The results are threefold: (i) functional networks in the four conditions were all found to satisfy the small-world property and cost-integrated global and local efficiency levels were approximately preserved across the different experimental conditions; (ii) weighted cost considerably decreased as working memory load increased; and (iii) subject-specific weighted costs significantly predicted behavioral
ERIC Educational Resources Information Center
Ferrando, Pere J.; Lorenzo, Urbano
2000-01-01
Describes a program for computing different person-fit measures under different parametric item response models for binary items. The indexes can be computed for the Rasch model and the two- and three-parameter logistic models. The program can plot person response curves to allow the researchers to investigate the nonfitting response behavior of…
System Availability: Time Dependence and Statistical Inference by (Semi) Non-Parametric Methods
1988-08-01
Technical FROM -TO 1988 August T 42 16. SUPPLEMENTARY NOTATION 17. COSATI CODES 18 SUBJECT TERMS (Continue on reverse if necessary and identify by block...availability in finite time (not steady-state or long -run), and to non-parametric estimates. 20 DISTRIBUTION, AVAILABILITY OF ABSTRACT 21 ABSTRACT...productivity of commercial nuclear power plants; in that arena it is quantified by probabilistic risk assessment (PRA). Relaued finite state
Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne
2017-01-01
Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with ‘no or minor gait deviations’ (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with ‘no or minor gait deviations’ differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus
Nieuwenhuys, Angela; Papageorgiou, Eirini; Desloovere, Kaat; Molenaers, Guy; De Laet, Tinne
2017-01-01
Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with 'no or minor gait deviations' (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with 'no or minor gait deviations' differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study
The application of non-parametric statistical techniques to an ALARA programme.
Moon, J H; Cho, Y H; Kang, C S
2001-01-01
For the cost-effective reduction of occupational radiation dose (ORD) at nuclear power plants, it is necessary to identify what are the processes of repetitive high ORD during maintenance and repair operations. To identify the processes, the point values such as mean and median are generally used, but they sometimes lead to misjudgment since they cannot show other important characteristics such as dose distributions and frequencies of radiation jobs. As an alternative, the non-parametric analysis method is proposed, which effectively identifies the processes of repetitive high ORD. As a case study, the method is applied to ORD data of maintenance and repair processes at Kori Units 3 and 4 that are pressurised water reactors with 950 MWe capacity and have been operating since 1986 and 1987 respectively, in Korea and the method is demonstrated to be an efficient way of analysing the data.
Abdalla, M. Sebawe Khalil, E.M. Obada, A.S.-F.
2007-11-15
A Hamiltonian model that includes two-photon interaction with a two-level atom and a degenerate parametric amplifier is considered. By invoking a canonical transformation an exact solution of the wave function in the Schroedinger picture is obtained. The result presented in this context is employed to discuss the purity, the entropy squeezing, and the variance squeezing, in addition to the normal squeezing. It has been shown that the existence of the second harmonic generation leads to reduction in the squeezing amount for all quadrature variances and we found that as the value of the coupling parameter {lambda}{sub 2} increases the squeezing phenomenon gets more apparent. Further we have also considered the Q-function as an example of the quasi-probability distribution.
Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy
NASA Astrophysics Data System (ADS)
Gil, D.; Garcia-Barnes, J.; Hernández-Sabate, A.; Marti, E.
2010-03-01
Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.
NASA Astrophysics Data System (ADS)
Fripp, Jurgen; Crozier, Stuart; Warfield, Simon K.; Ourselin, Sébastien
2006-03-01
Subdivision surfaces and parameterization are desirable for many algorithms that are commonly used in Medical Image Analysis. However, extracting an accurate surface and parameterization can be difficult for many anatomical objects of interest, due to noisy segmentations and the inherent variability of the object. The thin cartilages of the knee are an example of this, especially after damage is incurred from injuries or conditions like osteoarthritis. As a result, the cartilages can have different topologies or exist in multiple pieces. In this paper we present a topology preserving (genus 0) subdivision-based parametric deformable model that is used to extract the surfaces of the patella and tibial cartilages in the knee. These surfaces have minimal thickness in areas without cartilage. The algorithm inherently incorporates several desirable properties, including: shape based interpolation, sub-division remeshing and parameterization. To illustrate the usefulness of this approach, the surfaces and parameterizations of the patella cartilage are used to generate a 3D statistical shape model.
Bogaerts, Louisa; Siegelman, Noam; Frost, Ram
2016-08-01
What determines individuals' efficacy in detecting regularities in visual statistical learning? Our theoretical starting point assumes that the variance in performance of statistical learning (SL) can be split into the variance related to efficiency in encoding representations within a modality and the variance related to the relative computational efficiency of detecting the distributional properties of the encoded representations. Using a novel methodology, we dissociated encoding from higher-order learning factors, by independently manipulating exposure duration and transitional probabilities in a stream of visual shapes. Our results show that the encoding of shapes and the retrieving of their transitional probabilities are not independent and additive processes, but interact to jointly determine SL performance. The theoretical implications of these findings for a mechanistic explanation of SL are discussed.
Della Rosa, Pasquale Anthony; Cerami, Chiara; Gallivanone, Francesca; Prestia, Annapaola; Caroli, Anna; Castiglioni, Isabella; Gilardi, Maria Carla; Frisoni, Giovanni; Friston, Karl; Ashburner, John; Perani, Daniela
2014-10-01
[18F]-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) is a widely used diagnostic tool that can detect and quantify pathophysiology, as assessed through changes in cerebral glucose metabolism. [18F]-FDG PET scans can be analyzed using voxel-based statistical methods such as Statistical Parametric Mapping (SPM) that provide statistical maps of brain abnormalities in single patients. In order to perform SPM, a "spatial normalization" of an individual's PET scan is required to match a reference PET template. The PET template currently used for SPM normalization is based on [15O]-H2O images and does not resemble either the specific metabolic features of [18F]-FDG brain scans or the specific morphological characteristics of individual brains affected by neurodegeneration. Thus, our aim was to create a new [18F]-FDG PET aging and dementia-specific template for spatial normalization, based on images derived from both age-matched controls and patients. We hypothesized that this template would increase spatial normalization accuracy and thereby preserve crucial information for research and diagnostic purposes. We investigated the statistical sensitivity and registration accuracy of normalization procedures based on the standard and new template-at the single-subject and group level-independently for subjects with Mild Cognitive Impairment (MCI), probable Alzheimer's Disease (AD), Frontotemporal lobar degeneration (FTLD) and dementia with Lewy bodies (DLB). We found a significant statistical effect of the population-specific FDG template-based normalisation in key anatomical regions for each dementia subtype, suggesting that spatial normalization with the new template provides more accurate estimates of metabolic abnormalities for single-subject and group analysis, and therefore, a more effective diagnostic measure.
NASA Astrophysics Data System (ADS)
Thomas, M. A.
2016-12-01
The Waste Isolation Pilot Plant (WIPP) is the only deep geological repository for transuranic waste in the United States. As the Science Advisor for the WIPP, Sandia National Laboratories annually evaluates site data against trigger values (TVs), metrics whose violation is indicative of conditions that may impact long-term repository performance. This study focuses on a groundwater-quality dataset used to redesign a TV for the Culebra Dolomite Member (Culebra) of the Permian-age Rustler Formation. Prior to this study, a TV violation occurred if the concentration of a major ion fell outside a range defined as the mean +/- two standard deviations. The ranges were thought to denote conditions that 95% of future values would fall within. Groundwater-quality data used in evaluating compliance, however, are rarely normally distributed. To create a more robust Culebra groundwater-quality TV, this study employed the randomization test, a non-parametric permutation method. Recent groundwater compositions considered TV violations under the original ion concentration ranges are now interpreted as false positives in light of the insignificant p-values calculated with the randomization test. This work highlights that the normality assumption can weaken as the size of a groundwater-quality dataset grows over time. Non-parametric permutation methods are an attractive option because no assumption about the statistical distribution is required and calculating all combinations of the data is an increasingly tractable problem with modern workstations. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. This research is funded by WIPP programs administered by the Office of Environmental Management (EM) of the U.S. Department of Energy. SAND2016-7306A
Panagiotopoulou, Olga; Pataky, Todd C; Hill, Zoe; Hutchinson, John R
2012-05-01
Foot pressure distributions during locomotion have causal links with the anatomical and structural configurations of the foot tissues and the mechanics of locomotion. Elephant feet have five toes bound in a flexible pad of fibrous tissue (digital cushion). Does this specialized foot design control peak foot pressures in such giant animals? And how does body size, such as during ontogenetic growth, influence foot pressures? We addressed these questions by studying foot pressure distributions in elephant feet and their correlation with body mass and centre of pressure trajectories, using statistical parametric mapping (SPM), a neuro-imaging technology. Our results show a positive correlation between body mass and peak pressures, with the highest pressures dominated by the distal ends of the lateral toes (digits 3, 4 and 5). We also demonstrate that pressure reduction in the elephant digital cushion is a complex interaction of its viscoelastic tissue structure and its centre of pressure trajectories, because there is a tendency to avoid rear 'heel' contact as an elephant grows. Using SPM, we present a complete map of pressure distributions in elephant feet during ontogeny by performing statistical analysis at the pixel level across the entire plantar/palmar surface. We hope that our study will build confidence in the potential clinical and scaling applications of mammalian foot pressures, given our findings in support of a link between regional peak pressures and pathogenesis in elephant feet.
Fujita, André; Takahashi, Daniel Y; Patriota, Alexandre G; Sato, João R
2014-12-10
Statistical inference of functional magnetic resonance imaging (fMRI) data is an important tool in neuroscience investigation. One major hypothesis in neuroscience is that the presence or not of a psychiatric disorder can be explained by the differences in how neurons cluster in the brain. Therefore, it is of interest to verify whether the properties of the clusters change between groups of patients and controls. The usual method to show group differences in brain imaging is to carry out a voxel-wise univariate analysis for a difference between the mean group responses using an appropriate test and to assemble the resulting 'significantly different voxels' into clusters, testing again at cluster level. In this approach, of course, the primary voxel-level test is blind to any cluster structure. Direct assessments of differences between groups at the cluster level seem to be missing in brain imaging. For this reason, we introduce a novel non-parametric statistical test called analysis of cluster structure variability (ANOCVA), which statistically tests whether two or more populations are equally clustered. The proposed method allows us to compare the clustering structure of multiple groups simultaneously and also to identify features that contribute to the differential clustering. We illustrate the performance of ANOCVA through simulations and an application to an fMRI dataset composed of children with attention deficit hyperactivity disorder (ADHD) and controls. Results show that there are several differences in the clustering structure of the brain between them. Furthermore, we identify some brain regions previously not described to be involved in the ADHD pathophysiology, generating new hypotheses to be tested. The proposed method is general enough to be applied to other types of datasets, not limited to fMRI, where comparison of clustering structures is of interest.
Identify fracture-critical regions inside the proximal femur using statistical parametric mapping
Li, Wenjun; Kornak, John; Harris, Tamara; Keyak, Joyce; Li, Caixia; Lu, Ying; Cheng, Xiaoguang; Lang, Thomas
2009-01-01
We identified regions inside the proximal femur that are most strongly associated with hip fracture. Bone densitometry based on such fracture-critical regions showed improved power in discriminating fracture patients from controls. Introduction Hip fractures typically occur in lateral falls, with focal mechanical failure of the sub-volumes of tissue in which the applied stress exceeds the strength. In this study, we describe a new methodology to identify proximal femoral tissue elements with highest association with hip fracture. We hypothesize that bone mineral density (BMD) measured in such sub-volumes discriminates hip fracture risk better than BMD in standard anatomic regions such as the femoral neck and trochanter. Materials and Methods We employed inter-subject registration to transform hip QCT images of 37 patients with hip fractures and 38 age-matched controls into a voxel-based statistical atlas. Within voxels, we performed t-tests between the two groups to identify the regions which differed most. We then randomly divided the 75 scans into a training set and a test set. From the training set, we derived a fracture-driven region of interest (ROI) based on association with fracture. In the test set, we measured BMD in this ROI to determine fracture discrimination efficacy using ROC analysis. Additionally, we compared the BMD distribution differences between the 29 patients with neck fractures and the 8 patients with trochanteric fractures. Results By evaluating fracture discrimination power based on ROC analysis, the fracture-driven ROI had an AUC (area under curve) of 0.92, while anatomic ROIs (including the entire proximal femur, the femoral neck, trochanter and their cortical and trabecular compartments) had AUC values between 0.78 and 0.87. We also observed that the neck fracture patients had lower BMD (p=0.014) in a small region near the femoral neck and the femoral head, and patients with trochanteric fractures had lower BMD in trochanteric regions
NASA Astrophysics Data System (ADS)
Zhu, Xiaowei; Iungo, G. Valerio; Leonardi, Stefano; Anderson, William
2017-02-01
For a horizontally homogeneous, neutrally stratified atmospheric boundary layer (ABL), aerodynamic roughness length, z_0, is the effective elevation at which the streamwise component of mean velocity is zero. A priori prediction of z_0 based on topographic attributes remains an open line of inquiry in planetary boundary-layer research. Urban topographies - the topic of this study - exhibit spatial heterogeneities associated with variability of building height, width, and proximity with adjacent buildings; such variability renders a priori, prognostic z_0 models appealing. Here, large-eddy simulation (LES) has been used in an extensive parametric study to characterize the ABL response (and z_0) to a range of synthetic, urban-like topographies wherein statistical moments of the topography have been systematically varied. Using LES results, we determined the hierarchical influence of topographic moments relevant to setting z_0. We demonstrate that standard deviation and skewness are important, while kurtosis is negligible. This finding is reconciled with a model recently proposed by Flack and Schultz (J Fluids Eng 132:041203-1-041203-10, 2010), who demonstrate that z_0 can be modelled with standard deviation and skewness, and two empirical coefficients (one for each moment). We find that the empirical coefficient related to skewness is not constant, but exhibits a dependence on standard deviation over certain ranges. For idealized, quasi-uniform cubic topographies and for complex, fully random urban-like topographies, we demonstrate strong performance of the generalized Flack and Schultz model against contemporary roughness correlations.
Brinkmann, Benjamin H; Jones, David T; Stead, Matt; Kazemi, Noojan; O'Brien, Terence J; So, Elson L; Blumenfeld, Hal; Mullan, Brian P; Worrell, Gregory A
2012-01-01
Tc-99m ethyl cysteinate diethylester (ECD) and Tc-99m hexamethyl propylene amine oxime (HMPAO) are commonly used for single-photon emission computed tomography (SPECT) studies of a variety of neurologic disorders. Although these tracers have been very helpful in diagnosing and guiding treatment of neurologic disease, data describing the distribution and laterality of these tracers in normal resting brain are limited. Advances in quantitative functional imaging have demonstrated the value of using resting studies from control populations as a baseline to account for physiologic fluctuations in cerebral perfusion. Here, we report results from 30 resting Tc-99m ECD SPECT scans and 14 resting Tc-99m HMPAO scans of normal volunteers with no history of neurologic disease. Scans were analyzed with regions of interest and with statistical parametric mapping, with comparisons performed laterally (left vs. right), as well as for age, gender, and handedness. The results show regions of significant asymmetry in the normal controls affecting widespread areas in the cerebral hemispheres, but most marked in superior parietotemporal region and frontal lobes. The results have important implications for the use of normal control SPECT images in the evaluation of patients with neurologic disease. PMID:21934696
Santos, Gabriela Lopes; Russo, Thiago Luiz; Nieuwenhuys, Angela; Monari, Davide; Desloovere, Kaat
2017-09-19
To compare sitting posture and movement strategies between chronic hemiparetic and healthy subjects while performing a drinking task using Statistical Parametric Mapping (SPM) and feature analysis. Cross-sectional study. Department of Physical Therapy of University. Thirteen chronic hemiparetic and thirteen healthy individuals matched for gender and age. Not applicable. Drinking task was divided into phases: reaching, transporting the glass to mouth, transporting the glass to table, returning to initial position. SPM two-sample t test was used to compare the entire kinematic waveforms of different joint angles (trunk, scapulothoracic, humerothoracic, elbow). Joint angles at the beginning and end of the motion, movement time, peak velocity timing, trajectory deviation, normalized integrated jerk and range of motion were extracted from the motion data. Group differences for these parameters were analyzed using independent t-tests. At the static posture and beginning of the reaching phase, patients showed a shoulder position more deviated from the midline and externally rotated with increased scapula protraction, medial rotation, anterior tilting, trunk anterior flexion and inclination to the paretic side. Altered spatiotemporal variables throughout the task were found in all phases, except for the returning phase. Patients returned to a similar posture as the task onset, except for scapula, which was normalized after the reaching phase. Chronic hemiparetic subjects showed more deviations in the proximal joints during seated posture and reaching. However, the scapular movement drew nearer the healthy individuals patterns after the first phase, showing an interesting point to consider in rehabilitation programs. Copyright © 2017. Published by Elsevier Inc.
Li, Xiaotong; Santago, Anthony C; Vidt, Meghan E; Saul, Katherine R
2016-09-06
Continuous time-series data are frequently distilled into single values and analyzed using discrete statistical methods, underutilizing large datasets. Statistical parametric mapping (SPM) allows hypotheses over the entire spectrum, but consistency with discrete analyses of kinematic data is unclear. We applied SPM to evaluate effect of load and postural demands during reaching on thoracohumeral kinematics in older and young adults, and examined consistency between one-dimensional SPM and discrete analyses of the same dataset. We hypothesized that older adults would choose postures that bring the humerus anterior to the frontal plane (towards flexion) even for low demand tasks, and that SPM would reveal differences persisting over larger temporal portions of the reach. Ten healthy older (72.4±3.1yrs) and 16 young (22.9±2.5yrs) adults reached upward and forward with high and low loads. SPM and discrete t-tests were used to analyze group effects for elevation plane, elevation, and axial rotation joint angles and velocity. Older adults used more positive (anterior) elevation plane and less elevated postures to initiate and terminate reaching (p<0.008), with long duration differences during termination. When reaching upward, differences in elevation persisted over longer temporal periods at midreach for high loads (32-58% of reach) compared to low load (41-45%). SPM and discrete analyses were consistent, but SPM permitted clear identification of temporal periods over which differences persisted, while discrete methods allowed analysis of extracted values, like ROM. This work highlights the utility of SPM to analyze kinematics time series data, and emphasizes importance of task selection when assessing age-related changes in movement. Copyright © 2016 Elsevier Ltd. All rights reserved.
Vieira, Marcus Fraga; de Brito, Ademir Alves; Lehnen, Georgia Cristina; Rodrigues, Fábio Barbosa
2017-02-27
This study analyzed gait initiation (GI) on inclined surfaces with 68 young adult subjects of both sexes. Ground reaction forces and moments were collected using two AMTI force platforms, of which one was in a horizontal position and the other was inclined by 8% in relation to the horizontal plane. Departing from a standing position, each participant executed three trials in the following conditions: horizontal position (HOR), inclined position at ankle dorsi-flexion (UP), and inclined position at ankle plantar-flexion (DOWN). Statistical parametric mapping analysis was performed over the entire center of pressure (COP) and center of mass (COM) time series. COP excursion did not show significant differences in the medial-lateral (ML) direction in both inclined conditions, but it was greater in the anterior-posterior (AP) direction for both inclined conditions. COP velocities are smaller in discrete portions of GI for the UP and DOWN conditions. COM displacement was greater in the ML direction during anticipatory postural adjustments (APA) in the UP condition, and COM moves faster in the ML direction during APA in the UP condition but slower at the end of GI for both the UP and the DOWN conditions. The COP-COM vector showed a greater angle in the DOWN condition. We observed changes for COP and COM in GI in both the UP and the DOWN conditions, with the latter showing changes for a great extent of the task. Both the UP and the DOWN conditions showed increased COM displacement and velocity. The predominant characteristic during GI on inclined surfaces, including APA, appears to be the displacement of the COM.
Balasubramanian, Madhusudhanan; Arias-Castro, Ery; Medeiros, Felipe A; Kriegman, David J; Bowd, Christopher; Weinreb, Robert N; Holst, Michael; Sample, Pamela A; Zangwill, Linda M
2014-03-19
We evaluated three new pixelwise rates of retinal height changes (PixR) strategies to reduce false-positive errors while detecting glaucomatous progression. Diagnostic accuracy of nonparametric PixR-NP cluster test (CT), PixR-NP single threshold test (STT), and parametric PixR-P STT were compared to statistic image mapping (SIM) using the Heidelberg Retina Tomograph. We included 36 progressing eyes, 210 nonprogressing patient eyes, and 21 longitudinal normal eyes from the University of California, San Diego (UCSD) Diagnostic Innovations in Glaucoma Study. Multiple comparison problem due to simultaneous testing of retinal locations was addressed in PixR-NP CT by controlling family-wise error rate (FWER) and in STT methods by Lehmann-Romano's k-FWER. For STT methods, progression was defined as an observed progression rate (ratio of number of pixels with significant rate of decrease; i.e., red-pixels, to disk size) > 2.5%. Progression criterion for CT and SIM methods was presence of one or more significant (P < 1%) red-pixel clusters within disk. Specificity in normals: CT = 81% (90%), PixR-NP STT = 90%, PixR-P STT = 90%, SIM = 90%. Sensitivity in progressing eyes: CT = 86% (86%), PixR-NP STT = 75%, PixR-P STT = 81%, SIM = 39%. Specificity in nonprogressing patient eyes: CT = 49% (55%), PixR-NP STT = 56%, PixR-P STT = 50%, SIM = 79%. Progression detected by PixR in nonprogressing patient eyes was associated with early signs of visual field change that did not yet meet our definition of glaucomatous progression. The PixR provided higher sensitivity in progressing eyes and similar specificity in normals than SIM, suggesting that PixR strategies can improve our ability to detect glaucomatous progression. Longer follow-up is necessary to determine whether nonprogressing eyes identified as progressing by these methods will develop glaucomatous progression. (ClinicalTrials.gov number, NCT00221897).
Scarpazza, Cristina; Nichols, Thomas E.; Seramondi, Donato; Maumet, Camille; Sartori, Giuseppe; Mechelli, Andrea
2016-01-01
In recent years, an increasing number of studies have used Voxel Based Morphometry (VBM) to compare a single patient with a psychiatric or neurological condition of interest against a group of healthy controls. However, the validity of this approach critically relies on the assumption that the single patient is drawn from a hypothetical population with a normal distribution and variance equal to that of the control group. In a previous investigation, we demonstrated that family-wise false positive error rate (i.e., the proportion of statistical comparisons yielding at least one false positive) in single case VBM are much higher than expected (Scarpazza et al., 2013). Here, we examine whether the use of non-parametric statistics, which does not rely on the assumptions of normal distribution and equal variance, would enable the investigation of single subjects with good control of false positive risk. We empirically estimated false positive rates (FPRs) in single case non-parametric VBM, by performing 400 statistical comparisons between a single disease-free individual and a group of 100 disease-free controls. The impact of smoothing (4, 8, and 12 mm) and type of pre-processing (Modulated, Unmodulated) was also examined, as these factors have been found to influence FPRs in previous investigations using parametric statistics. The 400 statistical comparisons were repeated using two independent, freely available data sets in order to maximize the generalizability of the results. We found that the family-wise error rate was 5% for increases and 3.6% for decreases in one data set; and 5.6% for increases and 6.3% for decreases in the other data set (5% nominal). Further, these results were not dependent on the level of smoothing and modulation. Therefore, the present study provides empirical evidence that single case VBM studies with non-parametric statistics are not susceptible to high false positive rates. The critical implication of this finding is that VBM can be used
Scarpazza, Cristina; Nichols, Thomas E; Seramondi, Donato; Maumet, Camille; Sartori, Giuseppe; Mechelli, Andrea
2016-01-01
In recent years, an increasing number of studies have used Voxel Based Morphometry (VBM) to compare a single patient with a psychiatric or neurological condition of interest against a group of healthy controls. However, the validity of this approach critically relies on the assumption that the single patient is drawn from a hypothetical population with a normal distribution and variance equal to that of the control group. In a previous investigation, we demonstrated that family-wise false positive error rate (i.e., the proportion of statistical comparisons yielding at least one false positive) in single case VBM are much higher than expected (Scarpazza et al., 2013). Here, we examine whether the use of non-parametric statistics, which does not rely on the assumptions of normal distribution and equal variance, would enable the investigation of single subjects with good control of false positive risk. We empirically estimated false positive rates (FPRs) in single case non-parametric VBM, by performing 400 statistical comparisons between a single disease-free individual and a group of 100 disease-free controls. The impact of smoothing (4, 8, and 12 mm) and type of pre-processing (Modulated, Unmodulated) was also examined, as these factors have been found to influence FPRs in previous investigations using parametric statistics. The 400 statistical comparisons were repeated using two independent, freely available data sets in order to maximize the generalizability of the results. We found that the family-wise error rate was 5% for increases and 3.6% for decreases in one data set; and 5.6% for increases and 6.3% for decreases in the other data set (5% nominal). Further, these results were not dependent on the level of smoothing and modulation. Therefore, the present study provides empirical evidence that single case VBM studies with non-parametric statistics are not susceptible to high false positive rates. The critical implication of this finding is that VBM can be used
Balasubramanian, Madhusudhanan; Arias-Castro, Ery; Medeiros, Felipe A.; Kriegman, David J.; Bowd, Christopher; Weinreb, Robert N.; Holst, Michael; Sample, Pamela A.; Zangwill, Linda M.
2014-01-01
Purpose. We evaluated three new pixelwise rates of retinal height changes (PixR) strategies to reduce false-positive errors while detecting glaucomatous progression. Methods. Diagnostic accuracy of nonparametric PixR-NP cluster test (CT), PixR-NP single threshold test (STT), and parametric PixR-P STT were compared to statistic image mapping (SIM) using the Heidelberg Retina Tomograph. We included 36 progressing eyes, 210 nonprogressing patient eyes, and 21 longitudinal normal eyes from the University of California, San Diego (UCSD) Diagnostic Innovations in Glaucoma Study. Multiple comparison problem due to simultaneous testing of retinal locations was addressed in PixR-NP CT by controlling family-wise error rate (FWER) and in STT methods by Lehmann-Romano's k-FWER. For STT methods, progression was defined as an observed progression rate (ratio of number of pixels with significant rate of decrease; i.e., red-pixels, to disk size) > 2.5%. Progression criterion for CT and SIM methods was presence of one or more significant (P < 1%) red-pixel clusters within disk. Results. Specificity in normals: CT = 81% (90%), PixR-NP STT = 90%, PixR-P STT = 90%, SIM = 90%. Sensitivity in progressing eyes: CT = 86% (86%), PixR-NP STT = 75%, PixR-P STT = 81%, SIM = 39%. Specificity in nonprogressing patient eyes: CT = 49% (55%), PixR-NP STT = 56%, PixR-P STT = 50%, SIM = 79%. Progression detected by PixR in nonprogressing patient eyes was associated with early signs of visual field change that did not yet meet our definition of glaucomatous progression. Conclusions. The PixR provided higher sensitivity in progressing eyes and similar specificity in normals than SIM, suggesting that PixR strategies can improve our ability to detect glaucomatous progression. Longer follow-up is necessary to determine whether nonprogressing eyes identified as progressing by these methods will develop glaucomatous progression. (ClinicalTrials.gov number, NCT00221897.) PMID:24519427
Zhu, Yuankai; Feng, Jianhua; Wu, Shuang; Hou, Haifeng; Ji, Jianfeng; Zhang, Kai; Chen, Qing; Chen, Lin; Cheng, Haiying; Gao, Liuyan; Chen, Zexin; Zhang, Hong; Tian, Mei
2017-08-01
PET with (18)F-FDG has been used for presurgical localization of epileptogenic foci; however, in nonsurgical patients, the correlation between cerebral glucose metabolism and clinical severity has not been fully understood. The aim of this study was to evaluate the glucose metabolic profile using (18)F-FDG PET/CT imaging in patients with epilepsy. Methods: One hundred pediatric epilepsy patients who underwent (18)F-FDG PET/CT, MRI, and electroencephalography examinations were included. Fifteen age-matched controls were also included. (18)F-FDG PET images were analyzed by visual assessment combined with statistical parametric mapping (SPM) analysis. The absolute asymmetry index (|AI|) was calculated in patients with regional abnormal glucose metabolism. Results: Visual assessment combined with SPM analysis of (18)F-FDG PET images detected more patients with abnormal glucose metabolism than visual assessment only. The |AI| significantly positively correlated with seizure frequency (P < 0.01) but negatively correlated with the time since last seizure (P < 0.01) in patients with abnormal glucose metabolism. The only significant contributing variable to the |AI| was the time since last seizure, in patients both with hypometabolism (P = 0.001) and with hypermetabolism (P = 0.005). For patients with either hypometabolism (P < 0.01) or hypermetabolism (P = 0.209), higher |AI| values were found in those with drug resistance than with seizure remission. In the post-1-y follow-up PET studies, a significant change of |AI| (%) was found in patients with clinical improvement compared with those with persistence or progression (P < 0.01). Conclusion:(18)F-FDG PET imaging with visual assessment combined with SPM analysis could provide cerebral glucose metabolic profiles in nonsurgical epilepsy patients. |AI| might be used for evaluation of clinical severity and progress in these patients. Patients with a prolonged period of seizure freedom may have more subtle (or no) metabolic
Ito, K; Morrish, P; Rakshi, J; Uema, T; Ashburner, J; Bailey, D; Friston, K; Brooks, D
1999-01-01
OBJECTIVE—To apply statistical parametric mapping to 18F-dopa PET data sets, to examine the regional distribution of changes in dopaminergic metabolism in early asymmetric Parkinson's disease. METHODS—Thirteen normal volunteers (age 57.7 (SD 16.5) years; four women, nine men ) and six patients (age 50.3 (SD 13.5) years; three women, three men) with asymmetric (right sided) Parkinson's disease were studied. Images from each dynamic dopa PET dataset were aligned and parametric images of 18F-dopa influx (Ki) were created for each subject. The Ki images were transformed into standard stereotactic space. The Ki values of the caudate and putamen on spatially normalised images were compared with the Ki values before normalisation. The application of statistical parametric mapping (SPM) allowed statistical comparison of regional Ki values on a voxel by voxel basis between healthy volunteers and patients with Parkinson's disease. RESULTS—There was a strong correlation between the Ki values before and after spatial normalisation (r=0.898, p=0.0001). Significant decreases in the Ki values were found for the Parkinson's desease group throughout the entire left putamen (p< 0.001) and focally in the dorsal right putamen (p< 0.001). Decreased Ki values were also shown bilaterally in the substantia nigra (p< 0.01). CONCLUSION—Using (SPM) and 18F-dopa PET, reductions in both striatal and nigral brain dopaminergic function could be demonstrated in early Parkinson's disease. PMID:10329749
Carballido-Gamio, Julio; Bonaretti, Serena; Kazakia, Galateia J; Khosla, Sundeep; Majumdar, Sharmila; Lang, Thomas F; Burghardt, Andrew J
2017-04-01
HR-pQCT enables in vivo multi-parametric assessments of bone microstructure in the distal radius and distal tibia. Conventional HR-pQCT image analysis approaches summarize bone parameters into global scalars, discarding relevant spatial information. In this work, we demonstrate the feasibility and reliability of statistical parametric mapping (SPM) techniques for HR-pQCT studies, which enable population-based local comparisons of bone properties. We present voxel-based morphometry (VBM) to assess trabecular and cortical bone voxel-based features, and a surface-based framework to assess cortical bone features both in cross-sectional and longitudinal studies. In addition, we present tensor-based morphometry (TBM) to assess trabecular and cortical bone structural changes. The SPM techniques were evaluated based on scan-rescan HR-pQCT acquisitions with repositioning of the distal radius and distal tibia of 30 subjects. For VBM and surface-based SPM purposes, all scans were spatially normalized to common radial and tibial templates, while for TBM purposes, rescans (follow-up) were spatially normalized to their corresponding scans (baseline). VBM was evaluated based on maps of local bone volume fraction (BV/TV), homogenized volumetric bone mineral density (vBMD), and homogenized strain energy density (SED) derived from micro-finite element analysis; while the cortical bone framework was evaluated based on surface maps of cortical bone thickness, vBMD, and SED. Voxel-wise and vertex-wise comparisons of bone features were done between the groups of baseline and follow-up scans. TBM was evaluated based on mean square errors of determinants of Jacobians at baseline bone voxels. In both anatomical sites, voxel- and vertex-wise uni- and multi-parametric comparisons yielded non-significant differences, and TBM showed no artefactual bone loss or apposition. The presented SPM techniques demonstrated robust specificity thus warranting their application in future clinical HR
NASA Astrophysics Data System (ADS)
Gallego, A.; Benavent-Climent, A.; Romo-Melo, L.
2015-08-01
The paper proposes a new application of non-parametric statistical processing of signals recorded from vibration tests for damage detection and evaluation on I-section steel segments. The steel segments investigated constitute the energy dissipating part of a new type of hysteretic damper that is used for passive control of buildings and civil engineering structures subjected to earthquake-type dynamic loadings. Two I-section steel segments with different levels of damage were instrumented with piezoceramic sensors and subjected to controlled white noise random vibrations. The signals recorded during the tests were processed using two non-parametric methods (the power spectral density method and the frequency response function method) that had never previously been applied to hysteretic dampers. The appropriateness of these methods for quantifying the level of damage on the I-shape steel segments is validated experimentally. Based on the results of the random vibrations, the paper proposes a new index that predicts the level of damage and the proximity of failure of the hysteretic damper.
Jamalabadi, Hamidreza; Alizadeh, Sarah; Schönauer, Monika; Leibold, Christian; Gais, Steffen
2016-05-01
Multivariate pattern analysis (MVPA) has recently become a popular tool for data analysis. Often, classification accuracy as quantified by correct classification rate (CCR) is used to illustrate the size of the effect under investigation. However, we show that in low sample size (LSS), low effect size (LES) data, which is typical in neuroscience, the distribution of CCRs from cross-validation of linear MVPA is asymmetric and can show classification rates considerably below what would be expected from chance classification. Conversely, the mode of the distribution in these cases is above expected chance levels, leading to a spuriously high number of above chance CCRs. This unexpected distribution has strong implications when using MVPA for hypothesis testing. Our analyses warrant the conclusion that CCRs do not well reflect the size of the effect under investigation. Moreover, the skewness of the null-distribution precludes the use of many standard parametric tests to assess significance of CCRs. We propose that MVPA results should be reported in terms of P values, which are estimated using randomization tests. Also, our results show that cross-validation procedures using a low number of folds, e.g. twofold, are generally more sensitive, even though the average CCRs are often considerably lower than those obtained using a higher number of folds. Hum Brain Mapp 37:1842-1855, 2016. © 2016 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Valotto, Gabrio; Varin, Cristiano
2016-01-01
An additive modeling approach is employed to provide a statistical description of hourly variation in concentrations of NOx measured in proximity of the Venice "Marco Polo" International Airport, Italy. Differently from several previous studies on airport emissions based on daily time series, the paper analyzes hourly data because variations of NOx concentrations during the day are informative about the prevailing emission source. The statistical analysis is carried out using a one-year time series. Confounder effects due to seasonality, meteorology and airport traffic volume are accounted for by suitable covariates. Four different model specifications of increasing complexity are considered. The model with the aircraft source expressed as the NOx emitted near the airport is found to have the best predictive quality. Although the aircraft source is statistically significant, the comparison of model-based predictions suggests that the relative impact of aircraft emissions to ambient NOx concentrations is limited and the road traffic is the likely dominant source near the sampling point.
Harada, Kengo; Saeki, Hiroshi; Matsuya, Eiji; Okita, Izumi
2013-11-01
We carried out differential diagnosis of brain blood flow images using single-photon emission computed tomography (SPECT) for patients with Parkinson's disease (PD) or progressive supranuclear paralysis (PSP) using statistical parametric mapping (SPM) and to whom we had applied anatomical standardization. We studied two groups and compared brain blood flow images using SPECT (N-isopropyl-4-iodoamphetamine [(123)I] hydrochloride injection, 222 MGq dosage i.v.). A total of 27 patients were studied using SPM: 18 with PD and 9 with PSP; humming bird sign on MRI was from moderate to medium. The decline of brain bloodstream in the PSP group was more notable in the midbrain, near the domain where the humming bird sign was observable, than in the PD group. The observable differences in brain bloodstream decline in the midbrain of PSP and PD patients suggest the potential usefulness of this technique's clinical application to distinction diagnosis.
Korany, Mohamed A; Maher, Hadir M; Galal, Shereen M; Ragab, Marwa A A
2013-05-01
This manuscript discusses the application and the comparison between three statistical regression methods for handling data: parametric, nonparametric, and weighted regression (WR). These data were obtained from different chemometric methods applied to the high-performance liquid chromatography response data using the internal standard method. This was performed on a model drug Acyclovir which was analyzed in human plasma with the use of ganciclovir as internal standard. In vivo study was also performed. Derivative treatment of chromatographic response ratio data was followed by convolution of the resulting derivative curves using 8-points sin x i polynomials (discrete Fourier functions). This work studies and also compares the application of WR method and Theil's method, a nonparametric regression (NPR) method with the least squares parametric regression (LSPR) method, which is considered the de facto standard method used for regression. When the assumption of homoscedasticity is not met for analytical data, a simple and effective way to counteract the great influence of the high concentrations on the fitted regression line is to use WR method. WR was found to be superior to the method of LSPR as the former assumes that the y-direction error in the calibration curve will increase as x increases. Theil's NPR method was also found to be superior to the method of LSPR as the former assumes that errors could occur in both x- and y-directions and that might not be normally distributed. Most of the results showed a significant improvement in the precision and accuracy on applying WR and NPR methods relative to LSPR.
Hyun, Y; Lee, J S; Rha, J H; Lee, I K; Ha, C K; Lee, D S
2001-02-01
The purpose of this study was to investigate the differences between technetium-99m ethyl cysteinate dimer (99mTc-ECD) and technetium-99m hexamethylpropylene amine oxime (99mTc-HMPAO) uptake in the same brains by means of statistical parametric mapping (SPM) analysis. We examined 20 patients (9 male, 11 female, mean age 62+/-12 years) using 99mTc-ECD and 99mTc-HMPAO single-photon emission tomography (SPET) and magnetic resonance imaging (MRI) of the brain less than 7 days after onset of stroke. MRI showed no cortical infarctions. Infarctions in the pons (6 patients) and medulla (1), ischaemic periventricular white matter lesions (13) and lacunar infarction (7) were found on MRI. Split-dose and sequential SPET techniques were used for 99mTc-ECD and 99mTc-HMPAO brain SPET, without repositioning of the patient. All of the SPET images were spatially transformed to standard space, smoothed and globally normalized. The differences between the 99mTc-ECD and 99mTc-HMPAO SPET images were statistically analysed using statistical parametric mapping (SPM) 96 software. The difference between two groups was considered significant at a threshold of uncorrected P values less than 0.01. Visual analysis showed no hypoperfused areas on either 99mTc-ECD or 99mTc-HMPAO SPET images. SPM analysis revealed significantly different uptake of 99mTc-ECD and 99mTc-HMPAO in the same brains. On the 99mTc-ECD SPET images, relatively higher uptake was observed in the frontal, parietal and occipital lobes, in the left superior temporal lobe and in the superior region of the cerebellum. On the 99mTc-HMPAO SPET images, relatively higher uptake was observed in the medial temporal lobes, thalami, periventricular white matter and brain stem. These differences in uptake of the two tracers in the same brains on SPM analysis suggest that interpretation of cerebral perfusion is possible using SPET with 99mTc-ECD and 99mTc-HMPAO.
NASA Astrophysics Data System (ADS)
Marchand, Paul J.; Bouwens, Arno; Shamaei, Vincent; Nguyen, David; Extermann, Jerome; Bolmont, Tristan; Lasser, Theo
2016-03-01
Magnetic Resonance Imaging has revolutionised our understanding of brain function through its ability to image human cerebral structures non-invasively over the entire brain. By exploiting the different magnetic properties of oxygenated and deoxygenated blood, functional MRI can indirectly map areas undergoing neural activation. Alongside the development of fMRI, powerful statistical tools have been developed in an effort to shed light on the neural pathways involved in processing of sensory and cognitive information. In spite of the major improvements made in fMRI technology, the obtained spatial resolution of hundreds of microns prevents MRI in resolving and monitoring processes occurring at the cellular level. In this regard, Optical Coherence Microscopy is an ideal instrumentation as it can image at high spatio-temporal resolution. Moreover, by measuring the mean and the width of the Doppler spectra of light scattered by moving particles, OCM allows extracting the axial and lateral velocity components of red blood cells. The ability to assess quantitatively total blood velocity, as opposed to classical axial velocity Doppler OCM, is of paramount importance in brain imaging as a large proportion of cortical vascular is oriented perpendicularly to the optical axis. We combine here quantitative blood flow imaging with extended-focus Optical Coherence Microscopy and Statistical Parametric Mapping tools to generate maps of stimuli-evoked cortical hemodynamics at the capillary level.
Breitling, Rainer; Herzyk, Pawel
2005-10-01
We have recently introduced a rank-based test statistic, RankProducts (RP), as a new non-parametric method for detecting differentially expressed genes in microarray experiments. It has been shown to generate surprisingly good results with biological datasets. The basis for this performance and the limits of the method are, however, little understood. Here we explore the performance of such rank-based approaches under a variety of conditions using simulated microarray data, and compare it with classical Wilcoxon rank sums and t-statistics, which form the basis of most alternative differential gene expression detection techniques. We show that for realistic simulated microarray datasets, RP is more powerful and accurate for sorting genes by differential expression than t-statistics or Wilcoxon rank sums - in particular for replicate numbers below 10, which are most commonly used in biological experiments. Its relative performance is particularly strong when the data are contaminated by non-normal random noise or when the samples are very inhomogenous, e.g. because they come from different time points or contain a mixture of affected and unaffected cells. However, RP assumes equal measurement variance for all genes and tends to give overly optimistic p-values when this assumption is violated. It is therefore essential that proper variance stabilizing normalization is performed on the data before calculating the RP values. Where this is impossible, another rank-based variant of RP (average ranks) provides a useful alternative with very similar overall performance. The Perl scripts implementing the simulation and evaluation are available upon request. Implementations of the RP method are available for download from the authors website (http://www.brc.dcs.gla.ac.uk/glama).
Marchand, Paul J.; Bouwens, Arno; Bolmont, Tristan; Shamaei, Vincent K.; Nguyen, David; Szlag, Daniel; Extermann, Jérôme; Lasser, Theo
2016-01-01
Functional magnetic resonance (fMRI) imaging is the current gold-standard in neuroimaging. fMRI exploits local changes in blood oxygenation to map neuronal activity over the entire brain. However, its spatial resolution is currently limited to a few hundreds of microns. Here we use extended-focus optical coherence microscopy (xfOCM) to quantitatively measure changes in blood flow velocity during functional hyperaemia at high spatio-temporal resolution in the somatosensory cortex of mice. As optical coherence microscopy acquires hundreds of depth slices simultaneously, blood flow velocity measurements can be performed over several vessels in parallel. We present the proof-of-principle of an optimised statistical parametric mapping framework to analyse quantitative blood flow timetraces acquired with xfOCM using the general linear model. We demonstrate the feasibility of generating maps of cortical hemodynamic reactivity at the capillary level with optical coherence microscopy. To validate our method, we exploited 3 stimulation paradigms, covering different temporal dynamics and stimulated limbs, and demonstrated its repeatability over 2 trials, separated by a week. PMID:28101397
Jin, Qian; He, Li-Jun; Zhang, Ai-Bing
2012-01-01
In the recent worldwide campaign for the global biodiversity inventory via DNA barcoding, a simple and easily used measure of confidence for assigning sequences to species in DNA barcoding has not been established so far, although the likelihood ratio test and the bayesian approach had been proposed to address this issue from a statistical point of view. The TDR (Two Dimensional non-parametric Resampling) measure newly proposed in this study offers users a simple and easy approach to evaluate the confidence of species membership in DNA barcoding projects. We assessed the validity and robustness of the TDR approach using datasets simulated under coalescent models, and an empirical dataset, and found that TDR measure is very robust in assessing species membership of DNA barcoding. In contrast to the likelihood ratio test and bayesian approach, the TDR method stands out due to simplicity in both concepts and calculations, with little in the way of restrictive population genetic assumptions. To implement this approach we have developed a computer program package (TDR1.0beta) freely available from ftp://202.204.209.200/education/video/TDR1.0beta.rar.
Asano, Yoshitaka; Shinoda, Jun; Okumura, Ayumi; Aki, Tatsuki; Takenaka, Shunsuke; Miwa, Kazuhiro; Yamada, Mikito; Ito, Takeshi; Yokoyama, Kazutoshi
2012-01-01
Diffusion tensor imaging (DTI) has recently evolved as valuable technique to investigate diffuse axonal injury (DAI). This study examined whether fractional anisotropy (FA) images analyzed by statistical parametric mapping (FA-SPM images) are superior to T(2)*-weighted gradient recalled echo (T2*GRE) images or fluid-attenuated inversion recovery (FLAIR) images for detecting minute lesions in traumatic brain injury (TBI) patients. DTI was performed in 25 patients with cognitive impairments in the chronic stage after mild or moderate TBI. The FA maps obtained from the DTI were individually compared with those from age-matched healthy control subjects using voxel-based analysis and FA-SPM images (p < 0.001). Abnormal low-intensity areas on T2*GRE images (T2* lesions) were found in 10 patients (40.0%), abnormal high-intensity areas on FLAIR images in 4 patients (16.0%), and areas with significantly decreased FA on FA-SPM image in 16 patients (64.0%). Nine of 10 patients with T2* lesions had FA-SPM lesions. FA-SPM lesions topographically included most T2* lesions in the white matter and the deep brain structures, but did not include T2* lesions in the cortex/near-cortex or lesions containing substantial hemosiderin regardless of location. All 4 patients with abnormal areas on FLAIR images had FA-SPM lesions. FA-SPM imaging is useful for detecting minute lesions because of DAI in the white matter and the deep brain structures, which may not be visualized on T2*GRE or FLAIR images, and may allow the detection of minute brain lesions in patients with post-traumatic cognitive impairment.
Colloby, Sean J; Fenwick, John D; Williams, E David; Paling, Sean M; Lobotesis, Kyriakos; Ballard, Clive; McKeith, Ian; O'Brien, John T
2002-05-01
Differences in regional cerebral blood flow (rCBF) between subjects with Alzheimer's disease (AD), dementia with Lewy bodies (DLB) and healthy volunteers were investigated using statistical parametric mapping (SPM99). Forty-eight AD, 23 DLB and 20 age-matched control subjects participated. Technetium-99m hexamethylpropylene amine oxime (HMPAO) brain single-photon emission tomography (SPET) scans were acquired for each subject using a single-headed rotating gamma camera (IGE CamStar XR/T). The SPET images were spatially normalised and group comparison was performed by SPM99. In addition, covariate analysis was undertaken on the standardised images taking the Mini Mental State Examination (MMSE) scores as a variable. Applying a height threshold of P < or = 0.001 uncorrected, significant perfusion deficits in the parietal and frontal regions of the brain were observed in both AD and DLB groups compared with the control subjects. In addition, significant temporoparietal perfusion deficits were identified in the AD subjects, whereas the DLB patients had deficits in the occipital region. Comparison of dementia groups (height threshold of P < or = 0.01 uncorrected) yielded hypoperfusion in both the parietal [Brodmann area (BA) 7] and occipital (BA 17, 18) regions of the brain in DLB compared with AD. Abnormalities in these areas, which included visual cortex and several areas involved in higher visual processing and visuospatial function, may be important in understanding the visual hallucinations and visuospatial deficits which are characteristic of DLB. Covariate analysis indicated group differences between AD and DLB in terms of a positive correlation between cognitive test score and temporoparietal blood flow. In conclusion, we found evidence of frontal and parietal hypoperfusion in both AD and DLB, while temporal perfusion deficits were observed exclusively in AD and parieto-occipital deficits in DLB.
NASA Astrophysics Data System (ADS)
Oh, Jungsu S.; Kim, Jae Seung; Chae, Sun Young; Oh, Minyoung; Oh, Seung Jun; Cha, Seung Nam; Chang, Ho-Jong; Lee, Chong Sik; Lee, Jae Hong
2017-03-01
We present an optimized voxelwise statistical parametric mapping (SPM) of partial-volume (PV)-corrected positron emission tomography (PET) of 11C Pittsburgh Compound B (PiB), incorporating the anatomical precision of magnetic resonance image (MRI) and amyloid β (A β) burden-specificity of PiB PET. First, we applied region-based partial-volume correction (PVC), termed the geometric transfer matrix (GTM) method, to PiB PET, creating MRI-based lobar parcels filled with mean PiB uptakes. Then, we conducted a voxelwise PVC by multiplying the original PET by the ratio of a GTM-based PV-corrected PET to a 6-mm-smoothed PV-corrected PET. Finally, we conducted spatial normalizations of the PV-corrected PETs onto the study-specific template. As such, we increased the accuracy of the SPM normalization and the tissue specificity of SPM results. Moreover, lobar smoothing (instead of whole-brain smoothing) was applied to increase the signal-to-noise ratio in the image without degrading the tissue specificity. Thereby, we could optimize a voxelwise group comparison between subjects with high and normal A β burdens (from 10 patients with Alzheimer's disease, 30 patients with Lewy body dementia, and 9 normal controls). Our SPM framework outperformed than the conventional one in terms of the accuracy of the spatial normalization (85% of maximum likelihood tissue classification volume) and the tissue specificity (larger gray matter, and smaller cerebrospinal fluid volume fraction from the SPM results). Our SPM framework optimized the SPM of a PV-corrected A β PET in terms of anatomical precision, normalization accuracy, and tissue specificity, resulting in better detection and localization of A β burdens in patients with Alzheimer's disease and Lewy body dementia.
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
Parametric Cost Models for Space Telescopes
NASA Technical Reports Server (NTRS)
Stahl, H. Philip
2010-01-01
A study is in-process to develop a multivariable parametric cost model for space telescopes. Cost and engineering parametric data has been collected on 30 different space telescopes. Statistical correlations have been developed between 19 variables of 59 variables sampled. Single Variable and Multi-Variable Cost Estimating Relationships have been developed. Results are being published.
Jang, Jae-Won; Youn, Young Chul; Seok, Ju-Won; Ha, Sam-Yeol; Shin, Hae-Won; Ahan, Suk-Won; Park, Kwang-Yeol; Kwon, Oh-Sang
2011-08-01
Charles Bonnet syndrome (CBS) is characterized by the occurrence of complex visual hallucinations in visually impaired patients who understand that what they see is unreal. The pathophysiologic mechanism of CBS is poorly understood. However, hypermetabolism of the thalamocortical pathway as a result of deafferentation was recently proposed as a possible mechanism. A 69-year-old patient with CBS presented with a 5-year history of visual hallucinations after bilateral visual impairment, which had progressed to troublesome images of many unreal people and animals. Positron emission tomography-statistical parametric mapping (PET-SPM) imaging studies initially revealed hypermetabolism in the right inferior temporal area and left thalamus, which disappeared after treatment with valproic acid. This case, using PET-SPM analysis, supports the thalamic hypermetabolism theory of CBS.
Feng, Dagan; Wang, Zhizhong . Basser Dept. of Computer Science); Huang, Sung Cheng . Dept. of Radiological Sciences)
1993-06-01
With the advent of positron emission tomography (PET), a variety of techniques have been developed to measure local cerebral blood flow (LCBF) noninvasively in humans. It is essential that the techniques developed should be statistically reliable and computationally efficient. A potential class of techniques, which includes linear least squares (LS), linear weighted least squares (WLS), linear generalized least squares (GLS), and linear generalized weighted least squares (GWLS), is proposed. The statistical characteristics of the new methods were examined by computer simulation. The authors present a comparison of these four methods with two other rapid estimation techniques developed by Huang et al. and Alpert, and two classical methods, the unweighted and weighted nonlinear least squares regression which are supposed to have optimal statistical properties. The results show that the new methods can take full advantage of the contribution from the fine temporal sampling data of modern tomographs, and thus provide statistically reliable estimates that are comparable to those obtained from nonlinear least squares regression. The new methods also have high computational efficiency, and the parameters can be estimated directly from operational equations in one single step. Therefore, they can potentially be used in image-wide estimation of local cerebral blood flow and distribution volume with positron emission tomography.
Huang, Qi; Nie, Binbin; Ma, Chen; Wang, Jing; Zhang, Tianhao; Duan, Shaofeng; Wu, Shang; Liang, Shengxiang; Li, Panlong; Liu, Hua; Sun, Hua; Zhou, Jiangning; Xu, Lin; Shan, Baoci
2017-09-14
Tree shrews are proposed as an alternative animal model to nonhuman primates due to their close affinity to primates. Neuroimaging techniques are widely used to study brain functions and structures of humans and animals. However, tree shrews are rarely applied in neuroimaging field partly due to the lack of available species specific analysis methods. In this study, 10 PET/CT and 10 MRI images of tree shrew brain were used to construct PET and MRI templates; based on histological atlas we reconstructed a three-dimensional digital atlas with 628 structures delineated; then the digital atlas and templates were aligned into a stereotaxic space. Finally, we integrated the digital atlas and templates into a toolbox for tree shrew brain spatial normalization, statistical analysis and results localization. We validated the feasibility of the toolbox by simulated data with lesions in laterodorsal thalamic nucleus (LD). The lesion volumes of simulated PET and MRI images were (12.97±3.91)mm(3) and (7.04±0.84)mm(3). Statistical results at p<0.005 showed the lesion volumes of PET and MRI were 13.18mm(3) and 8.06mm(3) in LD. To our knowledge, we report the first PET template and digital atlas of tree shrew brain. Compared to the existing MRI templates, our MRI template was aligned into stereotaxic space. And the toolbox is the first software dedicated for tree shrew brain analysis. The templates and digital atlas of tree shrew brain, as well as the toolbox, facilitate the use of tree shrews in neuroimaging field. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Chen, Kewei; Ge, Xiaolin; Yao, Li; Bandy, Dan; Alexander, Gene E.; Prouty, Anita; Burns, Christine; Zhao, Xiaojie; Wen, Xiaotong; Korn, Ronald; Lawson, Michael; Reiman, Eric M.
2006-03-01
Having approved fluorodeoxyglucose positron emission tomography (FDG PET) for the diagnosis of Alzheimer's disease (AD) in some patients, the Centers for Medicare and Medicaid Services suggested the need to develop and test analysis techniques to optimize diagnostic accuracy. We developed an automated computer package comparing an individual's FDG PET image to those of a group of normal volunteers. The normal control group includes FDG-PET images from 82 cognitively normal subjects, 61.89+/-5.67 years of age, who were characterized demographically, clinically, neuropsychologically, and by their apolipoprotein E genotype (known to be associated with a differential risk for AD). In addition, AD-affected brain regions functionally defined as based on a previous study (Alexander, et al, Am J Psychiatr, 2002) were also incorporated. Our computer package permits the user to optionally select control subjects, matching the individual patient for gender, age, and educational level. It is fully streamlined to require minimal user intervention. With one mouse click, the program runs automatically, normalizing the individual patient image, setting up a design matrix for comparing the single subject to a group of normal controls, performing the statistics, calculating the glucose reduction overlap index of the patient with the AD-affected brain regions, and displaying the findings in reference to the AD regions. In conclusion, the package automatically contrasts a single patient to a normal subject database using sound statistical procedures. With further validation, this computer package could be a valuable tool to assist physicians in decision making and communicating findings with patients and patient families.
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1995-01-01
Parametric cost analysis is a mathematical approach to estimating cost. Parametric cost analysis uses non-cost parameters, such as quality characteristics, to estimate the cost to bring forth, sustain, and retire a product. This paper reviews parametric cost analysis and shows how it can be used within the cost deployment process.
PHAZE. Parametric Hazard Function Estimation
Atwood, C.L.
1990-09-01
Phaze performs statistical inference calculations on a hazard function ( also called a failure rate or intensity function) based on reported failure times of components that are repaired and restored to service. Three parametric models are allowed: the exponential, linear, and Weibull hazard models. The inference includes estimation (maximum likelihood estimators and confidence regions) of the parameters and of the hazard function itself, testing of hypotheses such as increasing failure rate, and checking of the model assumptions.
Xi, Yin; Yuan, Qing; Zhang, Yue; Madhuranthakam, Ananth J; Fulkerson, Michael; Margulis, Vitaly; Brugarolas, James; Kapur, Payal; Cadeddu, Jeffrey A; Pedrosa, Ivan
2017-07-05
To apply a statistical clustering algorithm to combine information from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) into a single tumour map to distinguish high-grade from low-grade T1b clear cell renal cell carcinoma (ccRCC). This prospective, Institutional Review Board -approved, Health Insurance Portability and Accountability Act -compliant study included 18 patients with solid T1b ccRCC who underwent pre-surgical DCE MRI. After statistical clustering of the parametric maps of the transfer constant between the intravascular and extravascular space (K (trans) ), rate constant (K ep ) and initial area under the concentration curve (iAUC) with a fuzzy c-means (FCM) algorithm, each tumour was segmented into three regions (low/medium/high active areas). Percentages of each region and tumour size were compared to tumour grade at histopathology. A decision-tree model was constructed to select the best parameter(s) to predict high-grade ccRCC. Seven high-grade and 11 low-grade T1b ccRCCs were included. High-grade histology was associated with higher percent high active areas (p = 0.0154) and this was the only feature selected by the decision tree model, which had a diagnostic performance of 78% accuracy, 86% sensitivity, 73% specificity, 67% positive predictive value and 89% negative predictive value. The FCM integrates multiple DCE-derived parameter maps and identifies tumour regions with unique pharmacokinetic characteristics. Using this approach, a decision tree model using criteria beyond size to predict tumour grade in T1b ccRCCs is proposed. • Tumour size did not correlate with tumour grade in T1b ccRCC. • Tumour heterogeneity can be analysed using statistical clustering via DCE-MRI parameters. • High-grade ccRCC has a larger percentage of high active area than low-grade ccRCCs. • A decision-tree model offers a simple way to differentiate high/low-grade ccRCCs.
Nakatsuka, Tomoya; Imabayashi, Etsuko; Matsuda, Hiroshi; Sakakibara, Ryuji; Inaoka, Tsutomu; Terada, Hitoshi
2013-05-01
The purpose of this study was to identify brain atrophy specific for dementia with Lewy bodies (DLB) and to evaluate the discriminatory performance of this specific atrophy between DLB and Alzheimer's disease (AD). We retrospectively reviewed 60 DLB and 30 AD patients who had undergone 3D T1-weighted MRI. We randomly divided the DLB patients into two equal groups (A and B). First, we obtained a target volume of interest (VOI) for DLB-specific atrophy using correlation analysis of the percentage rate of significant whole white matter (WM) atrophy calculated using the Voxel-based Specific Regional Analysis System for Alzheimer's Disease (VSRAD) based on statistical parametric mapping 8 (SPM8) plus diffeomorphic anatomic registration through exponentiated Lie algebra, with segmented WM images in group A. We then evaluated the usefulness of this target VOI for discriminating the remaining 30 DLB patients in group B from the 30 AD patients. Z score values in this target VOI obtained from VSRAD were used as the determinant in receiver operating characteristic (ROC) analysis. Specific target VOIs for DLB were determined in the right-side dominant dorsal midbrain, right-side dominant dorsal pons, and bilateral cerebellum. ROC analysis revealed that the target VOI limited to the midbrain exhibited the highest area under the ROC curves of 0.75. DLB patients showed specific atrophy in the midbrain, pons, and cerebellum. Midbrain atrophy demonstrated the highest power for discriminating DLB and AD. This approach may be useful for determining the contributions of DLB and AD pathologies to the dementia syndrome.
Parametrically defined differential equations
NASA Astrophysics Data System (ADS)
Polyanin, A. D.; Zhurov, A. I.
2017-01-01
The paper deals with nonlinear ordinary differential equations defined parametrically by two relations. It proposes techniques to reduce such equations, of the first or second order, to standard systems of ordinary differential equations. It obtains the general solution to some classes of nonlinear parametrically defined ODEs dependent on arbitrary functions. It outlines procedures for the numerical solution of the Cauchy problem for parametrically defined differential equations.
Parametric Resonance Revisited
NASA Astrophysics Data System (ADS)
van den Broeck, C.; Bena, I.
The phenomenon of parametric resonance is revisited. Several physical examples are reviewed and an exactly solvable model is discussed. A mean field theory is presented for globally coupled parametric oscillators with randomly distributed phases. A new type of collective instability appears, which is similar in nature to that of noise induced phase transitions.
Penalized Likelihood for General Semi-Parametric Regression Models.
1985-05-01
should be stressed that q, while it may be somewhat less than n, will still be ’large’, and parametric estimation of £ will not be appropriate...Partial spline models for the semi- parametric estimation of functions of several variables, in Statistical Analysis of Time Series, Tokyo: Institute of
Measurement selection for parametric IC fault diagnosis
NASA Technical Reports Server (NTRS)
Wu, A.; Meador, J.
1991-01-01
Experimental results obtained with the use of measurement reduction for statistical IC fault diagnosis are described. The reduction method used involves data pre-processing in a fashion consistent with a specific definition of parametric faults. The effects of this preprocessing are examined.
NASA Technical Reports Server (NTRS)
Prince, Frank A.
2017-01-01
Building a parametric cost model is hard work. The data is noisy and often does not behave like we want it to. We need statistics to give us an indication of the goodness of our models, but; statistics can be manipulated and mislead. On top of all of that, our own very human biases can lead us astray; causing us to see patterns in the noise and draw false conclusions from the data. Yet, it is the data itself that is the foundation for making better cost estimates and cost models. I believe the mistake we often make is we believe that our models are representative of the data; that our models summarize the experiences, the knowledge, and the stories contained in the data. However, it is the opposite that is true. Our models are but imitations of reality. They give us trends, but not truth. The experiences, the knowledge, and the stories that we need in order to make good cost estimates is bound up in the data. You cannot separate good cost estimating from a knowledge of the historical data. One final thought. It is our attempts to make sense out of the randomness that leads us astray. In order to make progress as cost modelers and cost estimators, we must accept that there are real limitations on our ability to model the past and predict the future. I do not believe we should throw up our hands and say this is the best we can do. Rather, to see real improvement we must first recognize these limitations, avoid the easy but misleading solutions, and seek to find ways to better model the world we live in. I don't have any simple solutions. Perhaps the answers lie in better data or in a totally different approach to simulating how the world works. All I know is that we must do our best to speak truth to ourselves and our customers. Misleading ourselves and our customers will, in the end, result in an inability to have a positive impact on those we serve.
Effects of mergers on non-parametric morphologies
NASA Astrophysics Data System (ADS)
Bignone, Lucas A.; Tissera, Patricia B.; Sillero, Emanuel; Pedrosa, Susana E.; Pellizza, Leonardo J.; Lambas, Diego G.
2017-06-01
We study the effects of mergers on non-parametric morphologies of galaxies. We compute the Gini index, M20, asymmetry and concentration statistics for z = 0 galaxies in the Illustris simulation and compare non-parametric morphologies of major mergers, minor merges, close pairs, distant pairs and unperturbed galaxies. We determine the effectiveness of observational methods based on these statistics to select merging galaxies.
Parametric resonance in tunable superconducting cavities
NASA Astrophysics Data System (ADS)
Wustmann, Waltraut; Shumeiko, Vitaly
2013-05-01
We develop a theory of parametric resonance in tunable superconducting cavities. The nonlinearity introduced by the superconducting quantum interference device (SQUID) attached to the cavity and damping due to connection of the cavity to a transmission line are taken into consideration. We study in detail the nonlinear classical dynamics of the cavity field below and above the parametric threshold for the degenerate parametric resonance, featuring regimes of multistability and parametric radiation. We investigate the phase-sensitive amplification of external signals on resonance, as well as amplification of detuned signals, and relate the amplifier performance to that of linear parametric amplifiers. We also discuss applications of the device for dispersive qubit readout. Beyond the classical response of the cavity, we investigate small quantum fluctuations around the amplified classical signals. We evaluate the noise power spectrum both for the internal field in the cavity and the output field. Other quantum-statistical properties of the noise are addressed such as squeezing spectra, second-order coherence, and two-mode entanglement.
Plodinec, M.J.
1998-11-20
After being filled with glass, DWPF canistered waste forms will be welded closed using an upset resistance welding process. This final closure weld must be leaktight, and must remain so during extended storage at SRS. As part of the DWPF Startup Test Program, a parametric study (DWPF-WP-24) has been performed to determine a range of welder operating parameters which will produce acceptable welds. The parametric window of acceptable welds defined by this study is 90,000 + 15,000 lb of force, 248,000 + 22,000 amps of current, and 95 + 15 cycles* for the time of application of the current.
Eberhard, B.J.; Harbour, J.R.; Plodinec, M.J.
1994-06-01
As part of the DWPF Startup Test Program, a parametric study has been performed to determine a range of welder operating parameters which will produce acceptable final welds for canistered waste forms. The parametric window of acceptable welds defined by this study is 90,000 {plus_minus} 15,000 lb of force, 248,000 {plus_minus} 22,000 amps of current, and 95 {plus_minus} 15 cycles (@ 60 cops) for the time of application of the current.
Parametric Rietveld refinement
Stinton, Graham W.; Evans, John S. O.
2007-01-01
In this paper the method of parametric Rietveld refinement is described, in which an ensemble of diffraction data collected as a function of time, temperature, pressure or any other variable are fitted to a single evolving structural model. Parametric refinement offers a number of potential benefits over independent or sequential analysis. It can lead to higher precision of refined parameters, offers the possibility of applying physically realistic models during data analysis, allows the refinement of ‘non-crystallographic’ quantities such as temperature or rate constants directly from diffraction data, and can help avoid false minima. PMID:19461841
Parametric Differentiation and Integration
ERIC Educational Resources Information Center
Chen, Hongwei
2009-01-01
Parametric differentiation and integration under the integral sign constitutes a powerful technique for calculating integrals. However, this topic is generally not included in the undergraduate mathematics curriculum. In this note, we give a comprehensive review of this approach, and show how it can be systematically used to evaluate most of the…
Parametric Interpretation in Yorktalk.
ERIC Educational Resources Information Center
Ogden, Richard
The method of parametric interpretation used in the computer program "Yorktalk," software that creates synthetic parameter files from phonological representations of speech, is explained. First, the design of the program is described, and the concept of "exponency" in prosodic analysis is explained as it is applied in the…
Parametric Differentiation and Integration
ERIC Educational Resources Information Center
Chen, Hongwei
2009-01-01
Parametric differentiation and integration under the integral sign constitutes a powerful technique for calculating integrals. However, this topic is generally not included in the undergraduate mathematics curriculum. In this note, we give a comprehensive review of this approach, and show how it can be systematically used to evaluate most of the…
Computation of Parametric Adaptive Fuzzy Controller for Wood Drying System
NASA Astrophysics Data System (ADS)
Situmorang, Zakarias; Wardoyo, Retantyo; Hartati, Sri; Istiyanto, Jazi Eko
2009-08-01
The paper reports the computation of parametric adaptive fuzzy controller for used to wood drying system. Parametric of adaptive fuzzy controller is control period system. Control period system is how long time need to hoist of temperature drying or humidity drying if the actuator in on-conditions. The parametric is implemented for control system of wood drying process at prototype chamber with solar is source of energy. The actuator of system is heater, damper and sprayer. From result of measurement, that data were doing to analysis statistic to have the parametric. Whenever the parametric want to implemented with mechanism adaptive. Membership Functions of variable control of system to became something is difficult to have effect to temperature and humidity drying. The result of implemented of adaptive fuzzy control is described in graphic typical. The control system is able to adapt change of humidity drying in system schedule of wood drying system.
Heat Transfer Parametric System Identification
1993-06-01
Transfer Parametric System Identification 6. AUTHOR(S Parker, Gregory K. 7. PERFORMING ORGANIZATION NAME(S) AND AOORESS(ES) 8. PERFORMING ORGANIZATION...distribution is unlimited. Heat Transfer Parametric System Identification by Gregory K. Parker Lieutenant, United States Navy BS., DeVry Institute of...Modeling Concept ........ ........... 3 2. Lumped Parameter Approach ...... ......... 4 3. Parametric System Identification ....... 4 B. BASIC MODELING
NASA Astrophysics Data System (ADS)
Khan, Shahjahan
Often scientific information on various data generating processes are presented in the from of numerical and categorical data. Except for some very rare occasions, generally such data represent a small part of the population, or selected outcomes of any data generating process. Although, valuable and useful information is lurking in the array of scientific data, generally, they are unavailable to the users. Appropriate statistical methods are essential to reveal the hidden "jewels" in the mess of the row data. Exploratory data analysis methods are used to uncover such valuable characteristics of the observed data. Statistical inference provides techniques to make valid conclusions about the unknown characteristics or parameters of the population from which scientifically drawn sample data are selected. Usually, statistical inference includes estimation of population parameters as well as performing test of hypotheses on the parameters. However, prediction of future responses and determining the prediction distributions are also part of statistical inference. Both Classical or Frequentists and Bayesian approaches are used in statistical inference. The commonly used Classical approach is based on the sample data alone. In contrast, increasingly popular Beyesian approach uses prior distribution on the parameters along with the sample data to make inferences. The non-parametric and robust methods are also being used in situations where commonly used model assumptions are unsupported. In this chapter,we cover the philosophical andmethodological aspects of both the Classical and Bayesian approaches.Moreover, some aspects of predictive inference are also included. In the absence of any evidence to support assumptions regarding the distribution of the underlying population, or if the variable is measured only in ordinal scale, non-parametric methods are used. Robust methods are employed to avoid any significant changes in the results due to deviations from the model
NASA Astrophysics Data System (ADS)
Khan, Shahjahan
Often scientific information on various data generating processes are presented in the from of numerical and categorical data. Except for some very rare occasions, generally such data represent a small part of the population, or selected outcomes of any data generating process. Although, valuable and useful information is lurking in the array of scientific data, generally, they are unavailable to the users. Appropriate statistical methods are essential to reveal the hidden “jewels” in the mess of the row data. Exploratory data analysis methods are used to uncover such valuable characteristics of the observed data. Statistical inference provides techniques to make valid conclusions about the unknown characteristics or parameters of the population from which scientifically drawn sample data are selected. Usually, statistical inference includes estimation of population parameters as well as performing test of hypotheses on the parameters. However, prediction of future responses and determining the prediction distributions are also part of statistical inference. Both Classical or Frequentists and Bayesian approaches are used in statistical inference. The commonly used Classical approach is based on the sample data alone. In contrast, increasingly popular Beyesian approach uses prior distribution on the parameters along with the sample data to make inferences. The non-parametric and robust methods are also being used in situations where commonly used model assumptions are unsupported. In this chapter,we cover the philosophical andmethodological aspects of both the Classical and Bayesian approaches.Moreover, some aspects of predictive inference are also included. In the absence of any evidence to support assumptions regarding the distribution of the underlying population, or if the variable is measured only in ordinal scale, non-parametric methods are used. Robust methods are employed to avoid any significant changes in the results due to deviations from the model
Microprocessors as an Adjunct to Statistics Instruction.
ERIC Educational Resources Information Center
Miller, William G.
Examinations of costs and acquisition of facilities indicate that an Altair 8800A microcomputer with a program library of parametric, non-parametric, mathematical, and teaching programs can be used effectively for teaching college-level statistics. Statistical packages presently in use require extensive computing knowledge beyond the students' and…
Chalcogenide optical parametric oscillator.
Ahmad, Raja; Rochette, Martin
2012-04-23
We demonstrate the first optical parametric oscillator (OPO) based on chalcogenide glass. The parametric gain medium is an As(2)Se(3) chalcogenide microwire coated with a layer of polymer. The doubly-resonant OPO oscillates simultaneously at a Stokes and an anti Stokes wavelength shift of >50 nm from the pump wavelength that lies at λ(P) = 1,552 nm. The oscillator has a peak power threshold of 21.6 dBm and a conversion efficiency of >19%. This OPO experiment provides an additional application of the chalcogenide microwire technology; and considering the transparency of As(2)Se(3) glass extending far in the mid-infrared (mid-IR) wavelengths, the device holds promise for realizing mid-IR OPOs utilizing existing optical sources in the telecommunications wavelength region.
Parametric Explosion Spectral Model
Ford, S R; Walter, W R
2012-01-19
Small underground nuclear explosions need to be confidently detected, identified, and characterized in regions of the world where they have never before occurred. We develop a parametric model of the nuclear explosion seismic source spectrum derived from regional phases that is compatible with earthquake-based geometrical spreading and attenuation. Earthquake spectra are fit with a generalized version of the Brune spectrum, which is a three-parameter model that describes the long-period level, corner-frequency, and spectral slope at high-frequencies. Explosion spectra can be fit with similar spectral models whose parameters are then correlated with near-source geology and containment conditions. We observe a correlation of high gas-porosity (low-strength) with increased spectral slope. The relationship between the parametric equations and the geologic and containment conditions will assist in our physical understanding of the nuclear explosion source.
NASA Astrophysics Data System (ADS)
Kakadiaris, Ioannis A.; Konstantinidis, Ioannis; Papadakis, Manos; Ding, Wei; Shen, Lixin
2005-08-01
Three dimensional (3D) surfaces can be sampled parametrically in the form of range image data. Smoothing/denoising of such raw data is usually accomplished by adapting techniques developed for intensity image processing, since both range and intensity images comprise parametrically sampled geometry and appearance measurements, respectively. We present a transform-based algorithm for surface denoising, motivated by our previous work on intensity image denoising, which utilizes a non-separable Parseval frame and an ensemble thresholding scheme. The frame is constructed from separable (tensor) products of a piecewise linear spline tight frame and incorporates the weighted average operator and the Sobel operators in directions that are integer multiples of 45°. We compare the performance of this algorithm with other transform-based methods from the recent literature. Our results indicate that such transform methods are suited to the task of smoothing range images.
A general framework for parametric survival analysis.
Crowther, Michael J; Lambert, Paul C
2014-12-30
Parametric survival models are being increasingly used as an alternative to the Cox model in biomedical research. Through direct modelling of the baseline hazard function, we can gain greater understanding of the risk profile of patients over time, obtaining absolute measures of risk. Commonly used parametric survival models, such as the Weibull, make restrictive assumptions of the baseline hazard function, such as monotonicity, which is often violated in clinical datasets. In this article, we extend the general framework of parametric survival models proposed by Crowther and Lambert (Journal of Statistical Software 53:12, 2013), to incorporate relative survival, and robust and cluster robust standard errors. We describe the general framework through three applications to clinical datasets, in particular, illustrating the use of restricted cubic splines, modelled on the log hazard scale, to provide a highly flexible survival modelling framework. Through the use of restricted cubic splines, we can derive the cumulative hazard function analytically beyond the boundary knots, resulting in a combined analytic/numerical approach, which substantially improves the estimation process compared with only using numerical integration. User-friendly Stata software is provided, which significantly extends parametric survival models available in standard software. Copyright © 2014 John Wiley & Sons, Ltd.
NASA Technical Reports Server (NTRS)
Rosu, Grigore (Inventor); Chen, Feng (Inventor); Chen, Guo-fang; Wu, Yamei; Meredith, Patrick O. (Inventor)
2014-01-01
A program trace is obtained and events of the program trace are traversed. For each event identified in traversing the program trace, a trace slice of which the identified event is a part is identified based on the parameter instance of the identified event. For each trace slice of which the identified event is a part, the identified event is added to an end of a record of the trace slice. These parametric trace slices can be used in a variety of different manners, such as for monitoring, mining, and predicting.
Multicast Parametric Synchronous Sampling
2011-09-01
28, No. 23, pp. 3478-3487 (2010). [7] S. Moro, E. Myslivets, J.R. Windmiller, N. Alic, J.M. Chavez Boggio , S. Radic “Synthesis of Equalized...Broadband Parametric Gain by Localized Dispersion Mapping” IEEE Photonics Technology Letters, Vol. 20, No. 23, pp. 1971 – 1973 (2008). [8] J.C. Boggio , S...21 No. 10, pp. 612-614 (2009). [9] C.S. Bres, J.M. Chavez- Boggio , N. Alic, S. Radic, “1-to-40 10-Gb/s Channel Multicasting and Amplification in
Optical parametric loop mirror
NASA Astrophysics Data System (ADS)
Mori, K.; Morioka, T.; Saruwatari, M.
1995-06-01
A novel configuration for four-wave mixing (FWM) is proposed that offers the remarkable feature of inherently separating the FWM wave from the input pump and signal waves and suppressing their background amplified stimulated emission without optical filtering. In the proposed configuration, an optical parametric loop mirror, two counterpropagating FWM waves generated in a Sagnac interferometer interfere with a relative phase difference that is introduced deliberately. FWM frequency-conversion experiments in a polarization-maintaining fiber achieved more than 35 dB of input-wave suppression against the FWM wave.
Progress in optical parametric oscillators
NASA Technical Reports Server (NTRS)
Fan, Y. X.; Byer, R. L.
1984-01-01
It is pointed out that tunable coherent sources are very useful for many applications, including spectroscopy, chemistry, combustion diagnostics, and remote sensing. Compared with other tunable sources, optical parametric oscillators (OPO) offer the potential advantage of a wide wavelength operating range, which extends from 0.2 micron to 25 microns. The current status of OPO is examined, taking into account mainly advances made during the last decade. Attention is given to early LiNbO3 parametric oscillators, problems which have prevented wide use of parametric oscillators, the demonstration of OPO's using urea and AgGaS2, progress related to picosecond OPO's, a breakthrough in nanosecond parametric oscillators, the first demonstration of a waveguide and fiber parametric amplification and generation, the importance of chalcopyrite crystals, and theoretical work performed with the aim to understand the factors affecting the parametric oscillator performance.
Wey, Andrew; Connett, John; Rudser, Kyle
2015-07-01
For estimating conditional survival functions, non-parametric estimators can be preferred to parametric and semi-parametric estimators due to relaxed assumptions that enable robust estimation. Yet, even when misspecified, parametric and semi-parametric estimators can possess better operating characteristics in small sample sizes due to smaller variance than non-parametric estimators. Fundamentally, this is a bias-variance trade-off situation in that the sample size is not large enough to take advantage of the low bias of non-parametric estimation. Stacked survival models estimate an optimally weighted combination of models that can span parametric, semi-parametric, and non-parametric models by minimizing prediction error. An extensive simulation study demonstrates that stacked survival models consistently perform well across a wide range of scenarios by adaptively balancing the strengths and weaknesses of individual candidate survival models. In addition, stacked survival models perform as well as or better than the model selected through cross-validation. Finally, stacked survival models are applied to a well-known German breast cancer study.
ERIC Educational Resources Information Center
Osler, James Edward
2014-01-01
This monograph provides an epistemological rational for the design of a novel post hoc statistical measure called "Tri-Center Analysis". This new statistic is designed to analyze the post hoc outcomes of the Tri-Squared Test. In Tri-Center Analysis trichotomous parametric inferential parametric statistical measures are calculated from…
Monolithic optical parametric oscillators
NASA Astrophysics Data System (ADS)
Breunig, Ingo; Beckmann, Tobias; Buse, Karsten
2012-02-01
Stability and footprint of optical parametric oscillators (OPOs) strongly depend on the cavity used. Monolithic OPOs tend to be most stable and compact since they do not require external mirrors that have to be aligned. The most straightforward way to get rid of the mirrors is to coat the end faces of the nonlinear crystal. Whispering gallery resonators (WGRs) are a more advanced solution since they provide ultra-high reflectivity over a wide spectral range without any coating. Furthermore, they can be fabricated out of nonlinear-optical materials like lithium niobate. Thus, they are ideally suited to serve as a monolithic OPO cavity. We present the experimental realization of optical parametric oscillators based on whispering gallery resonators. Pumped at 1 μm wavelength, they generate signal and idler fields tunable between 1.8 and 2.5 μm wavelength. We explore different schemes, how to phase match the nonlinear interaction in a WGR. In particular, we show improvements in the fabrication of quasi-phase-matching structures. They enable great flexibility for the tuning and for the choice of the pump laser.
Signal-to-noise ratio in parametrically driven oscillators.
Batista, Adriano A; Moreira, Raoni S N
2011-12-01
We report a theoretical model based on Green's functions and averaging techniques that gives analytical estimates to the signal-to-noise ratio (SNR) near the first parametric instability zone in parametrically driven oscillators in the presence of added ac drive and added thermal noise. The signal term is given by the response of the parametrically driven oscillator to the added ac drive, while the noise term has two different measures: one is dc and the other is ac. The dc measure of noise is given by a time average of the statistically averaged fluctuations of the displacement from equilibrium in the parametric oscillator due to thermal noise. The ac measure of noise is given by the amplitude of the statistically averaged fluctuations at the frequency of the parametric pump. We observe a strong dependence of the SNR on the phase between the external drive and the parametric pump. For some range of the phase there is a high SNR, while for other values of phase the SNR remains flat or decreases with increasing pump amplitude. Very good agreement between analytical estimates and numerical results is achieved.
NASA Astrophysics Data System (ADS)
Acomi, Nicoleta; Ancuţa, Cristian; Andrei, Cristian; Boştinǎ, Alina; Boştinǎ, Aurel
2016-12-01
Ships are mainly built to sail and transport cargo at sea. Environmental conditions and state of the sea are communicated to vessels through periodic weather forecasts. Despite officers being aware of the sea state, their sea time experience is a decisive factor when the vessel encounters severe environmental conditions. Another important factor is the loading condition of the vessel, which triggers different behaviour in similar marine environmental conditions. This paper aims to analyse the behaviour of a port container vessel in severe environmental conditions and to estimate the potential conditions of parametric roll resonance. Octopus software simulation is employed to simulate vessel motions under certain conditions of the sea, with possibility to analyse the behaviour of ships and the impact of high waves on ships due to specific wave encounter situations. The study should be regarded as a supporting tool during the decision making process.
Ebrahimzadeh, M
2003-12-15
Since its invention more than 40 years ago, the laser has become an indispensable optical tool, capable of transforming light from its naturally incoherent state to a highly coherent state in space and time. Yet, due to fundamental limitations, operation of the laser remains confined to restricted spectral and temporal regions. Nonlinear optics can overcome this limitation by allowing access to new spectral and temporal regimes through the exploitation of suitable dielectric materials in combination with the laser. In particular, optical parametric oscillators are versatile coherent light sources with unique flexibility that can provide optical radiation across an entire spectral range from the ultraviolet to the far-infrared and over all temporal scales from continuous wave to the ultrafast femtosecond domain.
Parametric lattice Boltzmann method
NASA Astrophysics Data System (ADS)
Shim, Jae Wan
2017-06-01
The discretized equilibrium distributions of the lattice Boltzmann method are presented by using the coefficients of the Lagrange interpolating polynomials that pass through the points related to discrete velocities and using moments of the Maxwell-Boltzmann distribution. The ranges of flow velocity and temperature providing positive valued distributions vary with regulating discrete velocities as parameters. New isothermal and thermal compressible models are proposed for flows of the level of the isothermal and thermal compressible Navier-Stokes equations. Thermal compressible shock tube flows are simulated by only five on-lattice discrete velocities. Two-dimensional isothermal and thermal vortices provoked by the Kelvin-Helmholtz instability are simulated by the parametric models.
Nanoscale electromechanical parametric amplifier
Aleman, Benjamin Jose; Zettl, Alexander
2016-09-20
This disclosure provides systems, methods, and apparatus related to a parametric amplifier. In one aspect, a device includes an electron source electrode, a counter electrode, and a pumping electrode. The electron source electrode may include a conductive base and a flexible conductor. The flexible conductor may have a first end and a second end, with the second end of the flexible conductor being coupled to the conductive base. A cross-sectional dimension of the flexible conductor may be less than about 100 nanometers. The counter electrode may be disposed proximate the first end of the flexible conductor and spaced a first distance from the first end of the flexible conductor. The pumping electrode may be disposed proximate a length of the flexible conductor and spaced a second distance from the flexible conductor.
Mechanical Parametric Oscillations and Waves
ERIC Educational Resources Information Center
Dittrich, William; Minkin, Leonid; Shapovalov, Alexander S.
2013-01-01
Usually parametric oscillations are not the topic of general physics courses. Probably it is because the mathematical theory of this phenomenon is relatively complicated, and until quite recently laboratory experiments for students were difficult to implement. However parametric oscillations are good illustrations of the laws of physics and can be…
Mechanical Parametric Oscillations and Waves
ERIC Educational Resources Information Center
Dittrich, William; Minkin, Leonid; Shapovalov, Alexander S.
2013-01-01
Usually parametric oscillations are not the topic of general physics courses. Probably it is because the mathematical theory of this phenomenon is relatively complicated, and until quite recently laboratory experiments for students were difficult to implement. However parametric oscillations are good illustrations of the laws of physics and can be…
NASA Technical Reports Server (NTRS)
Bokhari, Shahid H.; Crockett, Thomas W.; Nicol, David M.
1993-01-01
Binary dissection is widely used to partition non-uniform domains over parallel computers. This algorithm does not consider the perimeter, surface area, or aspect ratio of the regions being generated and can yield decompositions that have poor communication to computation ratio. Parametric Binary Dissection (PBD) is a new algorithm in which each cut is chosen to minimize load + lambda x(shape). In a 2 (or 3) dimensional problem, load is the amount of computation to be performed in a subregion and shape could refer to the perimeter (respectively surface) of that subregion. Shape is a measure of communication overhead and the parameter permits us to trade off load imbalance against communication overhead. When A is zero, the algorithm reduces to plain binary dissection. This algorithm can be used to partition graphs embedded in 2 or 3-d. Load is the number of nodes in a subregion, shape the number of edges that leave that subregion, and lambda the ratio of time to communicate over an edge to the time to compute at a node. An algorithm is presented that finds the depth d parametric dissection of an embedded graph with n vertices and e edges in O(max(n log n, de)) time, which is an improvement over the O(dn log n) time of plain binary dissection. Parallel versions of this algorithm are also presented; the best of these requires O((n/p) log(sup 3)p) time on a p processor hypercube, assuming graphs of bounded degree. How PBD is applied to 3-d unstructured meshes and yields partitions that are better than those obtained by plain dissection is described. Its application to the color image quantization problem is also discussed, in which samples in a high-resolution color space are mapped onto a lower resolution space in a way that minimizes the color error.
White-light parametric instabilities in plasmas.
Santos, J E; Silva, L O; Bingham, R
2007-06-08
Parametric instabilities driven by partially coherent radiation in plasmas are described by a generalized statistical Wigner-Moyal set of equations, formally equivalent to the full wave equation, coupled to the plasma fluid equations. A generalized dispersion relation for stimulated Raman scattering driven by a partially coherent pump field is derived, revealing a growth rate dependence, with the coherence width sigma of the radiation field, scaling with 1/sigma for backscattering (three-wave process), and with 1/sigma1/2 for direct forward scattering (four-wave process). Our results demonstrate the possibility to control the growth rates of these instabilities by properly using broadband pump radiation fields.
Ground-Based Telescope Parametric Cost Model
NASA Technical Reports Server (NTRS)
Stahl, H. Philip; Rowell, Ginger Holmes
2004-01-01
A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.
Vivancos, E; Healy, C; Mueller, F; Whalley, D
2001-05-09
Embedded systems often have real-time constraints. Traditional timing analysis statically determines the maximum execution time of a task or a program in a real-time system. These systems typically depend on the worst-case execution time of tasks in order to make static scheduling decisions so that tasks can meet their deadlines. Static determination of worst-case execution times imposes numerous restrictions on real-time programs, which include that the maximum number of iterations of each loop must be known statically. These restrictions can significantly limit the class of programs that would be suitable for a real-time embedded system. This paper describes work-in-progress that uses static timing analysis to aid in making dynamic scheduling decisions. For instance, different algorithms with varying levels of accuracy may be selected based on the algorithm's predicted worst-case execution time and the time allotted for the task. We represent the worst-case execution time of a function or a loop as a formula, where the unknown values affecting the execution time are parameterized. This parametric timing analysis produces formulas that can then be quickly evaluated at run-time so dynamic scheduling decisions can be made with little overhead. Benefits of this work include expanding the class of applications that can be used in a real-time system, improving the accuracy of dynamic scheduling decisions, and more effective utilization of system resources. This paper describes how static timing analysis can be used to aid in making dynamic scheduling decisions. The WCET of a function or a loop is represented as a formula, where the values affecting the execution time are parameterized. Such formulas can then be quickly evaluated at run-time so dynamic scheduling decisions can be made when scheduling a task or choosing algorithms within a task. Benefits of this parametric timing analysis include expanding the class of applications that can be used in a real-time system
NASA Astrophysics Data System (ADS)
Choi, Jongseong
The performance of a hypersonic flight vehicle will depend on existing materials and fuels; this work presents the performance of the ideal scramjet engine for three different combustion chamber materials and three different candidate fuels. Engine performance is explored by parametric cycle analysis for the ideal scramjet as a function of material maximum service temperature and the lower heating value of jet engine fuels. The thermodynamic analysis is based on the Brayton cycle as similarly employed in describing the performance of the ramjet, turbojet, and fanjet ideal engines. The objective of this work is to explore material operating temperatures and fuel possibilities for the combustion chamber of a scramjet propulsion system to show how they relate to scramjet performance and the seven scramjet engine parameters: specific thrust, fuel-to-air ratio, thrust-specific fuel consumption, thermal efficiency, propulsive efficiency, overall efficiency, and thrust flux. The information presented in this work has not been done by others in the scientific literature. This work yields simple algebraic equations for scramjet performance which are similar to that of the ideal ramjet, ideal turbojet and ideal turbofan engines.
Parametric Transformation Analysis
NASA Technical Reports Server (NTRS)
Gary, G. Allan
2003-01-01
Because twisted coronal features are important proxies for predicting solar eruptive events, and, yet not clearly understood, we present new results to resolve the complex, non-potential magnetic field configurations of active regions. This research uses free-form deformation mathematics to generate the associated coronal magnetic field. We use a parametric representation of the magnetic field lines such that the field lines can be manipulated to match the structure of EUV and SXR coronal loops. The objective is to derive sigmoidal magnetic field solutions which allows the beta greater than 1 regions to be included, aligned and non-aligned electric currents to be calculated, and the Lorentz force to be determined. The advantage of our technique is that the solution is independent of the unknown upper and side boundary conditions, allows non-vanishing magnetic forces, and provides a global magnetic field solution, which contains high- and low-beta regimes and is consistent with all the coronal images of the region. We show that the mathematical description is unique and physical.
Parametric Mass Reliability Study
NASA Technical Reports Server (NTRS)
Holt, James P.
2014-01-01
The International Space Station (ISS) systems are designed based upon having redundant systems with replaceable orbital replacement units (ORUs). These ORUs are designed to be swapped out fairly quickly, but some are very large, and some are made up of many components. When an ORU fails, it is replaced on orbit with a spare; the failed unit is sometimes returned to Earth to be serviced and re-launched. Such a system is not feasible for a 500+ day long-duration mission beyond low Earth orbit. The components that make up these ORUs have mixed reliabilities. Components that make up the most mass-such as computer housings, pump casings, and the silicon board of PCBs-typically are the most reliable. Meanwhile components that tend to fail the earliest-such as seals or gaskets-typically have a small mass. To better understand the problem, my project is to create a parametric model that relates both the mass of ORUs to reliability, as well as the mass of ORU subcomponents to reliability.
Parametric Equations, Maple, and Tubeplots.
ERIC Educational Resources Information Center
Feicht, Louis
1997-01-01
Presents an activity that establishes a graphical foundation for parametric equations by using a graphing output form called tubeplots from the computer program Maple. Provides a comprehensive review and exploration of many previously learned topics. (ASK)
Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models
ERIC Educational Resources Information Center
Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum
2011-01-01
Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…
Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models
ERIC Educational Resources Information Center
Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum
2011-01-01
Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…
Baker, C.
1994-10-01
The Department of Energy`s (DOE) Hanford site near Richland, Washington is being cleaned up after 50 years of nuclear materials production. One of the most serious problems at the site is the waste stored in single-shell underground storage tanks. There are 149 of these tanks containing the spent fuel residue remaining after the fuel is dissolved in acid and the desired materials (primarily plutonium and uranium) are separated out. The tanks are upright cylinders 75 ft. in diameter with domed tops. They are made of reinforced concrete, have steel liners, and each tank is buried under 7--12 ft. of overburden. The tanks are up to 40-ft. high, and have capacities of 500,000, 750,000, or 1,000,000 gallons of waste. As many as one-third of these tanks are known or suspected to leak. The waste form contained in the tanks varies in consistency from liquid supernatant to peanut-butter-like gels and sludges to hard salt cake (perhaps as hard as low-grade concrete). The current waste retrieval plan is to insert a large long-reach manipulator through a hole cut in the top of the tank, and use a variety of end-effectors to mobilize the waste and remove it from the tank. PNL has, with the assistance of Deneb robotics employees, developed a means of using the IGRIP code to perform parametric design of mechanical systems. This method requires no modifications to the IGRIP code, and all design data are stored in the IGRIP workcell. The method is presented in the context of development of a passive articulated mechanism that is used to deliver down-arm services to a gantry robot. The method is completely general, however, and could be used to design a fully articulated manipulator. Briefly, the method involves using IGCALC expressions to control manipulator joint angles, and IGCALC variables to allow user control of link lengths and offsets. This paper presents the method in detail, with examples drawn from PNL`s experience with the gantry robot service-providing mechanism.
Rephasing invariant parametrization of flavor mixing
NASA Astrophysics Data System (ADS)
Lee, Tae-Hun
A new rephasing invariant parametrization for the 3 x 3 CKM matrix, called (x, y) parametrization, is introduced and the properties and applications of the parametrization are discussed. The overall phase condition leads this parametrization to have only six rephsing invariant parameters and two constraints. Its simplicity and regularity become apparent when it is applied to the one-loop RGE (renormalization group equations) for the Yukawa couplings. The implications of this parametrization for unification of the Yukawa couplings are also explored.
Parametric Resonance for Material Characterization
NASA Astrophysics Data System (ADS)
Adler, Laszlo; Rokhlin, Stanislav I.
2009-03-01
While studying finite amplitude ultrasonic wave resonance in a one dimensional liquid filled cavity, formed by a narrow band transducer and a plane reflector, fractional harmonics of the driver's frequency were observed in addition to the expected high harmonics. Subsequently it was realized that the system was one of the many examples where parametric resonance takes place and the observed fractional harmonics are parametrically generated. Parametric resonance occurs in any physical system which has a periodically modulated natural frequency. The generation mechanism also requires a sufficiently high threshold value of the driving amplitude and the system becomes nonlinear. Further increase of the driving amplitude above the threshold produces additional fractional harmonics and at a certain value an almost continuous spectrum is produced and the phenomenon becomes chaotic. Our recently developed frequency modulated angle beam ultrasonic method for adhesive bond evaluation is an additional example of the use of a resonance parametric system. The acoustic resonator is formed by an adhesive layer with the resonance frequency affected by the bond quality between the adhesive and the substrates. In this case the interfacial stresses (due to an external low frequency excitation) may or may not produce parametric shift of the resonance depending on the quality of the interfacial bond.
Parametric functional principal component analysis.
Sang, Peijun; Wang, Liangliang; Cao, Jiguo
2017-09-01
Functional principal component analysis (FPCA) is a popular approach in functional data analysis to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs). Most existing FPCA approaches use a set of flexible basis functions such as B-spline basis to represent the FPCs, and control the smoothness of the FPCs by adding roughness penalties. However, the flexible representations pose difficulties for users to understand and interpret the FPCs. In this article, we consider a variety of applications of FPCA and find that, in many situations, the shapes of top FPCs are simple enough to be approximated using simple parametric functions. We propose a parametric approach to estimate the top FPCs to enhance their interpretability for users. Our parametric approach can also circumvent the smoothing parameter selecting process in conventional nonparametric FPCA methods. In addition, our simulation study shows that the proposed parametric FPCA is more robust when outlier curves exist. The parametric FPCA method is demonstrated by analyzing several datasets from a variety of applications. © 2017, The International Biometric Society.
A Stochastic Parametrization of Ocean Mesoscale Eddies (Invited)
NASA Astrophysics Data System (ADS)
Zanna, L.; Mana, L.
2013-12-01
The ocean contains a vigorous mesoscale eddy field important in establishing the ocean's circulation and tracer properties. Mesoscale eddies have spatial scales of approximately 10 to 100km and their effect needs to be parametrized in ocean climate models. Current deterministic parametrizations of mesoscale eddies do not, for example, account for the fluctuations in sub-grid transport or do not represent upscale turbulent cascades therefore leading to model error in the representation of present and future climate change. The goal of our study is to construct a stochastic parametrization of ocean mesoscale eddies in order to include such effects and account for model error associated with the uncertainty in the parameters and the parametrization. The parametrization is constructed by using the output of a high resolution model in order to derive the statistics of the eddy source term as function of the resolved (coarse) scales. The simulations are done in a quasi-geostrophic model in a double-gyre configuration to provide a tractable framework. Probability density functions (PDFs) of the eddy source term conditional on the intrinsic resolved large scale dynamics are calculated and therefore capture the fluctuations associated with mesoscale eddies and their impact on the mean flow. The conditional PDFs are based on a Rivlin-Ericksen tensor and a theory for their mean, standard deviation, skewness and kurtosis is provided as function of the coarse resolution model grid size, its forcing and stratification. The conditional PDFs are then implemented as the basis for a new parametrization of mesoscale eddies in a coarse resolution model. The results of the implementation of the stochastic parametrization are shown to improve the representation of the mean flow, its variability at most frequencies and the kinetic energy power spectrum as function of wavelength.
Comparison of thawing and freezing dark energy parametrizations
NASA Astrophysics Data System (ADS)
Pantazis, G.; Nesseris, S.; Perivolaropoulos, L.
2016-05-01
Dark energy equation of state w (z ) parametrizations with two parameters and given monotonicity are generically either convex or concave functions. This makes them suitable for fitting either freezing or thawing quintessence models but not both simultaneously. Fitting a data set based on a freezing model with an unsuitable (concave when increasing) w (z ) parametrization [like Chevallier-Polarski-Linder (CPL)] can lead to significant misleading features like crossing of the phantom divide line, incorrect w (z =0 ), incorrect slope, etc., that are not present in the underlying cosmological model. To demonstrate this fact we generate scattered cosmological data at both the level of w (z ) and the luminosity distance DL(z ) based on either thawing or freezing quintessence models and fit them using parametrizations of convex and of concave type. We then compare statistically significant features of the best fit w (z ) with actual features of the underlying model. We thus verify that the use of unsuitable parametrizations can lead to misleading conclusions. In order to avoid these problems it is important to either use both convex and concave parametrizations and select the one with the best χ2 or use principal component analysis thus splitting the redshift range into independent bins. In the latter case, however, significant information about the slope of w (z ) at high redshifts is lost. Finally, we propose a new family of parametrizations w (z )=w0+wa(z/1 +z )n which generalizes the CPL and interpolates between thawing and freezing parametrizations as the parameter n increases to values larger than 1.
Parametric study of statistical bias in laser Doppler velocimetry
NASA Technical Reports Server (NTRS)
Gould, Richard D.; Stevenson, Warren H.; Thompson, H. Doyle
1989-01-01
Analytical studies have often assumed that LDV velocity bias depends on turbulence intensity in conjunction with one or more characteristic time scales, such as the time between validated signals, the time between data samples, and the integral turbulence time-scale. These parameters are presently varied independently, in an effort to quantify the biasing effect. Neither of the post facto correction methods employed is entirely accurate. The mean velocity bias error is found to be nearly independent of data validation rate.
Further Research into a Non-Parametric Statistical Screening System.
1979-12-14
Goldstein and Dillon (1977) present an example that demon- strates the inappropriateness of the LDF for qualitative variables: L0 if birth weight is low...Let X = V if birth weight is high X2 = 0 if gestation length is short V2 if gestation length is long Normal babies have high birth weight and long...gestation length or low birth weight and short gestation length. Abnormal babies have either of the other two combinations ((0, 1) or (1, 0)). The LDF
Markovian Dynamics of Josephson Parametric Amplification
NASA Astrophysics Data System (ADS)
Kaiser, Waldemar; Haider, Michael; Russer, Johannes A.; Russer, Peter; Jirauschek, Christian
2017-09-01
In this work, we derive the dynamics of the lossy DC pumped non-degenerate Josephson parametric amplifier (DCPJPA). The main element in a DCPJPA is the superconducting Josephson junction. The DC bias generates the AC Josephson current varying the nonlinear inductance of the junction. By this way the Josephson junction acts as the pump oscillator as well as the time varying reactance of the parametric amplifier. In quantum-limited amplification, losses and noise have an increased impact on the characteristics of an amplifier. We outline the classical model of the lossy DCPJPA and derive the available noise power spectral densities. A classical treatment is not capable of including properties like spontaneous emission which is mandatory in case of amplification at the quantum limit. Thus, we derive a quantum mechanical model of the lossy DCPJPA. Thermal losses are modeled by the quantum Langevin approach, by coupling the quantized system to a photon heat bath in thermodynamic equilibrium. The mode occupation in the bath follows the Bose-Einstein statistics. Based on the second quantization formalism, we derive the Heisenberg equations of motion of both resonator modes. We assume the dynamics of the system to follow the Markovian approximation, i.e. the system only depends on its actual state and is memory-free. We explicitly compute the time evolution of the contributions to the signal mode energy and give numeric examples based on different damping and coupling constants. Our analytic results show, that this model is capable of including thermal noise into the description of the DC pumped non-degenerate Josephson parametric amplifier.
Parametric infrared tunable laser system
NASA Technical Reports Server (NTRS)
Garbuny, M.; Henningsen, T.; Sutter, J. R.
1980-01-01
A parametric tunable infrared laser system was built to serve as transmitter for the remote detection and density measurement of pollutant, poisonous, or trace gases in the atmosphere. The system operates with a YAG:Nd laser oscillator amplifier chain which pumps a parametric tunable frequency converter. The completed system produced pulse energies of up to 30 mJ. The output is tunable from 1.5 to 3.6 micrometers at linewidths of 0.2-0.5 /cm (FWHM), although the limits of the tuning range and the narrower line crystals presently in the parametric converter by samples of the higher quality already demonstrated is expected to improve the system performance further.
Polarization mixing optical parametric oscillator.
Pearl, Shaul; Smith, Arlee Virgil; Arie, Ady; Blau, Pinhas; Kalmani, Gal
2005-05-01
We report the experimental realization of a new type of optical parametric oscillator in which oscillation is achieved by polarization rotation in a linear retarder, followed by nonlinear polarization mixing. The mixing is performed by a type II degenerate parametric downconversion in a periodically poled KTP crystal pumped by a 1064 nm pulsed Nd:YAG pump. A single, linearly polarized beam, precisely at the degenerate wavelength is generated. The output spectrum has a narrow linewidth (below the instrumentation bandwidth of 1 nm) and is highly stable with respect to variations in the crystal temperature.
Graphical functions in parametric space
NASA Astrophysics Data System (ADS)
Golz, Marcel; Panzer, Erik; Schnetz, Oliver
2016-12-01
Graphical functions are positive functions on the punctured complex plane Csetminus {0,1} which arise in quantum field theory. We generalize a parametric integral representation for graphical functions due to Lam, Lebrun and Nakanishi, which implies the real analyticity of graphical functions. Moreover, we prove a formula that relates graphical functions of planar dual graphs.
Parametric modeling of quantile regression coefficient functions.
Frumento, Paolo; Bottai, Matteo
2016-03-01
Estimating the conditional quantiles of outcome variables of interest is frequent in many research areas, and quantile regression is foremost among the utilized methods. The coefficients of a quantile regression model depend on the order of the quantile being estimated. For example, the coefficients for the median are generally different from those of the 10th centile. In this article, we describe an approach to modeling the regression coefficients as parametric functions of the order of the quantile. This approach may have advantages in terms of parsimony, efficiency, and may expand the potential of statistical modeling. Goodness-of-fit measures and testing procedures are discussed, and the results of a simulation study are presented. We apply the method to analyze the data that motivated this work. The described method is implemented in the qrcm R package.
Large-scale parametric survival analysis.
Mittal, Sushil; Madigan, David; Cheng, Jerry Q; Burd, Randall S
2013-10-15
Survival analysis has been a topic of active statistical research in the past few decades with applications spread across several areas. Traditional applications usually consider data with only a small numbers of predictors with a few hundreds or thousands of observations. Recent advances in data acquisition techniques and computation power have led to considerable interest in analyzing very-high-dimensional data where the number of predictor variables and the number of observations range between 10(4) and 10(6). In this paper, we present a tool for performing large-scale regularized parametric survival analysis using a variant of the cyclic coordinate descent method. Through our experiments on two real data sets, we show that application of regularized models to high-dimensional data avoids overfitting and can provide improved predictive performance and calibration over corresponding low-dimensional models.
Large-Scale Parametric Survival Analysis†
Mittal, Sushil; Madigan, David; Cheng, Jerry; Burd, Randall S.
2013-01-01
Survival analysis has been a topic of active statistical research in the past few decades with applications spread across several areas. Traditional applications usually consider data with only small numbers of predictors with a few hundreds or thousands of observations. Recent advances in data acquisition techniques and computation power has led to considerable interest in analyzing very high-dimensional data where the number of predictor variables and the number of observations range between 104 – 106. In this paper, we present a tool for performing large-scale regularized parametric survival analysis using a variant of cyclic coordinate descent method. Through our experiments on two real data sets, we show that application of regularized models to high-dimensional data avoids overfitting and can provide improved predictive performance and calibration over corresponding low-dimensional models. PMID:23625862
Parametric Identification of Systems Via Linear Operators.
1978-09-01
A general parametric identification /approximation model is developed for the black box identification of linear time invariant systems in terms of... parametric identification techniques derive from the general model as special cases associated with a particular linear operator. Some possible
Parametric Model Checking with VerICS
NASA Astrophysics Data System (ADS)
Knapik, Michał; Niewiadomski, Artur; Penczek, Wojciech; Półrola, Agata; Szreter, Maciej; Zbrzezny, Andrzej
The paper presents the verification system verICS, extended with the three new modules aimed at parametric verification of Elementary Net Systems, Distributed Time Petri Nets, and a subset of UML. All the modules exploit Bounded Model Checking for verifying parametric reachability and the properties specified in the logic PRTECTL - the parametric extension of the existential fragment of CTL.
Small-window parametric imaging based on information entropy for ultrasound tissue characterization
Tsui, Po-Hsiang; Chen, Chin-Kuo; Kuo, Wen-Hung; Chang, King-Jen; Fang, Jui; Ma, Hsiang-Yang; Chou, Dean
2017-01-01
Constructing ultrasound statistical parametric images by using a sliding window is a widely adopted strategy for characterizing tissues. Deficiency in spatial resolution, the appearance of boundary artifacts, and the prerequisite data distribution limit the practicability of statistical parametric imaging. In this study, small-window entropy parametric imaging was proposed to overcome the above problems. Simulations and measurements of phantoms were executed to acquire backscattered radiofrequency (RF) signals, which were processed to explore the feasibility of small-window entropy imaging in detecting scatterer properties. To validate the ability of entropy imaging in tissue characterization, measurements of benign and malignant breast tumors were conducted (n = 63) to compare performances of conventional statistical parametric (based on Nakagami distribution) and entropy imaging by the receiver operating characteristic (ROC) curve analysis. The simulation and phantom results revealed that entropy images constructed using a small sliding window (side length = 1 pulse length) adequately describe changes in scatterer properties. The area under the ROC for using small-window entropy imaging to classify tumors was 0.89, which was higher than 0.79 obtained using statistical parametric imaging. In particular, boundary artifacts were largely suppressed in the proposed imaging technique. Entropy enables using a small window for implementing ultrasound parametric imaging. PMID:28106118
Small-window parametric imaging based on information entropy for ultrasound tissue characterization
NASA Astrophysics Data System (ADS)
Tsui, Po-Hsiang; Chen, Chin-Kuo; Kuo, Wen-Hung; Chang, King-Jen; Fang, Jui; Ma, Hsiang-Yang; Chou, Dean
2017-01-01
Constructing ultrasound statistical parametric images by using a sliding window is a widely adopted strategy for characterizing tissues. Deficiency in spatial resolution, the appearance of boundary artifacts, and the prerequisite data distribution limit the practicability of statistical parametric imaging. In this study, small-window entropy parametric imaging was proposed to overcome the above problems. Simulations and measurements of phantoms were executed to acquire backscattered radiofrequency (RF) signals, which were processed to explore the feasibility of small-window entropy imaging in detecting scatterer properties. To validate the ability of entropy imaging in tissue characterization, measurements of benign and malignant breast tumors were conducted (n = 63) to compare performances of conventional statistical parametric (based on Nakagami distribution) and entropy imaging by the receiver operating characteristic (ROC) curve analysis. The simulation and phantom results revealed that entropy images constructed using a small sliding window (side length = 1 pulse length) adequately describe changes in scatterer properties. The area under the ROC for using small-window entropy imaging to classify tumors was 0.89, which was higher than 0.79 obtained using statistical parametric imaging. In particular, boundary artifacts were largely suppressed in the proposed imaging technique. Entropy enables using a small window for implementing ultrasound parametric imaging.
Schuitemaker, Alie; van Berckel, Bart N M; Kropholler, Marc A; Veltman, Dick J; Scheltens, Philip; Jonker, Cees; Lammertsma, Adriaan A; Boellaard, Ronald
2007-05-01
(R)-[11C]PK11195 has been used for quantifying cerebral microglial activation in vivo. In previous studies, both plasma input and reference tissue methods have been used, usually in combination with a region of interest (ROI) approach. Definition of ROIs, however, can be labourious and prone to interobserver variation. In addition, results are only obtained for predefined areas and (unexpected) signals in undefined areas may be missed. On the other hand, standard pharmacokinetic models are too sensitive to noise to calculate (R)-[11C]PK11195 binding on a voxel-by-voxel basis. Linearised versions of both plasma input and reference tissue models have been described, and these are more suitable for parametric imaging. The purpose of this study was to compare the performance of these plasma input and reference tissue parametric methods on the outcome of statistical parametric mapping (SPM) analysis of (R)-[11C]PK11195 binding. Dynamic (R)-[11C]PK11195 PET scans with arterial blood sampling were performed in 7 younger and 11 elderly healthy subjects. Parametric images of volume of distribution (Vd) and binding potential (BP) were generated using linearised versions of plasma input (Logan) and reference tissue (Reference Parametric Mapping) models. Images were compared at the group level using SPM with a two-sample t-test per voxel, both with and without proportional scaling. Parametric BP images without scaling provided the most sensitive framework for determining differences in (R)-[11C]PK11195 binding between younger and elderly subjects. Vd images could only demonstrate differences in (R)-[11C]PK11195 binding when analysed with proportional scaling due to intersubject variation in K1/k2 (blood-brain barrier transport and non-specific binding).
Parametric sonars for seafloor characterization
NASA Astrophysics Data System (ADS)
Caiti, Andrea; Bergem, Oddbjorn; Dybedal, Johnny
1999-12-01
Parametric sonars are instruments capable of transmitting acoustic signals in the water with a very narrow beam and almost no sidelobes. These features are exploited in this paper to define a methodology for quantitative estimation of the geo-acoustic and morphological properties of the uppermost seafloor sediment layer. The three major components of the approach are the parametric instrument itself; the modelling of the forward-propagation problem, with the use of the Kirchhoff approximation for surface scattering and of the small-perturbation theory for the volume scattering; and the definition of a criterion for comparison between data and model predictions, which is accomplished by a generalized time-frequency analysis. In this way the estimation becomes one of a model-based identification, or a model-based inverse problem. Results from a field trial in a shallow water area of the Mediterranean are shown, and compared with independently gathered ground truth.
Frequency domain optical parametric amplification
Schmidt, Bruno E.; Thiré, Nicolas; Boivin, Maxime; Laramée, Antoine; Poitras, François; Lebrun, Guy; Ozaki, Tsuneyuki; Ibrahim, Heide; Légaré, François
2014-01-01
Today’s ultrafast lasers operate at the physical limits of optical materials to reach extreme performances. Amplification of single-cycle laser pulses with their corresponding octave-spanning spectra still remains a formidable challenge since the universal dilemma of gain narrowing sets limits for both real level pumped amplifiers as well as parametric amplifiers. We demonstrate that employing parametric amplification in the frequency domain rather than in time domain opens up new design opportunities for ultrafast laser science, with the potential to generate single-cycle multi-terawatt pulses. Fundamental restrictions arising from phase mismatch and damage threshold of nonlinear laser crystals are not only circumvented but also exploited to produce a synergy between increased seed spectrum and increased pump energy. This concept was successfully demonstrated by generating carrier envelope phase stable, 1.43 mJ two-cycle pulses at 1.8 μm wavelength. PMID:24805968
Experience with parametric binary dissection
NASA Technical Reports Server (NTRS)
Bokhari, Shahid H.
1993-01-01
Parametric Binary Dissection (PBD) is a new algorithm that can be used for partitioning graphs embedded in 2- or 3-dimensional space. It partitions explicitly on the basis of nodes + (lambda)x(edges cut), where lambda is the ratio of time to communicate over an edge to the time to compute at a node. The new algorithm is faster than the original binary dissection algorithm and attempts to obtain better partitions than the older algorithm, which only takes nodes into account. The performance of parametric dissection with plain binary dissection on 3 large unstructured 3-d meshes obtained from computational fluid dynamics and on 2 random graphs were compared. It was showm that the new algorithm can usually yield partitions that are substantially superior, but that its performance is heavily dependent on the input data.
Song, Dong; Wang, Zhuo; Marmarelis, Vasilis Z; Berger, Theodore W
2009-02-01
This paper presents a synergistic parametric and non-parametric modeling study of short-term plasticity (STP) in the Schaffer collateral to hippocampal CA1 pyramidal neuron (SC) synapse. Parametric models in the form of sets of differential and algebraic equations have been proposed on the basis of the current understanding of biological mechanisms active within the system. Non-parametric Poisson-Volterra models are obtained herein from broadband experimental input-output data. The non-parametric model is shown to provide better prediction of the experimental output than a parametric model with a single set of facilitation/depression (FD) process. The parametric model is then validated in terms of its input-output transformational properties using the non-parametric model since the latter constitutes a canonical and more complete representation of the synaptic nonlinear dynamics. Furthermore, discrepancies between the experimentally-derived non-parametric model and the equivalent non-parametric model of the parametric model suggest the presence of multiple FD processes in the SC synapses. Inclusion of an additional set of FD process in the parametric model makes it replicate better the characteristics of the experimentally-derived non-parametric model. This improved parametric model in turn provides the requisite biological interpretability that the non-parametric model lacks.
Parametric Modeling for Fluid Systems
NASA Technical Reports Server (NTRS)
Pizarro, Yaritzmar Rosario; Martinez, Jonathan
2013-01-01
Fluid Systems involves different projects that require parametric modeling, which is a model that maintains consistent relationships between elements as is manipulated. One of these projects is the Neo Liquid Propellant Testbed, which is part of Rocket U. As part of Rocket U (Rocket University), engineers at NASA's Kennedy Space Center in Florida have the opportunity to develop critical flight skills as they design, build and launch high-powered rockets. To build the Neo testbed; hardware from the Space Shuttle Program was repurposed. Modeling for Neo, included: fittings, valves, frames and tubing, between others. These models help in the review process, to make sure regulations are being followed. Another fluid systems project that required modeling is Plant Habitat's TCUI test project. Plant Habitat is a plan to develop a large growth chamber to learn the effects of long-duration microgravity exposure to plants in space. Work for this project included the design and modeling of a duct vent for flow test. Parametric Modeling for these projects was done using Creo Parametric 2.0.
A unified framework for weighted parametric multiple test procedures.
Xi, Dong; Glimm, Ekkehard; Maurer, Willi; Bretz, Frank
2017-09-01
We describe a general framework for weighted parametric multiple test procedures based on the closure principle. We utilize general weighting strategies that can reflect complex study objectives and include many procedures in the literature as special cases. The proposed weighted parametric tests bridge the gap between rejection rules using either adjusted significance levels or adjusted p-values. This connection is made by allowing intersection hypotheses of the underlying closed test procedure to be tested at level smaller than α. This may be also necessary to take certain study situations into account. For such cases we introduce a subclass of exact α-level parametric tests that satisfy the consonance property. When the correlation is known only for certain subsets of the test statistics, a new procedure is proposed to fully utilize this knowledge within each subset. We illustrate the proposed weighted parametric tests using a clinical trial example and conduct a simulation study to investigate its operating characteristics. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
System and Method of Use for Non-parametric Circular Autocorrelation for Signal Processing
2012-07-30
0012] Wald , A. and J. Wolfowitz , An exact test for randomness in the non–Parametric case based on serial correlation, Annals of Mathematical...Statistics Vol. 14, No. 4, pages 378–388, 1943, (hereinafter “ Wald and Wolfowitz ”) provides a non-parametric permutations method such that if n is...present disclosure models accurately and efficiently. 8 [0015] Wald and Wolfowitz generally describe the properties of hxxR , in the context
Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A
2015-05-01
Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories.
Parametric methods for estimating covariate-dependent reference limits.
Virtanen, Arja; Kairisto, Veli; Uusipaikka, Esa
2004-01-01
Age-specific reference limits are required for many clinical laboratory measurements. Statistical assessment of calculated intervals must be performed to obtain reliable reference limits. When parametric, covariate-dependent limits are derived, normal distribution theory usually is applied due to its mathematical simplicity and relative ease of fitting. However, it is not always possible to transform data and achieve a normal distribution. Therefore, models other than those based on normal distribution theory are needed. Generalized linear model theory offers one such alternative. Regardless of the statistical model used, the assumptions behind the model should always be examined.
Stimulated Parametric Emission Microscope Systems
NASA Astrophysics Data System (ADS)
Itoh, Kazuyoshi; Isobe, Keisuke
2006-10-01
We present a novel microscopy technique based on the fourwave mixing (FWM) process that is enhanced by two-photon electronic resonance induced by a pump pulse along with stimulated emission induced by a dump pulse. A Ti:sapphire laser and an optical parametric oscillator are used as light sources for the pump and dump pulses, respectively. We demonstrate that our FWM technique can be used to obtain two-dimensional microscopic images of an unstained leaf of Camellia sinensis and an unlabeled tobacco BY2 Cell.
Whispering gallery optical parametric oscillators
NASA Astrophysics Data System (ADS)
Breunig, Ingo; Buse, Karsten
2013-12-01
Whispering gallery optical parametric oscillators (WGR OPOs) are monolithic sources for tunable coherent and non-classical light. They are based on total internal reflection. Since reflection losses are negligible, their oscillation threshold can be far below one milliwatt. With sub-millimeter diameters, they are the most compact OPOs demonstrated so far. Recent experimental results demonstrate that WGR OPOs emit coherent light tunable over hundreds of nanometers. Operation in the visible as well as in the near-infrared has been demonstrated with up to 30 % conversion efficiency. These results indicate a great potential of WGR OPOs for spectroscopic and sensing applications.
Parametric nanomechanical amplification at very high frequency.
Karabalin, R B; Feng, X L; Roukes, M L
2009-09-01
Parametric resonance and amplification are important in both fundamental physics and technological applications. Here we report very high frequency (VHF) parametric resonators and mechanical-domain amplifiers based on nanoelectromechanical systems (NEMS). Compound mechanical nanostructures patterned by multilayer, top-down nanofabrication are read out by a novel scheme that parametrically modulates longitudinal stress in doubly clamped beam NEMS resonators. Parametric pumping and signal amplification are demonstrated for VHF resonators up to approximately 130 MHz and provide useful enhancement of both resonance signal amplitude and quality factor. We find that Joule heating and reduced thermal conductance in these nanostructures ultimately impose an upper limit to device performance. We develop a theoretical model to account for both the parametric response and nonequilibrium thermal transport in these composite nanostructures. The results closely conform to our experimental observations, elucidate the frequency and threshold-voltage scaling in parametric VHF NEMS resonators and sensors, and establish the ultimate sensitivity limits of this approach.
Rosetta stone for parametrized tests of gravity
NASA Astrophysics Data System (ADS)
Sampson, Laura; Yunes, Nicolás; Cornish, Neil
2013-09-01
Several model-independent parametrizations of deviations from general relativity have been developed to test Einstein’s theory. Although these different parametrizations were developed for different gravitational observables, they ultimately all test the same underlying physics. In this paper, we develop connections between the parametrized post-Newtonian, parametrized post-Keplerian, and the parametrized post-Einsteinian frameworks, developed to carry out tests of general relativity with Solar System, binary pulsar, and gravitational wave observations, respectively. These connections, although only valid under certain assumptions such as energy/momentum conservation, allow us to use knowledge gained from one framework to inform and guide tests using the others. Relating these parametrizations and combining the results from each approach strengthens our tests of general relativity.
Parametric and Non-Parametric Vibration-Based Structural Identification Under Earthquake Excitation
NASA Astrophysics Data System (ADS)
Pentaris, Fragkiskos P.; Fouskitakis, George N.
2014-05-01
]. Preliminary results indicate that parametric methods are capable of sufficiently providing the structural/modal characteristics such as natural frequencies and damping ratios. The study also aims - at a further level of investigation - to provide a reliable statistically-based methodology for structural health monitoring after major seismic events which potentially cause harming consequences in structures. Acknowledgments This work was supported by the State Scholarships Foundation of Hellas. References [1] J. S. Sakellariou and S. D. Fassois, "Stochastic output error vibration-based damage detection and assessment in structures under earthquake excitation," Journal of Sound and Vibration, vol. 297, pp. 1048-1067, 2006. [2] G. Hloupis, I. Papadopoulos, J. P. Makris, and F. Vallianatos, "The South Aegean seismological network - HSNC," Adv. Geosci., vol. 34, pp. 15-21, 2013. [3] F. P. Pentaris, J. Stonham, and J. P. Makris, "A review of the state-of-the-art of wireless SHM systems and an experimental set-up towards an improved design," presented at the EUROCON, 2013 IEEE, Zagreb, 2013. [4] S. D. Fassois, "Parametric Identification of Vibrating Structures," in Encyclopedia of Vibration, S. G. Braun, D. J. Ewins, and S. S. Rao, Eds., ed London: Academic Press, London, 2001. [5] S. D. Fassois and J. S. Sakellariou, "Time-series methods for fault detection and identification in vibrating structures," Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 365, pp. 411-448, February 15 2007.
A THEORY FOR BROADBAND VARACTOR PARAMETRIC AMPLIFIERS
This thesis is concerned with the development of a general and rigorous broadbanding theory for varactor parametric amplifiers . Fundamental gain...bandwidth limitations of a varactor parametric amplifier are obtained which are independent of the equalizer. Results obtained in this theory lead to the...design and synthesis of broadband varactor parametric amplifiers . The circuit considered in this thesis is that of linear variable capacitors embedded
Stellar parametrization from Gaia RVS spectra
NASA Astrophysics Data System (ADS)
Recio-Blanco, A.; de Laverny, P.; Allende Prieto, C.; Fustes, D.; Manteiga, M.; Arcay, B.; Bijaoui, A.; Dafonte, C.; Ordenovic, C.; Ordoñez Blanco, D.
2016-01-01
found for A-type stars, while the log(g) derivation is more accurate (errors of 0.07 and 0.12 dex at GRVS = 12.6 and 13.4, respectively). For the faintest stars, with GRVS≳ 13-14, a Teff input from the spectrophotometric-derived parameters will allow the final GSP-Spec parametrization to be improved. Conclusions: The reported results, while neglecting possible mismatches between synthetic and real spectra, show that the contribution of the RVS-based stellar parameters will be unique in the brighter part of the Gaia survey, which allows for crucial age estimations and accurate chemical abundances. This will constitute a unique and precious sample, providing many pieces of the Milky Way history puzzle with unprecedented precision and statistical relevance.
Software for Managing Parametric Studies
NASA Technical Reports Server (NTRS)
Yarrow, Maurice; McCann, Karen M.; DeVivo, Adrian
2003-01-01
The Information Power Grid Virtual Laboratory (ILab) is a Practical Extraction and Reporting Language (PERL) graphical-user-interface computer program that generates shell scripts to facilitate parametric studies performed on the Grid. (The Grid denotes a worldwide network of supercomputers used for scientific and engineering computations involving data sets too large to fit on desktop computers.) Heretofore, parametric studies on the Grid have been impeded by the need to create control language scripts and edit input data files painstaking tasks that are necessary for managing multiple jobs on multiple computers. ILab reflects an object-oriented approach to automation of these tasks: All data and operations are organized into packages in order to accelerate development and debugging. A container or document object in ILab, called an experiment, contains all the information (data and file paths) necessary to define a complex series of repeated, sequenced, and/or branching processes. For convenience and to enable reuse, this object is serialized to and from disk storage. At run time, the current ILab experiment is used to generate required input files and shell scripts, create directories, copy data files, and then both initiate and monitor the execution of all computational processes.
Bayesian non parametric modelling of Higgs pair production
NASA Astrophysics Data System (ADS)
Scarpa, Bruno; Dorigo, Tommaso
2017-03-01
Statistical classification models are commonly used to separate a signal from a background. In this talk we face the problem of isolating the signal of Higgs pair production using the decay channel in which each boson decays into a pair of b-quarks. Typically in this context non parametric methods are used, such as Random Forests or different types of boosting tools. We remain in the same non-parametric framework, but we propose to face the problem following a Bayesian approach. A Dirichlet process is used as prior for the random effects in a logit model which is fitted by leveraging the Polya-Gamma data augmentation. Refinements of the model include the insertion in the simple model of P-splines to relate explanatory variables with the response and the use of Bayesian trees (BART) to describe the atoms in the Dirichlet process.
Parametric vs. non-parametric daily weather generator: validation and comparison
NASA Astrophysics Data System (ADS)
Dubrovsky, Martin
2016-04-01
As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series
Acceleration of the direct reconstruction of linear parametric images using nested algorithms.
Wang, Guobao; Qi, Jinyi
2010-03-07
Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.
Treister, Roi; Nielsen, Christopher S; Stubhaug, Audun; Farrar, John T; Pud, Dorit; Sawilowsky, Shlomo; Oaklander, Anne Louise
2015-06-01
Parametric statistical methods are common in human pain research. They require normally distributed data, but this assumption is rarely tested. The current study analyzes the appropriateness of parametric testing for outcomes from the cold pressor test (CPT), a common human experimental pain test. We systematically reviewed published CPT studies to quantify how often researchers test for normality and how often they use parametric versus nonparametric tests. We then measured the normality of CPT data from 7 independent small to medium cohorts and 1 study of >10,000 subjects. We then examined the ability of 2 common mathematical transformations to normalize our skewed data sets. Lastly, we performed Monte Carlo simulations on a representative data set to compare the statistical power of the parametric t-test versus the nonparametric Wilcoxon Mann-Whitney test. We found that only 39% of published CPT studies (47/122) mentioned checking data distribution, yet 72% (88/122) used parametric statistics. Furthermore, among our 8 data sets, CPT outcomes were virtually always nonnormally distributed, and mathematical transformations were largely ineffective in normalizing them. The simulations demonstrated that the nonparametric Wilcoxon Mann-Whitney test had greater statistical power than the parametric t-test for all scenarios tested: For small effect sizes, the Wilcoxon Mann-Whitney test had up to 300% more power. These results demonstrate that parametric analyses of CPT data are routine but incorrect and that they likely increase the chances of failing to detect significant between-group differences. They suggest that nonparametric analyses become standard for CPT studies and that assumptions of normality be routinely tested for other types of pain outcomes as well. Copyright © 2015 American Pain Society. Published by Elsevier Inc. All rights reserved.
Observation of Parametric Instability in Advanced LIGO
NASA Astrophysics Data System (ADS)
Evans, Matthew; Gras, Slawek; Fritschel, Peter; Miller, John; Barsotti, Lisa; Martynov, Denis; Brooks, Aidan; Coyne, Dennis; Abbott, Rich; Adhikari, Rana X.; Arai, Koji; Bork, Rolf; Kells, Bill; Rollins, Jameson; Smith-Lefebvre, Nicolas; Vajente, Gabriele; Yamamoto, Hiroaki; Adams, Carl; Aston, Stuart; Betzweiser, Joseph; Frolov, Valera; Mullavey, Adam; Pele, Arnaud; Romie, Janeen; Thomas, Michael; Thorne, Keith; Dwyer, Sheila; Izumi, Kiwamu; Kawabe, Keita; Sigg, Daniel; Derosa, Ryan; Effler, Anamaria; Kokeyama, Keiko; Ballmer, Stefan; Massinger, Thomas J.; Staley, Alexa; Heinze, Matthew; Mueller, Chris; Grote, Hartmut; Ward, Robert; King, Eleanor; Blair, David; Ju, Li; Zhao, Chunnong
2015-04-01
Parametric instabilities have long been studied as a potentially limiting effect in high-power interferometric gravitational wave detectors. Until now, however, these instabilities have never been observed in a kilometer-scale interferometer. In this Letter, we describe the first observation of parametric instability in a gravitational wave detector, and the means by which it has been removed as a barrier to progress.
Why preferring parametric forecasting to nonparametric methods?
Jabot, Franck
2015-05-07
A recent series of papers by Charles T. Perretti and collaborators have shown that nonparametric forecasting methods can outperform parametric methods in noisy nonlinear systems. Such a situation can arise because of two main reasons: the instability of parametric inference procedures in chaotic systems which can lead to biased parameter estimates, and the discrepancy between the real system dynamics and the modeled one, a problem that Perretti and collaborators call "the true model myth". Should ecologists go on using the demanding parametric machinery when trying to forecast the dynamics of complex ecosystems? Or should they rely on the elegant nonparametric approach that appears so promising? It will be here argued that ecological forecasting based on parametric models presents two key comparative advantages over nonparametric approaches. First, the likelihood of parametric forecasting failure can be diagnosed thanks to simple Bayesian model checking procedures. Second, when parametric forecasting is diagnosed to be reliable, forecasting uncertainty can be estimated on virtual data generated with the fitted to data parametric model. In contrast, nonparametric techniques provide forecasts with unknown reliability. This argumentation is illustrated with the simple theta-logistic model that was previously used by Perretti and collaborators to make their point. It should convince ecologists to stick to standard parametric approaches, until methods have been developed to assess the reliability of nonparametric forecasting.
Pump noise cancellation in parametric wavelength converters.
Ataie, Vahid; Myslivets, Evgeny; Wiberg, Andereas O J; Alic, Nikola; Radic, Stojan
2012-12-10
A novel technique for pump noise effect mitigation in parametric wavelength converters is introduced. The method relies on digital signal processing and effectively takes advantage of the correlation property between the pump and idler, imposed by the parametric interaction. A 4 dB improvement in receiver performance is demonstrated experimentally for the conventional 10 Gbps OOK signal converted over 20 nm.
Calculations of superconducting parametric amplifiers performances
NASA Astrophysics Data System (ADS)
Goto, T.; Takeda, M.; Saito, S.; Shimakage, H.
2017-07-01
A superconducting parametric amplifier is an electromagnetic wave amplifier with high-quality characteristics such as a wide bandwidth, an extremely low noise, and a high dynamic range. In this paper, we report on the estimations of a YBCO superconducting parametric amplifier characteristic. The YBCO thin films were deposited on an MgO substrate by a pulsed laser deposition method. Based on the measured YBCO thin film parameters, theoretical calculations were implemented for evaluations of kinetic inductance nonlinearities and parametric gains. The nonlinearity of the YBCO thin film was estimated to be stronger than a single crystal NbTiN thin film. It is indicated that the YBCO parametric amplifier has a potential to be realized the amplifier with the high parametric gain. It is also expected that it could be operated in the range of the high frequency band, at the high temperature, and low applied current.
Marmarelis, Vasilis Z.; Berger, Theodore W.
2009-01-01
Parametric and non-parametric modeling methods are combined to study the short-term plasticity (STP) of synapses in the central nervous system (CNS). The nonlinear dynamics of STP are modeled by means: (1) previously proposed parametric models based on mechanistic hypotheses and/or specific dynamical processes, and (2) non-parametric models (in the form of Volterra kernels) that transforms the presynaptic signals into postsynaptic signals. In order to synergistically use the two approaches, we estimate the Volterra kernels of the parametric models of STP for four types of synapses using synthetic broadband input–output data. Results show that the non-parametric models accurately and efficiently replicate the input–output transformations of the parametric models. Volterra kernels provide a general and quantitative representation of the STP. PMID:18506609
Direct fluorescence characterisation of a picosecond seeded optical parametric amplifier
NASA Astrophysics Data System (ADS)
Stuart, N. H.; Bigourd, D.; Hill, R. W.; Robinson, T. S.; Mecseki, K.; Patankar, S.; New, G. H. C.; Smith, R. A.
2015-02-01
The temporal intensity contrast of high-power lasers based on optical parametric amplification (OPA) can be limited by parametric fluorescence from the non-linear gain stages. Here we present a spectroscopic method for direct measurement of unwanted parametric fluorescence widely applicable from unseeded to fully seeded and saturated OPA operation. Our technique employs simultaneous spectroscopy of fluorescence photons slightly outside the seed bandwidth and strongly attenuated light at the seed central wavelength. To demonstrate its applicability we have characterised the performance of a two-stage picosecond OPA pre-amplifier with 2.8×105 gain, delivering 335 μJ pulses at 1054 nm. We show that fluorescence from a strongly seeded OPA is reduced by ~500× from the undepleted to full pump depletion regimes. We also determine the vacuum fluctuation driven noise term seeding this OPA fluorescence to be 0.7±0.4 photons ps-1 nm-1 bandwidth. The resulting shot-to-shot statistics highlights a 1.5% probability of a five-fold and 0.3% probability of a ten-fold increase of fluorescence above the average value. Finally, we show that OPA fluorescence can be limited to a few-ps pedestal with 3×10-9 temporal intensity contrast 1.3 ps ahead of an intense laser pulse, a level highly attractive for large scale chirped-pulse OPA laser systems.
Nonparametric predictive inference for combining diagnostic tests with parametric copula
NASA Astrophysics Data System (ADS)
Muhammad, Noryanti; Coolen, F. P. A.; Coolen-Maturi, T.
2017-09-01
Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine and health care. The Receiver Operating Characteristic (ROC) curve is a popular statistical tool for describing the performance of diagnostic tests. The area under the ROC curve (AUC) is often used as a measure of the overall performance of the diagnostic test. In this paper, we interest in developing strategies for combining test results in order to increase the diagnostic accuracy. We introduce nonparametric predictive inference (NPI) for combining two diagnostic test results with considering dependence structure using parametric copula. NPI is a frequentist statistical framework for inference on a future observation based on past data observations. NPI uses lower and upper probabilities to quantify uncertainty and is based on only a few modelling assumptions. While copula is a well-known statistical concept for modelling dependence of random variables. A copula is a joint distribution function whose marginals are all uniformly distributed and it can be used to model the dependence separately from the marginal distributions. In this research, we estimate the copula density using a parametric method which is maximum likelihood estimator (MLE). We investigate the performance of this proposed method via data sets from the literature and discuss results to show how our method performs for different family of copulas. Finally, we briefly outline related challenges and opportunities for future research.
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Shi, Runhua; McLarty, Jerry W
2009-10-01
In this article, we introduced basic concepts of statistics, type of distributions, and descriptive statistics. A few examples were also provided. The basic concepts presented herein are only a fraction of the concepts related to descriptive statistics. Also, there are many commonly used distributions not presented herein, such as Poisson distributions for rare events and exponential distributions, F distributions, and logistic distributions. More information can be found in many statistics books and publications.
Multivariable Parametric Cost Model for Ground Optical: Telescope Assembly
NASA Technical Reports Server (NTRS)
Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia
2004-01-01
A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature were examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter were derived.
Multivariable Parametric Cost Model for Ground Optical Telescope Assembly
NASA Technical Reports Server (NTRS)
Stahl, H. Philip; Rowell, Ginger Holmes; Reese, Gayle; Byberg, Alicia
2005-01-01
A parametric cost model for ground-based telescopes is developed using multivariable statistical analysis of both engineering and performance parameters. While diameter continues to be the dominant cost driver, diffraction-limited wavelength is found to be a secondary driver. Other parameters such as radius of curvature are examined. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e., multi-telescope phased-array systems). Additionally, single variable models Based on aperture diameter are derived.
Single-variable parametric cost models for space telescopes
NASA Astrophysics Data System (ADS)
Stahl, H. Philip; Henrichs, Todd; Smart, Christian; Prince, Frank A.
2010-07-01
Parametric cost models are routinely used to plan missions, compare concepts, and justify technology investments. Unfortunately, there is no definitive space telescope cost model. For example, historical cost estimating relationships (CERs) based on primary mirror diameter vary by an order of magnitude. We present new single-variable cost models for space telescope optical telescope assembly (OTA). They are based on data collected from 30 different space telescope missions. Standard statistical methods are used to derive CERs for OTA cost versus aperture diameter and mass. The results are compared with previously published models
Likert scales, levels of measurement and the "laws" of statistics.
Norman, Geoff
2010-12-01
Reviewers of research reports frequently criticize the choice of statistical methods. While some of these criticisms are well-founded, frequently the use of various parametric methods such as analysis of variance, regression, correlation are faulted because: (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The data are from Likert scales, which are ordinal, so parametric statistics cannot be used. In this paper, I dissect these arguments, and show that many studies, dating back to the 1930s consistently show that parametric statistics are robust with respect to violations of these assumptions. Hence, challenges like those above are unfounded, and parametric methods can be utilized without concern for "getting the wrong answer".
ERIC Educational Resources Information Center
Petocz, Peter; Sowey, Eric
2008-01-01
As a branch of knowledge, Statistics is ubiquitous and its applications can be found in (almost) every field of human endeavour. In this article, the authors track down the possible source of the link between the "Siren song" and applications of Statistics. Answers to their previous five questions and five new questions on Statistics are presented.
ERIC Educational Resources Information Center
Callamaras, Peter
1983-01-01
This buyer's guide to seven major types of statistics software packages for microcomputers reviews Edu-Ware Statistics 3.0; Financial Planning; Speed Stat; Statistics with DAISY; Human Systems Dynamics package of Stats Plus, ANOVA II, and REGRESS II; Maxistat; and Moore-Barnes' MBC Test Construction and MBC Correlation. (MBR)
Characteristics of stereo reproduction with parametric loudspeakers
NASA Astrophysics Data System (ADS)
Aoki, Shigeaki; Toba, Masayoshi; Tsujita, Norihisa
2012-05-01
A parametric loudspeaker utilizes nonlinearity of a medium and is known as a super-directivity loudspeaker. The parametric loudspeaker is one of the prominent applications of nonlinear ultrasonics. So far, the applications have been limited monaural reproduction sound system for public address in museum, station and street etc. In this paper, we discussed characteristics of stereo reproduction with two parametric loudspeakers by comparing with those with two ordinary dynamic loudspeakers. In subjective tests, three typical listening positions were selected to investigate the possibility of correct sound localization in a wide listening area. The binaural information was ILD (Interaural Level Difference) or ITD (Interaural Time Delay). The parametric loudspeaker was an equilateral hexagon. The inner and outer diameters were 99 and 112 mm, respectively. Signals were 500 Hz, 1 kHz, 2 kHz and 4 kHz pure tones and pink noise. Three young males listened to test signals 10 times in each listening condition. Subjective test results showed that listeners at the three typical listening positions perceived correct sound localization of all signals using the parametric loudspeakers. It was almost similar to those using the ordinary dynamic loudspeakers, however, except for the case of sinusoidal waves with ITD. It was determined the parametric loudspeaker could exclude the contradiction between the binaural information ILD and ITD that occurred in stereo reproduction with ordinary dynamic loudspeakers because the super directivity of parametric loudspeaker suppressed the cross talk components.
Bayesian adjustment for covariate measurement errors: a flexible parametric approach.
Hossain, Shahadut; Gustafson, Paul
2009-05-15
In most epidemiological investigations, the study units are people, the outcome variable (or the response) is a health-related event, and the explanatory variables are usually environmental and/or socio-demographic factors. The fundamental task in such investigations is to quantify the association between the explanatory variables (covariates/exposures) and the outcome variable through a suitable regression model. The accuracy of such quantification depends on how precisely the relevant covariates are measured. In many instances, we cannot measure some of the covariates accurately. Rather, we can measure noisy (mismeasured) versions of them. In statistical terminology, mismeasurement in continuous covariates is known as measurement errors or errors-in-variables. Regression analyses based on mismeasured covariates lead to biased inference about the true underlying response-covariate associations. In this paper, we suggest a flexible parametric approach for avoiding this bias when estimating the response-covariate relationship through a logistic regression model. More specifically, we consider the flexible generalized skew-normal and the flexible generalized skew-t distributions for modeling the unobserved true exposure. For inference and computational purposes, we use Bayesian Markov chain Monte Carlo techniques. We investigate the performance of the proposed flexible parametric approach in comparison with a common flexible parametric approach through extensive simulation studies. We also compare the proposed method with the competing flexible parametric method on a real-life data set. Though emphasis is put on the logistic regression model, the proposed method is unified and is applicable to the other generalized linear models, and to other types of non-linear regression models as well. (c) 2009 John Wiley & Sons, Ltd.
Ionization Cooling using Parametric Resonances
Johnson, Rolland P.
2008-06-07
Ionization Cooling using Parametric Resonances was an SBIR project begun in July 2004 and ended in January 2008 with Muons, Inc., (Dr. Rolland Johnson, PI), and Thomas Jefferson National Accelerator Facility (JLab) (Dr. Yaroslav Derbenev, Subcontract PI). The project was to develop the theory and simulations of Parametric-resonance Ionization Cooling (PIC) so that it could be used to provide the extra transverse cooling needed for muon colliders in order to relax the requirements on the proton driver, reduce the site boundary radiation, and provide a better environment for experiments. During the course of the project, the theoretical understanding of PIC was developed and a final exposition is ready for publication. Workshops were sponsored by Muons, Inc. in May and September of 2007 that were devoted to the PIC technique. One outcome of the workshops was the interesting and somewhat unexpected realization that the beam emittances using the PIC technique can get small enough that space charge forces can be important. A parallel effort to develop our G4beamline simulation program to include space charge effects was initiated to address this problem. A method of compensating for chromatic aberrations by employing synchrotron motion was developed and simulated. A method of compensating for spherical aberrations using beamline symmetry was also developed and simulated. Different optics designs have been developed using the OptiM program in preparation for applying our G4beamline simulation program, which contains all the power of the Geant4 toolkit. However, no PIC channel design that has been developed has had the desired cooling performance when subjected to the complete G4beamline simulation program. This is believed to be the consequence of the difficulties of correcting the aberrations associated with the naturally large beam angles and beam sizes of the PIC method that are exacerbated by the fringe fields of the rather complicated channel designs that have been
Simulation of parametric model towards the fixed covariate of right censored lung cancer data
NASA Astrophysics Data System (ADS)
Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Ridwan Olaniran, Oyebayo; Enera Amran, Syahila
2017-09-01
In this study, simulation procedure was applied to measure the fixed covariate of right censored data by using parametric survival model. The scale and shape parameter were modified to differentiate the analysis of parametric regression survival model. Statistically, the biases, mean biases and the coverage probability were used in this analysis. Consequently, different sample sizes were employed to distinguish the impact of parametric regression model towards right censored data with 50, 100, 150 and 200 number of sample. R-statistical software was utilised to develop the coding simulation with right censored data. Besides, the final model of right censored simulation was compared with the right censored lung cancer data in Malaysia. It was found that different values of shape and scale parameter with different sample size, help to improve the simulation strategy for right censored data and Weibull regression survival model is suitable fit towards the simulation of survival of lung cancer patients data in Malaysia.
Quantiles, parametric-select density estimation, and bi-information parameter estimators
NASA Technical Reports Server (NTRS)
Parzen, E.
1982-01-01
A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.
Quantiles, parametric-select density estimation, and bi-information parameter estimators
NASA Technical Reports Server (NTRS)
Parzen, E.
1982-01-01
A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.
Self-seeding ring optical parametric oscillator
Smith, Arlee V.; Armstrong, Darrell J.
2005-12-27
An optical parametric oscillator apparatus utilizing self-seeding with an external nanosecond-duration pump source to generate a seed pulse resulting in increased conversion efficiency. An optical parametric oscillator with a ring configuration are combined with a pump that injection seeds the optical parametric oscillator with a nanosecond duration, mJ pulse in the reverse direction as the main pulse. A retroreflecting means outside the cavity injects the seed pulse back into the cavity in the direction of the main pulse to seed the main pulse, resulting in higher conversion efficiency.
NASA Astrophysics Data System (ADS)
Eliazar, Iddo
2017-05-01
The exponential, the normal, and the Poisson statistical laws are of major importance due to their universality. Harmonic statistics are as universal as the three aforementioned laws, but yet they fall short in their 'public relations' for the following reason: the full scope of harmonic statistics cannot be described in terms of a statistical law. In this paper we describe harmonic statistics, in their full scope, via an object termed harmonic Poisson process: a Poisson process, over the positive half-line, with a harmonic intensity. The paper reviews the harmonic Poisson process, investigates its properties, and presents the connections of this object to an assortment of topics: uniform statistics, scale invariance, random multiplicative perturbations, Pareto and inverse-Pareto statistics, exponential growth and exponential decay, power-law renormalization, convergence and domains of attraction, the Langevin equation, diffusions, Benford's law, and 1/f noise.
Airy beam optical parametric oscillator
NASA Astrophysics Data System (ADS)
Aadhi, A.; Chaitanya, N. Apurv; Jabir, M. V.; Vaity, Pravin; Singh, R. P.; Samanta, G. K.
2016-05-01
Airy beam, a non-diffracting waveform, has peculiar properties of self-healing and self-acceleration. Due to such unique properties, the Airy beam finds many applications including curved plasma wave-guiding, micro-particle manipulation, optically mediated particle clearing, long distance communication, and nonlinear frequency conversion. However, many of these applications including laser machining of curved structures, generation of curved plasma channels, guiding of electric discharges in a curved path, study of nonlinear propagation dynamics, and nonlinear interaction demand Airy beam with high power, energy, and wavelength tunability. Till date, none of the Airy beam sources have all these features in a single device. Here, we report a new class of coherent sources based on cubic phase modulation of a singly-resonant optical parametric oscillator (OPO), producing high-power, continuous-wave (cw), tunable radiation in 2-D Airy intensity profile existing over a length >2 m. Based on a MgO-doped periodically poled LiNbO3 crystal pumped at 1064 nm, the Airy beam OPO produces output power more than 8 W, and wavelength tunability across 1.51–1.97 μm. This demonstration gives new direction for the development of sources of arbitrary structured beams at any wavelength, power, and energy in all time scales (cw to femtosecond).
Airy beam optical parametric oscillator
Aadhi, A.; Chaitanya, N. Apurv; Jabir, M. V.; Vaity, Pravin; Singh, R. P.; Samanta, G. K.
2016-01-01
Airy beam, a non-diffracting waveform, has peculiar properties of self-healing and self-acceleration. Due to such unique properties, the Airy beam finds many applications including curved plasma wave-guiding, micro-particle manipulation, optically mediated particle clearing, long distance communication, and nonlinear frequency conversion. However, many of these applications including laser machining of curved structures, generation of curved plasma channels, guiding of electric discharges in a curved path, study of nonlinear propagation dynamics, and nonlinear interaction demand Airy beam with high power, energy, and wavelength tunability. Till date, none of the Airy beam sources have all these features in a single device. Here, we report a new class of coherent sources based on cubic phase modulation of a singly-resonant optical parametric oscillator (OPO), producing high-power, continuous-wave (cw), tunable radiation in 2-D Airy intensity profile existing over a length >2 m. Based on a MgO-doped periodically poled LiNbO3 crystal pumped at 1064 nm, the Airy beam OPO produces output power more than 8 W, and wavelength tunability across 1.51–1.97 μm. This demonstration gives new direction for the development of sources of arbitrary structured beams at any wavelength, power, and energy in all time scales (cw to femtosecond). PMID:27143582
Airy beam optical parametric oscillator.
Aadhi, A; Chaitanya, N Apurv; Jabir, M V; Vaity, Pravin; Singh, R P; Samanta, G K
2016-05-04
Airy beam, a non-diffracting waveform, has peculiar properties of self-healing and self-acceleration. Due to such unique properties, the Airy beam finds many applications including curved plasma wave-guiding, micro-particle manipulation, optically mediated particle clearing, long distance communication, and nonlinear frequency conversion. However, many of these applications including laser machining of curved structures, generation of curved plasma channels, guiding of electric discharges in a curved path, study of nonlinear propagation dynamics, and nonlinear interaction demand Airy beam with high power, energy, and wavelength tunability. Till date, none of the Airy beam sources have all these features in a single device. Here, we report a new class of coherent sources based on cubic phase modulation of a singly-resonant optical parametric oscillator (OPO), producing high-power, continuous-wave (cw), tunable radiation in 2-D Airy intensity profile existing over a length >2 m. Based on a MgO-doped periodically poled LiNbO3 crystal pumped at 1064 nm, the Airy beam OPO produces output power more than 8 W, and wavelength tunability across 1.51-1.97 μm. This demonstration gives new direction for the development of sources of arbitrary structured beams at any wavelength, power, and energy in all time scales (cw to femtosecond).
Parametric display of myocardial function.
Eusemann, C D; Ritman, E L; Bellemann, M E; Robb, R A
2001-01-01
Quantitative assessment of regional heart motion has significant potential to provide more specific diagnosis of cardiac disease and cardiac malfunction than currently possible. Local heart motion may be captured from various medical imaging scanners. In this study, 3-D reconstructions of pre-infarct and post-infarct hearts were obtained from the Dynamic Spatial Reconstructor (DSR)[Ritman EL, Robb RA, Harris LD. Imaging physiological functions: experience with DSR. Philadelphia: Praeger, 1985; Robb RA, Lent AH, Gilbert BK, Chu A. The dynamic spatial reconstructor: a computed tomography system for high-speed simultaneous scanning of multiple cross sections of the heart. J Med Syst 1980;4(2):253-88; Jorgensen SM, Whitlock SV, Thomas PJ, Roessler RW, Ritman EL. The dynamic spatial reconstructor: a high speed, stop action, 3-D, digital radiographic imager of moving internal organs and blood. Proceedings of SPIE, Ultrahigh- and High-speed Photography, Videography, Photonics, and Velocimetry 1990;1346:180-91.] (DSR). Using functional parametric mapping of disturbances in regional contractility and relaxation, regional myocardial motion during a cardiac cycle is color mapped onto a deformable heart model to facilitate appreciation of the structure-to-function relationships in the myocardium, such as occurs in regional patterns of akinesis or dyskinesis associated with myocardial ischemia or infarction resulting from coronary artery occlusion.
Parametrically enhanced hidden photon search
NASA Astrophysics Data System (ADS)
Graham, Peter W.; Mardon, Jeremy; Rajendran, Surjeet; Zhao, Yue
2014-10-01
Many theories beyond the Standard Model contain hidden photons. A light hidden photon will generically couple to the Standard Model through a kinetic mixing term, giving a powerful avenue for detection using "light-shining-through-a-wall"-type transmission experiments with resonant cavities. We demonstrate a parametric enhancement of the signal in such experiments, resulting from transmission of the longitudinal mode of the hidden photon. While previous literature has focused on the production and detection of transverse modes, the longitudinal mode allows a significant improvement in experimental sensitivity. Although optical experiments such as ALPS are unable to take useful advantage of this enhancement, the reach of existing microwave cavity experiments such as CROWS is significantly enhanced beyond their published results. Future microwave cavity experiments, designed with appropriate geometry to take full advantage of the longitudinal mode, will provide a powerful probe of hidden-photon parameter space extending many orders of magnitude beyond current limits, including significant regions where the hidden photon can be dark matter.
Generating Entangled State with Parametric Amplifier
NASA Astrophysics Data System (ADS)
Huang, Jian
2017-04-01
We present a scheme for generating entangled state with parametric amplifier with different initial states. Its shown that the entangled state is always generated except some special cases by adjusting the coupling strength and the total number of photons.
Ranking Forestry Investments With Parametric Linear Programming
Paul A. Murphy
1976-01-01
Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.
Conformally covariant parametrizations for relativistic initial data
NASA Astrophysics Data System (ADS)
Delay, Erwann
2017-01-01
We revisit the Lichnerowicz-York method, and an alternative method of York, in order to obtain some conformally covariant systems. This type of parametrization is certainly more natural for non constant mean curvature initial data.
Parametrically disciplined operation of a vibratory gyroscope
NASA Technical Reports Server (NTRS)
Shcheglov, Kirill V. (Inventor); Hayworth, Ken J. (Inventor); Challoner, A. Dorian (Inventor); Peay, Chris S. (Inventor)
2008-01-01
Parametrically disciplined operation of a symmetric nearly degenerate mode vibratory gyroscope is disclosed. A parametrically-disciplined inertial wave gyroscope having a natural oscillation frequency in the neighborhood of a sub-harmonic of an external stable clock reference is produced by driving an electrostatic bias electrode at approximately twice this sub-harmonic frequency to achieve disciplined frequency and phase operation of the resonator. A nearly symmetric parametrically-disciplined inertial wave gyroscope that can oscillate in any transverse direction and has more than one bias electrostatic electrode that can be independently driven at twice its oscillation frequency at an amplitude and phase that disciplines its damping to zero in any vibration direction. In addition, operation of a parametrically-disciplined inertial wave gyroscope is taught in which the precession rate of the driven vibration pattern is digitally disciplined to a prescribed non-zero reference value.
A Parametric k-Means Algorithm
Tarpey, Thaddeus
2007-01-01
Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692
A Parametric k-Means Algorithm.
Tarpey, Thaddeus
2007-04-01
The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm.
The Quantum Theory of Optical Parametric Amplification
NASA Astrophysics Data System (ADS)
Hussain, N. A.
Available from UMI in association with The British Library. Requires signed TDF. The aim of this thesis is to investigate the effect of parametric amplification on various forms of light. In particular we shall consider number and coherent states, but many of the calculations hold for those states whose operators satisfy the properties, < {a}^+{a}^+ >=<{a}{a }> = < {a}^+>=<{a }>=0 e.g. chaotic light. The first chapter lays down the fundamental preliminaries necessary for our calculations and reviews linear amplifier theory. We consider the phase sensitive and insensitive forms of amplifiers modelling the former on the degenerate parametric amplifier and the latter on the non-degenerate and inverted population amplifiers. Chapter 2 deals with balanced homodyne detection of a narrow band coherent state before and after degenerate parametric amplification. In chapter 3 we consider a continuous mode number state produced by atomic emission and parametrically amplified using the formalism of Collett and Gardiner. We give general results for the output flux intensity and also consider the simpler case where the atomic decay rate is much smaller than the parametric cavity decay rate. Also we consider the degree of second order coherence using this simplified theory. Chapters 4 and 5 consider the double amplifier interferometer, using single and continuous mode theories, and enable us to determine the form of amplifier which produces the best visibility and hence lowest noise figures. The travelling-wave parametric amplifier is discussed in chapter 6 and is contrasted with the cavity parametric amplifier discussed in chapters 1 and 2. Finally we consider the much contemplated idea of using amplifiers to boost signals in fibre optic transmission lines using our model of the parametric amplifier and examining the degradation of the signal-to-noise ratio. We consider both coherent and squeezed inputs and our results hold for both cavity and travelling -wave amplifiers.
Chaos control of parametric driven Duffing oscillators
Jin, Leisheng; Mei, Jie; Li, Lijie
2014-03-31
Duffing resonators are typical dynamic systems, which can exhibit chaotic oscillations, subject to certain driving conditions. Chaotic oscillations of resonating systems with negative and positive spring constants are identified to investigate in this paper. Parametric driver imposed on these two systems affects nonlinear behaviours, which has been theoretically analyzed with regard to variation of driving parameters (frequency, amplitude). Systematic calculations have been performed for these two systems driven by parametric pumps to unveil the controllability of chaos.
Chaos control of parametric driven Duffing oscillators
NASA Astrophysics Data System (ADS)
Jin, Leisheng; Mei, Jie; Li, Lijie
2014-03-01
Duffing resonators are typical dynamic systems, which can exhibit chaotic oscillations, subject to certain driving conditions. Chaotic oscillations of resonating systems with negative and positive spring constants are identified to investigate in this paper. Parametric driver imposed on these two systems affects nonlinear behaviours, which has been theoretically analyzed with regard to variation of driving parameters (frequency, amplitude). Systematic calculations have been performed for these two systems driven by parametric pumps to unveil the controllability of chaos.
NON-PARAMETRIC ESTIMATION UNDER STRONG DEPENDENCE
Zhao, Zhibiao; Zhang, Yiyun; Li, Runze
2014-01-01
We study non-parametric regression function estimation for models with strong dependence. Compared with short-range dependent models, long-range dependent models often result in slower convergence rates. We propose a simple differencing-sequence based non-parametric estimator that achieves the same convergence rate as if the data were independent. Simulation studies show that the proposed method has good finite sample performance. PMID:25018572
Theory of Parametric Amplification in Superlattices
NASA Astrophysics Data System (ADS)
Hyart, Timo; Shorokhov, Alexey V.; Alekseev, Kirill N.
2007-06-01
We consider a high-frequency response of electrons in a single miniband of superlattice subject to dc and ac electric fields. We show that Bragg reflections in miniband result in a parametric resonance which is detectable using ac probe field. We establish theoretical feasibility of phase-sensitive THz amplification at the resonance. The parametric amplification does not require operation in conditions of negative differential conductance. This prevents a formation of destructive domains of high electric field inside the superlattice.
NON-PARAMETRIC ESTIMATION UNDER STRONG DEPENDENCE.
Zhao, Zhibiao; Zhang, Yiyun; Li, Runze
2014-01-01
We study non-parametric regression function estimation for models with strong dependence. Compared with short-range dependent models, long-range dependent models often result in slower convergence rates. We propose a simple differencing-sequence based non-parametric estimator that achieves the same convergence rate as if the data were independent. Simulation studies show that the proposed method has good finite sample performance.
Validation of two (parametric vs non-parametric) daily weather generators
NASA Astrophysics Data System (ADS)
Dubrovsky, M.; Skalak, P.
2015-12-01
As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series
On Topological Structures of Fuzzy Parametrized Soft Sets
Zorlutuna, İdris
2014-01-01
We introduce the topological structure of fuzzy parametrized soft sets and fuzzy parametrized soft mappings. We define the notion of quasi-coincidence for fuzzy parametrized soft sets and investigated its basic properties. We study the closure, interior, base, continuity, and compactness and properties of these concepts in fuzzy parametrized soft topological spaces. PMID:24955386
ERIC Educational Resources Information Center
Petocz, Peter; Sowey, Eric
2008-01-01
In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…
... of cancer on the population and to develop strategies to address the challenges that cancer poses to the society at large. Statistical trends are also important for measuring the success of efforts to control and manage cancer. Statistics at a Glance: The ...
ERIC Educational Resources Information Center
Petocz, Peter; Sowey, Eric
2008-01-01
In this article, the authors focus on hypothesis testing--that peculiarly statistical way of deciding things. Statistical methods for testing hypotheses were developed in the 1920s and 1930s by some of the most famous statisticians, in particular Ronald Fisher, Jerzy Neyman and Egon Pearson, who laid the foundations of almost all modern methods of…
Single-arm phase II trial design under parametric cure models.
Wu, Jianrong
2015-01-01
The current practice of designing single-arm phase II survival trials is limited under the exponential model. Trial design under the exponential model may not be appropriate when a portion of patients are cured. There is no literature available for designing single-arm phase II trials under the parametric cure model. In this paper, a test statistic is proposed, and a sample size formula is derived for designing single-arm phase II trials under a class of parametric cure models. Extensive simulations showed that the proposed test and sample size formula perform very well under different scenarios. Copyright © 2015 John Wiley & Sons, Ltd.
Single-Arm Phase II Trial Design Under Parametric Cure Models
Wu, Jianrong
2015-01-01
The current practice of designing single-arm phase II survival trials is limited under the exponential model. Trial design under the exponential model may not be appropriate when a portion of patients are cured. There is no literature available for designing single-arm phase II trials under the parametric cure model. In this article, a test statistic is proposed, and a sample size formula is derived for designing single-arm phase II trials under a class of parametric cure models. Extensive simulations showed that the proposed test and sample size formula perform very well under different scenarios. PMID:25846141
A general non-parametric classifier applied to discriminating surface water from terrain shadows
NASA Technical Reports Server (NTRS)
Eppler, W. G.
1975-01-01
A general non-parametric classifier is described in the context of discriminating surface water from terrain shadows. In addition to using non-parametric statistics, this classifier permits the use of a cost matrix to assign different penalties to various types of misclassifications. The approach also differs from conventional classifiers in that it applies the maximum-likelihood criterion to overall class probabilities as opposed to the standard practice of choosing the most likely individual subclass. The classifier performance is evaluated using two different effectiveness measures for a specific set of ERTS data.
Parametrizing arbitrary galaxy morphologies: potentials and pitfalls
NASA Astrophysics Data System (ADS)
Andrae, René; Jahnke, Knud; Melchior, Peter
2011-02-01
Given the enormous galaxy data bases of modern sky surveys, parametrizing galaxy morphologies is a very challenging task due to the huge number and variety of objects. We assess the different problems faced by existing parametrization schemes (CAS, Gini, M20, Sérsic profile, shapelets) in an attempt to understand why parametrization is so difficult and in order to suggest improvements for future parametrization schemes. We demonstrate that morphological observables (e.g. steepness of the radial light profile, ellipticity, asymmetry) are intertwined and cannot be measured independently of each other. We present strong arguments in favour of model-based parametrization schemes, namely reliability assessment, disentanglement of morphological observables and point spread function modelling. Furthermore, we demonstrate that estimates of the concentration and Sérsic index obtained from the Zurich Structure & Morphology catalogue are in excellent agreement with theoretical predictions. We also demonstrate that the incautious use of the concentration index for classification purposes can cause a severe loss of the discriminative information contained in a given data sample. Moreover, we show that, for poorly resolved galaxies, concentration index and M20 suffer from strong discontinuities, i.e. similar morphologies are not necessarily mapped to neighbouring points in the parameter space. This limits the reliability of these parameters for classification purposes. Two-dimensional Sérsic profiles accounting for centroid and ellipticity are identified as the currently most reliable parametrization scheme in the regime of intermediate signal-to-noise ratios and resolutions, where asymmetries and substructures do not play an important role. We argue that basis functions provide good parametrization schemes in the regimes of high signal-to-noise ratios and resolutions. Concerning Sérsic profiles, we show that scale radii cannot be compared directly for profiles of different
NASA Technical Reports Server (NTRS)
Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James
2014-01-01
Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.
Trend Analysis of Golestan's Rivers Discharges Using Parametric and Non-parametric Methods
NASA Astrophysics Data System (ADS)
Mosaedi, Abolfazl; Kouhestani, Nasrin
2010-05-01
One of the major problems in human life is climate changes and its problems. Climate changes will cause changes in rivers discharges. The aim of this research is to investigate the trend analysis of seasonal and yearly rivers discharges of Golestan province (Iran). In this research four trend analysis method including, conjunction point, linear regression, Wald-Wolfowitz and Mann-Kendall, for analyzing of river discharges in seasonal and annual periods in significant level of 95% and 99% were applied. First, daily discharge data of 12 hydrometrics stations with a length of 42 years (1965-2007) were selected, after some common statistical tests such as, homogeneity test (by applying G-B and M-W tests), the four mentioned trends analysis tests were applied. Results show that in all stations, for summer data time series, there are decreasing trends with a significant level of 99% according to Mann-Kendall (M-K) test. For autumn time series data, all four methods have similar results. For other periods, the results of these four tests were more or less similar together. While, for some stations the results of tests were different. Keywords: Trend Analysis, Discharge, Non-parametric methods, Wald-Wolfowitz, The Mann-Kendall test, Golestan Province.
... population, or about 25 million Americans, has experienced tinnitus lasting at least five minutes in the past ... by NIDCD Epidemiology and Statistics Program staff: (1) tinnitus prevalence was obtained from the 2008 National Health ...
Fiber-optic parametric amplifier and oscillator based on intracavity parametric pump technique.
Luo, Zhengqian; Zhong, Wen-De; Tang, Ming; Cai, Zhiping; Ye, Chenchun; Xiao, Xiaosheng
2009-01-15
A cost-effective fiber optical parametric amplifier (FOPA) based on the laser intracavity pump technique has been proposed and demonstrated experimentally. The parametric process is realized by inserting a 1 km highly nonlinear dispersion-shifted fiber (HNL-DSF) into a fiber ring-laser cavity that consists of a high-power erbium-doped fiber (EDF) amplifier and two highly reflective fiber Bragg gratings. Compared with the conventional parametric pump schemes, the proposed pumping technique is free from a tunable semiconductor laser as the pump source and also the pump phase modulation. When the oscillating power of 530 mW in the EDF laser cavity is achieved to pump the HNL-DSF, a peak parametric gain of 27.5 dB and a net gain over 45 nm are obtained. Moreover, a widely tunable fiber-optic parametric oscillator is further developed using the FOPA as a gain medium.
Parametric instability of pressurized propellant tanks
NASA Astrophysics Data System (ADS)
Albus, Jochen; Dieker, Stefan; Őry, Huba; Rittweger, Andreas
2008-01-01
Pressurized propellant tanks might become dynamically unstable with detrimental dynamic responses if a dynamic excitation leads to a coupling of pressure oscillations (especially due to the response of axisymmetric modes) with very low damped ovalizing modes. This phenomenon can be described and identified as the so-called parametric instability. During the dynamic qualification test campaign of the new Ariane 5 Cryogenic Upper Stage ESC-A, a parametric instability was observed for sinusoidal tests under certain test conditions with low static pressure in the propellant tank. The parametric instability was identified and an analytical simulation was performed that confirmed the instability. During flight, harmonic excitations might occur due to pressure oscillations within the solid rocket booster. However, the application of the analytical model on flight conditions indicates that the flight behaviour will be stable. This was confirmed by results from additional tests. This paper describes the phenomenon of the parametric instability of pressurized propellant tanks and presents an analytical methodology to assess the risk of the occurrence of a parametric instability.
Optimization of noncollinear optical parametric amplification
NASA Astrophysics Data System (ADS)
Schimpf, D. N.; Rothardt, J.; Limpert, J.; Tünnermann, A.
2007-02-01
Noncollinearly phase-matched optical parametric amplifiers (NOPAs) - pumped with the green light of a frequency doubled Yb-doped fiber-amplifier system 1, 2 - permit convenient generation of ultrashort pulses in the visible (VIS) and near infrared (NIR) 3. The broad bandwidth of the parametric gain via the noncollinear pump configuration allows amplification of few-cycle optical pulses when seeded with a spectrally flat, re-compressible signal. The short pulses tunable over a wide region in the visible permit transcend of frontiers in physics and lifescience. For instance, the resulting high temporal resolution is of significance for many spectroscopic techniques. Furthermore, the high magnitudes of the peak-powers of the produced pulses allow research in high-field physics. To understand the demands of noncollinear optical parametric amplification using a fiber pump source, it is important to investigate this configuration in detail 4. An analysis provides not only insight into the parametric process but also determines an optimal choice of experimental parameters for the objective. Here, the intention is to design a configuration which yields the shortest possible temporal pulse. As a consequence of this analysis, the experimental setup could be optimized. A number of aspects of optical parametric amplifier performance have been treated analytically and computationally 5, but these do not fully cover the situation under consideration here.
Grating lobe elimination in steerable parametric loudspeaker.
Shi, Chuang; Gan, Woon-Seng
2011-02-01
In the past two decades, the majority of research on the parametric loudspeaker has concentrated on the nonlinear modeling of acoustic propagation and pre-processing techniques to reduce nonlinear distortion in sound reproduction. There are, however, very few studies on directivity control of the parametric loudspeaker. In this paper, we propose an equivalent circular Gaussian source array that approximates the directivity characteristics of the linear ultrasonic transducer array. By using this approximation, the directivity of the sound beam from the parametric loudspeaker can be predicted by the product directivity principle. New theoretical results, which are verified through measurements, are presented to show the effectiveness of the delay-and-sum beamsteering structure for the parametric loudspeaker. Unlike the conventional loudspeaker array, where the spacing between array elements must be less than half the wavelength to avoid spatial aliasing, the parametric loudspeaker can take advantage of grating lobe elimination to extend the spacing of ultrasonic transducer array to more than 1.5 wavelengths in a typical application.
Parametric wavelength conversion in photonic crystal fibers
NASA Astrophysics Data System (ADS)
Yang, Sigang; Wu, Zhaohui; Yang, Yi; Chen, Minghua; Xie, Shizhong
2016-11-01
Nonlinear wavelength conversion provides flexible solutions for generating wideband tunable radiation in novel wavelength band. Parametric process in photonic crystal fibers (PCFs) has attracted comprehensive interests since it can act as broadband tunable light sources in non-conventional wavelength bands. The current state-of-the-art photonic crystal fibers can provide more freedom for customizing the dispersion and nonlinearity which is critical to the nonlinear process, such as four wave mixing (FWM), compared with the traditional fibers fabricated with doping techniques. Here we demonstrate broadband parametric wavelength conversion in our homemade photonic crystal fibers. The zero dispersion wavelength (ZDW) of PCFs is critical for the requirement of phase matching condition in the parametric four wave mixing process. Firstly a procedure of the theoretical design of PCF with the ZDW at 1060 nm is proposed through our homemade simulation software. A group of PCF samples with gradually variable parameters are fabricated according to the theoretical design. The broadband parametric gain around 1060 nm band is demonstrated pumped with our homemade mode locked fiber laser in the anomalous dispersion region. Also a narrow gain band with very large wavelength detune with the pump wavelength in the normal dispersion region is realized. Wavelength conversion with a span of 194 nm is realized. Furthermore a fiber optical parametric oscillator based on the fabricated PCF is built up. A wavelength tunable range as high as 340 nm is obtained. This report demonstrates a systematic procedure to realize wide band wavelength conversion based on PCFs.
Phase noise suppression through parametric filtering
NASA Astrophysics Data System (ADS)
Cassella, Cristian; Strachan, Scott; Shaw, Steven W.; Piazza, Gianluca
2017-02-01
In this work, we introduce and experimentally demonstrate a parametric phase noise suppression technique, which we call "parametric phase noise filtering." This technique is based on the use of a solid-state parametric amplifier operating in its instability region and included in a non-autonomous feedback loop connected at the output of a noisy oscillator. We demonstrate that such a system behaves as a parametrically driven Duffing resonator and can operate at special points where it becomes largely immune to the phase fluctuations that affect the oscillator output signal. A prototype of a parametric phase noise filter (PFIL) was designed and fabricated to operate in the very-high-frequency range. The PFIL prototype allowed us to significantly reduce the phase noise at the output of a commercial signal generator operating around 220 MHz. Noise reduction of 16 dB (40×) and 13 dB (20×) were obtained, respectively, at 1 and 10 kHz offsets from the carrier frequency. The demonstration of this phase noise suppression technique opens up scenarios in the development of passive and low-cost phase noise cancellation circuits for any application demanding high quality frequency generation.
Lan, Ling; Datta, Somnath
2010-04-01
As a type of multivariate survival data, multistate models have a wide range of applications, notably in cancer and infectious disease progression studies. In this article, we revisit the problem of estimation of state occupation, entry and exit times in a multistate model where various estimators have been proposed in the past under a variety of parametric and non-parametric assumptions. We focus on two non-parametric approaches, one using a product limit formula as recently proposed in Datta and Sundaram(1) and a novel approach using a fractional risk set calculation followed by a subtraction formula to calculate the state occupation probability of a transient state. A numerical comparison between the two methods is presented using detailed simulation studies. We show that the new estimators have lower statistical errors of estimation of state occupation probabilities for the distant states. We illustrate the two methods using a pubertal development data set obtained from the NHANES III.(2).
Non-parametric morphologies of mergers in the Illustris simulation
NASA Astrophysics Data System (ADS)
Bignone, L. A.; Tissera, P. B.; Sillero, E.; Pedrosa, S. E.; Pellizza, L. J.; Lambas, D. G.
2017-02-01
We study non-parametric morphologies of mergers events in a cosmological context, using the Illustris project. We produce mock g-band images comparable to observational surveys from the publicly available Illustris simulation idealized mock images at z = 0. We then measure non-parametric indicators: asymmetry, Gini, M20, clumpiness, and concentration for a set of galaxies with M* > 1010 M⊙. We correlate these automatic statistics with the recent merger history of galaxies and with the presence of close companions. Our main contribution is to assess in a cosmological framework, the empirically derived non-parametric demarcation line and average time-scales used to determine the merger rate observationally. We found that 98 per cent of galaxies above the demarcation line have a close companion or have experienced a recent merger event. On average, merger signatures obtained from the G-M20 criterion anti-correlate clearly with the elapsing time to the last merger event. We also find that the asymmetry correlates with galaxy pair separation and relative velocity, exhibiting the larger enhancements for those systems with pair separations d < 50 h-1 kpc and relative velocities V < 350 km s-1. We find that the G-M20 is most sensitive to recent mergers (∼0.14 Gyr) and to ongoing mergers with stellar mass ratios greater than 0.1. For this indicator, we compute a merger average observability time-scale of ∼0.2 Gyr, in agreement with previous results and demonstrate that the morphologically derived merger rate recovers the intrinsic total merger rate of the simulation and the merger rate as a function of stellar mass.
Ku band low noise parametric amplifier
NASA Technical Reports Server (NTRS)
1976-01-01
A low noise, K sub u-band, parametric amplifier (paramp) was developed. The unit is a spacecraft-qualifiable, prototype, parametric amplifier for eventual application in the shuttle orbiter. The amplifier was required to have a noise temperature of less than 150 K. A noise temperature of less than 120 K at a gain level of 17 db was achieved. A 3-db bandwidth in excess of 350 MHz was attained, while deviation from phase linearity of about + or - 1 degree over 50 MHz was achieved. The paramp operates within specification over an ambient temperature range of -5 C to +50 C. The performance requirements and the operation of the K sub u-band parametric amplifier system are described. The final test results are also given.
Parametric modelling of a knee joint prosthesis.
Khoo, L P; Goh, J C; Chow, S L
1993-01-01
This paper presents an approach for the establishment of a parametric model of knee joint prosthesis. Four different sizes of a commercial prosthesis are used as an example in the study. A reverse engineering technique was employed to reconstruct the prosthesis on CATIA, a CAD (computer aided design) system. Parametric models were established as a result of the analysis. Using the parametric model established and the knee data obtained from a clinical study on 21 pairs of cadaveric Asian knees, the development of a prototype prosthesis that suits a patient with a very small knee joint is presented. However, it was found that modification to certain parameters may be inevitable due to the uniqueness of the Asian knee. An avenue for rapid modelling and eventually economical production of a customized knee joint prosthesis for patients is proposed and discussed.
Modeling personnel turnover in the parametric organization
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1991-01-01
A model is developed for simulating the dynamics of a newly formed organization, credible during all phases of organizational development. The model development process is broken down into the activities of determining the tasks required for parametric cost analysis (PCA), determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the model, implementing the model, and testing it. The model, parameterized by the likelihood of job function transition, has demonstrated by the capability to represent the transition of personnel across functional boundaries within a parametric organization using a linear dynamical system, and the ability to predict required staffing profiles to meet functional needs at the desired time. The model can be extended by revisions of the state and transition structure to provide refinements in functional definition for the parametric and extended organization.
Modeling personnel turnover in the parametric organization
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1991-01-01
A model is developed for simulating the dynamics of a newly formed organization, credible during all phases of organizational development. The model development process is broken down into the activities of determining the tasks required for parametric cost analysis (PCA), determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the model, implementing the model, and testing it. The model, parameterized by the likelihood of job function transition, has demonstrated by the capability to represent the transition of personnel across functional boundaries within a parametric organization using a linear dynamical system, and the ability to predict required staffing profiles to meet functional needs at the desired time. The model can be extended by revisions of the state and transition structure to provide refinements in functional definition for the parametric and extended organization.
Ince-Strutt stability charts for ship parametric roll resonance in irregular waves
NASA Astrophysics Data System (ADS)
Zhang, Xiao; Yang, He-zhen; Xiao, Fei; Xu, Pei-ji
2017-08-01
Ince-Strutt stability chart of ship parametric roll resonance in irregular waves is conducted and utilized for the exploration of the parametric roll resonance in irregular waves. Ship parametric roll resonance will lead to large amplitude roll motion and even wreck. Firstly, the equation describing the parametric roll resonance in irregular waves is derived according to Grim's effective theory and the corresponding Ince-Strutt stability charts are obtained. Secondly, the differences of stability charts for the parametric roll resonance in irregular and regular waves are compared. Thirdly, wave phases and peak periods are taken into consideration to obtain a more realistic sea condition. The influence of random wave phases should be taken into consideration when the analyzed points are located near the instability boundary. Stability charts for different wave peak periods are various. Stability charts are helpful for the parameter determination in design stage to better adapt to sailing condition. Last, ship variables are analyzed according to stability charts by a statistical approach. The increase of the metacentric height will help improve ship stability.
Adaptive Parametric Spectral Estimation with Kalman Smoothing for Online Early Seizure Detection
Park, Yun S.; Hochberg, Leigh R.; Eskandar, Emad N.; Cash, Sydney S.; Truccolo, Wilson
2014-01-01
Tracking spectral changes in neural signals, such as local field potentials (LFPs) and scalp or intracranial electroencephalograms (EEG, iEEG), is an important problem in early detection and prediction of seizures. Most approaches have focused on either parametric or nonparametric spectral estimation methods based on moving time windows. Here, we explore an adaptive (time-varying) parametric ARMA approach for tracking spectral changes in neural signals based on the fixed-interval Kalman smoother. We apply the method to seizure detection based on spectral features of intracortical LFPs recorded from a person with pharmacologically intractable focal epilepsy. We also devise and test an approach for real-time tracking of spectra based on the adaptive parametric method with the fixed-interval Kalman smoother. The order of ARMA models is determined via the AIC computed in moving time windows. We quantitatively demonstrate the advantages of using the adaptive parametric estimation method in seizure detection over nonparametric alternatives based exclusively on moving time windows. Overall, the adaptive parametric approach significantly improves the statistical separability of interictal and ictal epochs. PMID:24663686
Use of robust estimators in parametric classifiers
NASA Technical Reports Server (NTRS)
Safavian, S. Rasoul; Landgrebe, David A.
1989-01-01
The parametric approach to density estimation and classifier design is a well studied subject. The parametric approach is desirable because basically it reduces the problem of classifier design to that of estimating a few parameters for each of the pattern classes. The class parameters are usually estimated using maximum-likelihood (ML) estimators. ML estimators are, however, very sensitive to the presence of outliers. Several robust estimators of mean and covariance matrix and their effect on the probability of error in classification are examined. Comments are made about alpha-ranked (alpha-trimmed) estimators.
Parametric number covariance in quantum chaotic spectra.
Vinayak; Kumar, Sandeep; Pandey, Akhilesh
2016-03-01
We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.
Use of robust estimators in parametric classifiers
NASA Technical Reports Server (NTRS)
Safavian, S. Rasoul; Landgrebe, David A.
1989-01-01
The parametric approach to density estimation and classifier design is a well studied subject. The parametric approach is desirable because basically it reduces the problem of classifier design to that of estimating a few parameters for each of the pattern classes. The class parameters are usually estimated using maximum-likelihood (ML) estimators. ML estimators are, however, very sensitive to the presence of outliers. Several robust estimators of mean and covariance matrix and their effect on the probability of error in classification are examined. Comments are made about alpha-ranked (alpha-trimmed) estimators.
Modern Robust Statistical Methods: An Easy Way to Maximize the Accuracy and Power of Your Research
ERIC Educational Resources Information Center
Erceg-Hurn, David M.; Mirosevich, Vikki M.
2008-01-01
Classic parametric statistical significance tests, such as analysis of variance and least squares regression, are widely used by researchers in many disciplines, including psychology. For classic parametric tests to produce accurate results, the assumptions underlying them (e.g., normality and homoscedasticity) must be satisfied. These assumptions…
A Comparison of Parametric and Non-Parametric Methods Applied to a Likert Scale.
Mircioiu, Constantin; Atkinson, Jeffrey
2017-05-10
A trenchant and passionate dispute over the use of parametric versus non-parametric methods for the analysis of Likert scale ordinal data has raged for the past eight decades. The answer is not a simple "yes" or "no" but is related to hypotheses, objectives, risks, and paradigms. In this paper, we took a pragmatic approach. We applied both types of methods to the analysis of actual Likert data on responses from different professional subgroups of European pharmacists regarding competencies for practice. Results obtained show that with "large" (>15) numbers of responses and similar (but clearly not normal) distributions from different subgroups, parametric and non-parametric analyses give in almost all cases the same significant or non-significant results for inter-subgroup comparisons. Parametric methods were more discriminant in the cases of non-similar conclusions. Considering that the largest differences in opinions occurred in the upper part of the 4-point Likert scale (ranks 3 "very important" and 4 "essential"), a "score analysis" based on this part of the data was undertaken. This transformation of the ordinal Likert data into binary scores produced a graphical representation that was visually easier to understand as differences were accentuated. In conclusion, in this case of Likert ordinal data with high response rates, restraining the analysis to non-parametric methods leads to a loss of information. The addition of parametric methods, graphical analysis, analysis of subsets, and transformation of data leads to more in-depth analyses.
NASA Astrophysics Data System (ADS)
Prakash, Gyan; Raman, Arvind; Rhoads, Jeffrey; Reifenberger, Ronald G.
2012-06-01
In this work, parametric noise squeezing and parametric resonance are realized through the use of an electronic feedback circuit to excite a microcantilever with a signal proportional to the product of the microcantilever's displacement and a harmonic signal. The cantilever's displacement is monitored using an optical lever technique. By adjusting the gain of an amplifier in the feedback circuit, regimes of parametric noise squeezing/amplification and the principal and secondary parametric resonances of fundamental and higher order eigenmodes can be easily accessed. The exceptionally symmetric amplitude response of the microcantilever in the narrow frequency bandwidth is traced to a nonlinear parametric excitation term that arises due to the cubic nonlinearity in the output of the position-sensitive photodiode. The feedback circuit, working in both the regimes of parametric resonance and noise squeezing, allows an enhancement of the microcantilever's effective quality-factor (Q-factor) by two orders of magnitude under ambient conditions, extending the mass sensing capabilities of a conventional microcantilever into the sub-picogram regime. Likewise, experiments designed to parametrically oscillate a microcantilever in water using electronic feedback also show an increase in the microcantilever's effective Q-factor by two orders of magnitude, opening the field to high-sensitivity mass sensing in liquid environments.
Prakash, Gyan; Raman, Arvind; Rhoads, Jeffrey; Reifenberger, Ronald G
2012-06-01
In this work, parametric noise squeezing and parametric resonance are realized through the use of an electronic feedback circuit to excite a microcantilever with a signal proportional to the product of the microcantilever's displacement and a harmonic signal. The cantilever's displacement is monitored using an optical lever technique. By adjusting the gain of an amplifier in the feedback circuit, regimes of parametric noise squeezing/amplification and the principal and secondary parametric resonances of fundamental and higher order eigenmodes can be easily accessed. The exceptionally symmetric amplitude response of the microcantilever in the narrow frequency bandwidth is traced to a nonlinear parametric excitation term that arises due to the cubic nonlinearity in the output of the position-sensitive photodiode. The feedback circuit, working in both the regimes of parametric resonance and noise squeezing, allows an enhancement of the microcantilever's effective quality-factor (Q-factor) by two orders of magnitude under ambient conditions, extending the mass sensing capabilities of a conventional microcantilever into the sub-picogram regime. Likewise, experiments designed to parametrically oscillate a microcantilever in water using electronic feedback also show an increase in the microcantilever's effective Q-factor by two orders of magnitude, opening the field to high-sensitivity mass sensing in liquid environments.
Huang, Xinrui; Zhou, Yun; Bao, Shangliang; Huang, Sung-Cheng
2007-01-01
Parametric images generated from dynamic positron emission tomography (PET) studies are useful for presenting functional/biological information in the 3-dimensional space, but usually suffer from their high sensitivity to image noise. To improve the quality of these images, we proposed in this study a modified linear least square (LLS) fitting method named cLLS that incorporates a clustering-based spatial constraint for generation of parametric images from dynamic PET data of high noise levels. In this method, the combination of K-means and hierarchical cluster analysis was used to classify dynamic PET data. Compared with conventional LLS, cLLS can achieve high statistical reliability in the generated parametric images without incurring a high computational burden. The effectiveness of the method was demonstrated both with computer simulation and with a human brain dynamic FDG PET study. The cLLS method is expected to be useful for generation of parametric images from dynamic FDG PET study. PMID:18273393
Parametric plate-bridge dynamic filter model of violin radiativity.
Bissinger, George
2012-07-01
A hybrid, deterministic-statistical, parametric "dynamic filter" model of the violin's radiativity profile [characterized by an averaged-over-sphere, mean-square radiativity (R(ω)(2))] is developed based on the premise that acoustic radiation depends on (1) how strongly it vibrates [characterized by the averaged-over-corpus, mean-square mobility (Y(ω)(2))] and (2) how effectively these vibrations are turned into sound, characterized by the radiation efficiency, which is proportional to (R(ω)(2))/(Y(ω)(2)). Two plate mode frequencies were used to compute 1st corpus bending mode frequencies using empirical trend lines; these corpus bending modes in turn drive cavity volume flows to excite the two lowest cavity modes A0 and A1. All widely-separated, strongly-radiating corpus and cavity modes in the low frequency deterministic region are then parameterized in a dual-Helmholtz resonator model. Mid-high frequency statistical regions are parameterized with the aid of a distributed-excitation statistical mobility function (no bridge) to help extract bridge filter effects associated with (a) bridge rocking mode frequency changes and (b) bridge-corpus interactions from 14-violin-average, excited-via-bridge (Y(ω)(2)) and (R(ω)(2)). Deterministic-statistical regions are rejoined at ~630 Hz in a mobility-radiativity "trough" where all violin quality classes had a common radiativity. Simulations indicate that typical plate tuning has a significantly weaker effect on radiativity profile trends than bridge tuning.
ERIC Educational Resources Information Center
Catley, Alan
2007-01-01
Following the announcement last year that there will be no more math coursework assessment at General Certificate of Secondary Education (GCSE), teachers will in the future be able to devote more time to preparing learners for formal examinations. One of the key things that the author has learned when teaching statistics is that it makes for far…
ERIC Educational Resources Information Center
Chicot, Katie; Holmes, Hilary
2012-01-01
The use, and misuse, of statistics is commonplace, yet in the printed format data representations can be either over simplified, supposedly for impact, or so complex as to lead to boredom, supposedly for completeness and accuracy. In this article the link to the video clip shows how dynamic visual representations can enliven and enhance the…
Quantifying parametric uncertainty in the Rothermel model
S. Goodrick
2008-01-01
The purpose of the present work is to quantify parametric uncertainty in the Rothermel wildland fire spreadmodel (implemented in software such as fire spread models in the United States. This model consists of a non-linear system of equations that relates environmentalvariables (input parameter groups...
Noise figure of hybrid optical parametric amplifiers.
Marhic, Michel E
2012-12-17
Following a fiber optical parametric amplifier, used as a wavelength converter or in the phase-sensitive mode, by a phase-insensitive amplifier (PIA) can significantly reduce four-wave mixing between signals in broadband systems. We derive the quantum mechanical noise figures (NF) for these two hybrid configurations, and show that adding the PIA only leads to a moderate increase in NF.
New Logic Circuit with DC Parametric Excitation
NASA Astrophysics Data System (ADS)
Sugahara, Masanori; Kaneda, Hisayoshi
1982-12-01
It is shown that dc parametric excitation is possible in a circuit named JUDO, which is composed of two resistively-connected Josephson junctions. Simulation study proves that the circuit has large gain and properties suitable for the construction of small, high-speed logic circuits.
Holographic Dark Energy Density and JBP Parametrization
NASA Astrophysics Data System (ADS)
Saadat, Hassan; Mousavi, S. N.; Saadat, A. M.
2011-09-01
In this article we consider the holographic dark energy density. We study dark energy density in Universe with arbitrary spatially curvature described by the Friedmann-Robertson-Walker metric. We use Jassal-Bagla-Padmanabhan parametrization to specify dark energy density.
Parametric Oscillations in High Power Microwave Amplifiers.
1979-01-01
report. I j I 1 1) G. Dohler, Parametric Oscillations in High Power Microwave Amplifiers, L Contract No. F49620-77-C-O0 (1979). 2) O. Doehler B. Dohler...IEEE Transactions on Electron Devices, ED 26(10),[ 1602 (19795. 3) 0. Doehler , G. Dohler, International Electron Devices Meeting, I Washington, D.C
A parametric reconstruction of the deceleration parameter
NASA Astrophysics Data System (ADS)
Mamon, Abdulla Al; Das, Sudipta
2017-07-01
The present work is based on a parametric reconstruction of the deceleration parameter q( z) in a model for the spatially flat FRW universe filled with dark energy and non-relativistic matter. In cosmology, the parametric reconstruction technique deals with an attempt to build up a model by choosing some specific evolution scenario for a cosmological parameter and then estimate the values of the parameters with the help of different observational datasets. In this paper, we have proposed a logarithmic parametrization of q( z) to probe the evolution history of the universe. Using the type Ia supernova, baryon acoustic oscillation and the cosmic microwave background datasets, the constraints on the arbitrary model parameters q0 and q1 are obtained (within 1σ and 2σ confidence limits) by χ 2-minimization technique. We have then reconstructed the deceleration parameter, the total EoS parameter ω _tot, the jerk parameter and have compared the reconstructed results of q( z) with other well-known parametrizations of q( z). We have also shown that two model selection criteria (namely, the Akaike information criterion and Bayesian information criterion) provide a clear indication that our reconstructed model is well consistent with other popular models.
The fast parametric slantlet transform with applications
NASA Astrophysics Data System (ADS)
Agaian, Sos S.; Tourshan, Khaled; Noonan, Joseph P.
2004-05-01
Transform methods have played an important role in signal and image processing applications. Recently, Selesnick has constructed the new orthogonal discrete wavelet transform, called the slantlet wavelet, with two zero moments and with improved time localization. The discrete slantlet wavelet transform is carried out by an existing filterbank which lacks a tree structure and has a complexity problem. The slantlet wavelet has been successfully applied in compression and denoising. In this paper, we present a new class of orthogonal parametric fast Haar slantlet transform system where the slantlet wavelet and Haar transforms are special cases of it. We propose designing the slantlet wavelet transform using Haar slantlet transform matrix. A new class of parametric filterbanks is developed. The behavior of the parametric Haar slantlet transforms in signal and image denoising is presented. We show that the new technique performs better than the slantlet wavelet transform in denoising for piecewise constant signals. We also show that the parametric Haar slantlet transform performs better than the cosine and Fourier transforms for grey level images.
Robustness analysis for real parametric uncertainty
NASA Technical Reports Server (NTRS)
Sideris, Athanasios
1989-01-01
Some key results in the literature in the area of robustness analysis for linear feedback systems with structured model uncertainty are reviewed. Some new results are given. Model uncertainty is described as a combination of real uncertain parameters and norm bounded unmodeled dynamics. Here the focus is on the case of parametric uncertainty. An elementary and unified derivation of the celebrated theorem of Kharitonov and the Edge Theorem is presented. Next, an algorithmic approach for robustness analysis in the cases of multilinear and polynomic parametric uncertainty (i.e., the closed loop characteristic polynomial depends multilinearly and polynomially respectively on the parameters) is given. The latter cases are most important from practical considerations. Some novel modifications in this algorithm which result in a procedure of polynomial time behavior in the number of uncertain parameters is outlined. Finally, it is shown how the more general problem of robustness analysis for combined parametric and dynamic (i.e., unmodeled dynamics) uncertainty can be reduced to the case of polynomic parametric uncertainty, and thus be solved by means of the algorithm.
Statistical description for survival data
2016-01-01
Statistical description is always the first step in data analysis. It gives investigator a general impression of the data at hand. Traditionally, data are described as central tendency and deviation. However, this framework does not fit to the survival data (also termed time-to-event data). Such data type contains two components. One is the survival time and the other is the status. Researchers are usually interested in the probability of event at a given survival time point. Hazard function, cumulative hazard function and survival function are commonly used to describe survival data. Survival function can be estimated using Kaplan-Meier estimator, which is also the default method in most statistical packages. Alternatively, Nelson-Aalen estimator is available to estimate survival function. Survival functions of subgroups can be compared using log-rank test. Furthermore, the article also introduces how to describe time-to-event data with parametric modeling. PMID:27867953
Statistical Methods for Cardiovascular Researchers
Moyé, Lem
2016-01-01
Rationale Biostatistics continues to play an essential role in contemporary cardiovascular investigations, but successful implementation of biostatistical methods can be complex. Objective To present the rationale behind statistical applications and to review useful tools for cardiology research. Methods and Results Prospective declaration of the research question, clear methodology, and study execution that adheres to the protocol together serve as the critical foundation of a research endeavor. Both parametric and distribution-free measures of central tendency and dispersion are presented. T-testing, analysis of variance, and regression analyses are reviewed. Survival analysis, logistic regression, and interim monitoring are also discussed. Finally, common weaknesses in statistical analyses are considered. Conclusion Biostatistics can be productively applied to cardiovascular research if investigators 1) develop and rely on a well-written protocol and analysis plan, 2) consult with a biostatistician when necessary, and 3) write results clearly, differentiating confirmatory from exploratory findings. PMID:26846639
Parametric and experimental analysis using a power flow approach
NASA Technical Reports Server (NTRS)
Cuschieri, J. M.
1990-01-01
A structural power flow approach for the analysis of structure-borne transmission of vibrations is used to analyze the influence of structural parameters on transmitted power. The parametric analysis is also performed using the Statistical Energy Analysis approach and the results are compared with those obtained using the power flow approach. The advantages of structural power flow analysis are demonstrated by comparing the type of results that are obtained by the two analytical methods. Also, to demonstrate that the power flow results represent a direct physical parameter that can be measured on a typical structure, an experimental study of structural power flow is presented. This experimental study presents results for an L shaped beam for which an available solution was already obtained. Various methods to measure vibrational power flow are compared to study their advantages and disadvantages.
Parametric acoustic arrays: A state of the art review
NASA Technical Reports Server (NTRS)
Fenlon, F. H.
1976-01-01
Following a brief introduction to the concept of parametric acoustic interactions, the basic properties of parametric transmitting and receiving arrays are considered in the light of conceptual advances resulting from experimental and theoretical investigations that have taken place since 1963.
Rendón-Macías, Mario Enrique; Villasís-Keever, Miguel Ángel; Miranda-Novales, María Guadalupe
2016-01-01
Descriptive statistics is the branch of statistics that gives recommendations on how to summarize clearly and simply research data in tables, figures, charts, or graphs. Before performing a descriptive analysis it is paramount to summarize its goal or goals, and to identify the measurement scales of the different variables recorded in the study. Tables or charts aim to provide timely information on the results of an investigation. The graphs show trends and can be histograms, pie charts, "box and whiskers" plots, line graphs, or scatter plots. Images serve as examples to reinforce concepts or facts. The choice of a chart, graph, or image must be based on the study objectives. Usually it is not recommended to use more than seven in an article, also depending on its length.
NASA Astrophysics Data System (ADS)
Goodman, Joseph W.
2000-07-01
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I RIchard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research
Order Statistics and Nonparametric Statistics.
2014-09-26
Topics investigated include the following: Probability that a fuze will fire; moving order statistics; distribution theory and properties of the...problem posed by an Army Scientist: A fuze will fire when at least n-i (or n-2) of n detonators function within time span t. What is the probability of
Parametric Acoustic Receiving Array (Parray) Research and Experiments.
1980-02-06
AD-AC83 704 TEXAS UNIV AT AUSTIN APPLIED RESEARCH LABS FIG 17/1 PARAMETRIC ACOUSTIC RECEIVING ARRAY ( PARRAY ) RESEARCH AND EXPER-CTC(U) FEB 80 T G...TITLE anld Subtitle) ,__t, I -1rilUl tT :. 40441" ,APT19* .... ,. L PARAMETRIC ACOUSTIC RECEIVING ARRAY ( PARRAY ) inal technical re. m , LIESEARCH AND...WORDS (Continue on reverse side it necaesary and Identify by block number) PARRAY parametric acoustic receiver nonlinear acoustics parametric acoustic
Hyperbolic and semi-parametric models in finance
NASA Astrophysics Data System (ADS)
Bingham, N. H.; Kiesel, Rüdiger
2001-02-01
The benchmark Black-Scholes-Merton model of mathematical finance is parametric, based on the normal/Gaussian distribution. Its principal parametric competitor, the hyperbolic model of Barndorff-Nielsen, Eberlein and others, is briefly discussed. Our main theme is the use of semi-parametric models, incorporating the mean vector and covariance matrix as in the Markowitz approach, plus a non-parametric part, a scalar function incorporating features such as tail-decay. Implementation is also briefly discussed.
Unifying framework for decomposition models of parametric and non-parametric image registration
NASA Astrophysics Data System (ADS)
Ibrahim, Mazlinda; Chen, Ke
2017-08-01
Image registration aims to find spatial transformations such that the so-called given template image becomes similar in some sense to the reference image. Methods in image registration can be divided into two classes (parametric or non-parametric) based on the degree of freedom of the given method. In parametric image registration, the transformation is governed by a finite set of image features or by expanding the transformation in terms of basis functions. Meanwhile, in non-parametric image registration, the problem is modelled as a functional minimisation problem via the calculus of variations. In this paper, we provide a unifying framework for decomposition models for image registration which combine parametric and non-parametric models. Several variants of the models are presented with focus on the affine, diffusion and linear curvature models. An effective numerical solver is provided for the models as well as experimental results to show the effectiveness, robustness and accuracy of the models. The decomposition model of affine and linear curvature outperforms the competing models based on tested images.
Shaikh, Masood Ali
2016-04-01
Statistical tests help infer meaningful conclusions from studies conducted and data collected. This descriptive study analyzed the type of statistical tests used and the statistical software utilized for analysis reported in the original articles published in 2014 by the three Medline-indexed journals of Pakistan. Cumulatively, 466 original articles were published in 2014. The most frequently reported statistical tests for original articles by all three journals were bivariate parametric and non-parametric tests i.e. involving comparisons between two groups e.g. Chi-square test, t-test, and various types of correlations. Cumulatively, 201 (43.1%) articles used these tests. SPSS was the primary choice for statistical analysis, as it was exclusively used in 374 (80.3%) original articles. There has been a substantial increase in the number of articles published, and in the sophistication of statistical tests used in the articles published in the Pakistani Medline indexed journals in 2014, compared to 2007.
Parametrization of the precipitation in the Northern Hemisphere and its verification in Mexico
NASA Astrophysics Data System (ADS)
Mendoza, V. M.; Oda, B.; Adem, J.
1998-07-01
To improve results in monthly rainfall prediction, a parametrization of precipitation has been developed. The thermodynamic energy equation used in the Adem thermodynamic model (ATM) and the Clausius and Clapeyron equation, were used to obtain a linear parametrization of the precipitation anomalies as a function of the surface temperature and the 700 mb temperature anomalies. The observed rainfall in Mexico over 36 months, from January 1981 to December 1983, was compared with the results obtained of the heat released by condensation, which is proportional to precipitation, using our theoretical formula, and those obtained using a statistical formula, which was derived for the ATM using 12 years of hemispheric real data. The verification using our formula in Mexico, showed better results than the one using the statistical formula.
Data-based stochastic subgrid-scale parametrization: an approach using cluster-weighted modelling.
Kwasniok, Frank
2012-03-13
A new approach for data-based stochastic parametrization of unresolved scales and processes in numerical weather and climate prediction models is introduced. The subgrid-scale model is conditional on the state of the resolved scales, consisting of a collection of local models. A clustering algorithm in the space of the resolved variables is combined with statistical modelling of the impact of the unresolved variables. The clusters and the parameters of the associated subgrid models are estimated simultaneously from data. The method is implemented and explored in the framework of the Lorenz '96 model using discrete Markov processes as local statistical models. Performance of the cluster-weighted Markov chain scheme is investigated for long-term simulations as well as ensemble prediction. It clearly outperforms simple parametrization schemes and compares favourably with another recently proposed subgrid modelling scheme also based on conditional Markov chains.
Using scientifically and statistically sufficient statistics in comparing image segmentations.
Chi, Yueh-Yun; Muller, Keith E
2010-01-01
Automatic computer segmentation in three dimensions creates opportunity to reduce the cost of three-dimensional treatment planning of radiotherapy for cancer treatment. Comparisons between human and computer accuracy in segmenting kidneys in CT scans generate distance values far larger in number than the number of CT scans. Such high dimension, low sample size (HDLSS) data present a grand challenge to statisticians: how do we find good estimates and make credible inference? We recommend discovering and using scientifically and statistically sufficient statistics as an additional strategy for overcoming the curse of dimensionality. First, we reduced the three-dimensional array of distances for each image comparison to a histogram to be modeled individually. Second, we used non-parametric kernel density estimation to explore distributional patterns and assess multi-modality. Third, a systematic exploratory search for parametric distributions and truncated variations led to choosing a Gaussian form as approximating the distribution of a cube root transformation of distance. Fourth, representing each histogram by an individually estimated distribution eliminated the HDLSS problem by reducing on average 26,000 distances per histogram to just 2 parameter estimates. In the fifth and final step we used classical statistical methods to demonstrate that the two human observers disagreed significantly less with each other than with the computer segmentation. Nevertheless, the size of all disagreements was clinically unimportant relative to the size of a kidney. The hierarchal modeling approach to object-oriented data created response variables deemed sufficient by both the scientists and statisticians. We believe the same strategy provides a useful addition to the imaging toolkit and will succeed with many other high throughput technologies in genetics, metabolomics and chemical analysis.
A Comparison of Parametric and Non-Parametric Methods Applied to a Likert Scale
Mircioiu, Constantin; Atkinson, Jeffrey
2017-01-01
A trenchant and passionate dispute over the use of parametric versus non-parametric methods for the analysis of Likert scale ordinal data has raged for the past eight decades. The answer is not a simple “yes” or “no” but is related to hypotheses, objectives, risks, and paradigms. In this paper, we took a pragmatic approach. We applied both types of methods to the analysis of actual Likert data on responses from different professional subgroups of European pharmacists regarding competencies for practice. Results obtained show that with “large” (>15) numbers of responses and similar (but clearly not normal) distributions from different subgroups, parametric and non-parametric analyses give in almost all cases the same significant or non-significant results for inter-subgroup comparisons. Parametric methods were more discriminant in the cases of non-similar conclusions. Considering that the largest differences in opinions occurred in the upper part of the 4-point Likert scale (ranks 3 “very important” and 4 “essential”), a “score analysis” based on this part of the data was undertaken. This transformation of the ordinal Likert data into binary scores produced a graphical representation that was visually easier to understand as differences were accentuated. In conclusion, in this case of Likert ordinal data with high response rates, restraining the analysis to non-parametric methods leads to a loss of information. The addition of parametric methods, graphical analysis, analysis of subsets, and transformation of data leads to more in-depth analyses. PMID:28970438
Revisiting Parametric Types and Virtual Classes
NASA Astrophysics Data System (ADS)
Madsen, Anders Bach; Ernst, Erik
This paper presents a conceptually oriented updated view on the relationship between parametric types and virtual classes. The traditional view is that parametric types excel at structurally oriented composition and decomposition, and virtual classes excel at specifying mutually recursive families of classes whose relationships are preserved in derived families. Conversely, while class families can be specified using a large number of F-bounded type parameters, this approach is complex and fragile; and it is difficult to use traditional virtual classes to specify object composition in a structural manner, because virtual classes are closely tied to nominal typing. This paper adds new insight about the dichotomy between these two approaches; it illustrates how virtual constraints and type refinements, as recently introduced in gbeta and Scala, enable structural treatment of virtual types; finally, it shows how a novel kind of dynamic type check can detect compatibility among entire families of classes.
Parametric amplification of a superconducting plasma wave
NASA Astrophysics Data System (ADS)
Rajasekaran, S.; Casandruc, E.; Laplace, Y.; Nicoletti, D.; Gu, G. D.; Clark, S. R.; Jaksch, D.; Cavalleri, A.
2016-11-01
Many applications in photonics require all-optical manipulation of plasma waves, which can concentrate electromagnetic energy on sub-wavelength length scales. This is difficult in metallic plasmas because of their small optical nonlinearities. Some layered superconductors support Josephson plasma waves, involving oscillatory tunnelling of the superfluid between capacitively coupled planes. Josephson plasma waves are also highly nonlinear, and exhibit striking phenomena such as cooperative emission of coherent terahertz radiation, superconductor-metal oscillations and soliton formation. Here, we show that terahertz Josephson plasma waves can be parametrically amplified through the cubic tunnelling nonlinearity in a cuprate superconductor. Parametric amplification is sensitive to the relative phase between pump and seed waves, and may be optimized to achieve squeezing of the order-parameter phase fluctuations or terahertz single-photon devices.
Parametric structural modeling of insect wings.
Mengesha, T E; Vallance, R R; Barraja, M; Mittal, R
2009-09-01
Insects produce thrust and lift forces via coupled fluid-structure interactions that bend and twist their compliant wings during flapping cycles. Insight into this fluid-structure interaction is achieved with numerical modeling techniques such as coupled finite element analysis and computational fluid dynamics, but these methods require accurate and validated structural models of insect wings. Structural models of insect wings depend principally on the shape, dimensions and material properties of the veins and membrane cells. This paper describes a method for parametric modeling of wing geometry using digital images and demonstrates the use of the geometric models in constructing three-dimensional finite element (FE) models and simple reduced-order models. The FE models are more complete and accurate than previously reported models since they accurately represent the topology of the vein network, as well as the shape and dimensions of the veins and membrane cells. The methods are demonstrated by developing a parametric structural model of a cicada forewing.
Rayleigh-type parametric chemical oscillation.
Ghosh, Shyamolina; Ray, Deb Shankar
2015-09-28
We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.
A multimode electromechanical parametric resonator array
Mahboob, I.; Mounaix, M.; Nishiguchi, K.; Fujiwara, A.; Yamaguchi, H.
2014-01-01
Electromechanical resonators have emerged as a versatile platform in which detectors with unprecedented sensitivities and quantum mechanics in a macroscopic context can be developed. These schemes invariably utilise a single resonator but increasingly the concept of an array of electromechanical resonators is promising a wealth of new possibilities. In spite of this, experimental realisations of such arrays have remained scarce due to the formidable challenges involved in their fabrication. In a variation to this approach, we identify 75 harmonic vibration modes in a single electromechanical resonator of which 7 can also be parametrically excited. The parametrically resonating modes exhibit vibrations with only 2 oscillation phases which are used to build a binary information array. We exploit this array to execute a mechanical byte memory, a shift-register and a controlled-NOT gate thus vividly illustrating the availability and functionality of an electromechanical resonator array by simply utilising higher order vibration modes. PMID:24658349
Parametric amplification by coupled flux qubits
Rehák, M.; Neilinger, P.; Grajcar, M.; Oelsner, G.; Hübner, U.; Meyer, H.-G.; Il'ichev, E.
2014-04-21
We report parametric amplification of a microwave signal in a Kerr medium formed from superconducting qubits. Two mutually coupled flux qubits, embedded in the current antinode of a superconducting coplanar waveguide resonator, are used as a nonlinear element. Shared Josephson junctions provide the qubit-resonator coupling, resulting in a device with a tunable Kerr constant (up to 3 × 10{sup −3}) and a measured gain of about 20 dB. This arrangement represents a unit cell which can be straightforwardly extended to a quasi one-dimensional quantum metamaterial with large tunable Kerr nonlinearity, providing a basis for implementation of wide-band travelling wave parametric amplifiers.
Parametric amplification of a superconducting plasma wave
Rajasekaran, S.; Casandruc, E.; Laplace, Y.; ...
2016-07-11
Many applications in photonics require all-optical manipulation of plasma waves, which can concentrate electromagnetic energy on sub-wavelength length scales. This is difficult in metallic plasmas because of their small optical nonlinearities. Some layered superconductors support Josephson plasma waves, involving oscillatory tunnelling of the superfluid between capacitively coupled planes. Josephson plasma waves are also highly nonlinear, and exhibit striking phenomena such as cooperative emission of coherent terahertz radiation, superconductor–metal oscillations and soliton formation. In this paper, we show that terahertz Josephson plasma waves can be parametrically amplified through the cubic tunnelling nonlinearity in a cuprate superconductor. Finally, parametric amplification is sensitivemore » to the relative phase between pump and seed waves, and may be optimized to achieve squeezing of the order-parameter phase fluctuations or terahertz single-photon devices.« less
Nondegenerate optical parametric chirped pulse amplifier
Jovanovic, Igor; Ebbers, Christopher A.
2005-03-22
A system provides an input pump pulse and a signal pulse. A first dichroic beamsplitter is highly reflective for the input signal pulse and highly transmissive for the input pump pulse. A first optical parametric amplifier nonlinear crystal transfers part of the energy from the input pump pulse to the input signal pulse resulting in a first amplified signal pulse and a first depleted pump pulse. A second dichroic beamsplitter is highly reflective for the first amplified signal pulse and highly transmissive for the first depleted pump pulse. A second optical parametric amplifier nonlinear crystal transfers part of the energy from the first depleted pump pulse to the first amplified signal pulse resulting in a second amplified signal pulse and a second depleted pump pulse. A third dichroic beamsplitter receives the second amplified signal pulse and the second depleted pump pulse. The second depleted pump pulse is discarded.
Phase shielding soliton in parametrically driven systems.
Clerc, Marcel G; Garcia-Ñustes, Mónica A; Zárate, Yair; Coulibaly, Saliya
2013-05-01
Parametrically driven extended systems exhibit dissipative localized states. Analytical solutions of these states are characterized by a uniform phase and a bell-shaped modulus. Recently, a type of dissipative localized state with a nonuniform phase structure has been reported: the phase shielding solitons. Using the parametrically driven and damped nonlinear Schrödinger equation, we investigate the main properties of this kind of solution in one and two dimensions and develop an analytical description for its structure and dynamics. Numerical simulations are consistent with our analytical results, showing good agreement. A numerical exploration conducted in an anisotropic ferromagnetic system in one and two dimensions indicates the presence of phase shielding solitons. The structure of these dissipative solitons is well described also by our analytical results. The presence of corrective higher-order terms is relevant in the description of the observed phase dynamical behavior.
Parametric amplification of a superconducting plasma wave
Rajasekaran, S.; Casandruc, E.; Laplace, Y.; Nicoletti, D.; Gu, G. D.; Clark, S. R.; Jaksch, D.; Cavalleri, A.
2016-07-11
Many applications in photonics require all-optical manipulation of plasma waves, which can concentrate electromagnetic energy on sub-wavelength length scales. This is difficult in metallic plasmas because of their small optical nonlinearities. Some layered superconductors support Josephson plasma waves, involving oscillatory tunnelling of the superfluid between capacitively coupled planes. Josephson plasma waves are also highly nonlinear, and exhibit striking phenomena such as cooperative emission of coherent terahertz radiation, superconductor–metal oscillations and soliton formation. In this paper, we show that terahertz Josephson plasma waves can be parametrically amplified through the cubic tunnelling nonlinearity in a cuprate superconductor. Finally, parametric amplification is sensitive to the relative phase between pump and seed waves, and may be optimized to achieve squeezing of the order-parameter phase fluctuations or terahertz single-photon devices.
Diode-pumped optical parametric oscillator
Geiger, A.R.; Hemmati, H.; Farr, W.H.
1996-02-01
Diode-pumped optical parametric oscillation has been demonstrated for the first time to our knowledge in a single Nd:MgO:LiNbO{sub 3} nonlinear crystal. The crystal is pumped by a semiconductor diode laser array at 812 nm. The Nd{sup 3+} ions absorb the 812-nm radiation to generate 1084-nm laser oscillation. On internal {ital Q} switching the 1084-nm radiation pumps the LiNbO{sub 3} host crystal that is angle cut at 46.5{degree} and generates optical parametric oscillation. The oscillation threshold that is due to the 1084-nm laser pump with a pulse length of 80 ns in a 1-mm-diameter beam was measured to be {approx_equal}1 mJ and produced 0.5-mJ output at 3400-nm signal wavelength. {copyright} {ital 1996 Optical Society of America.}
Rayleigh-type parametric chemical oscillation
Ghosh, Shyamolina; Ray, Deb Shankar
2015-09-28
We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.
Rayleigh-type parametric chemical oscillation
NASA Astrophysics Data System (ADS)
Ghosh, Shyamolina; Ray, Deb Shankar
2015-09-01
We consider a nonlinear chemical dynamical system of two phase space variables in a stable steady state. When the system is driven by a time-dependent sinusoidal forcing of a suitable scaling parameter at a frequency twice the output frequency and the strength of perturbation exceeds a threshold, the system undergoes sustained Rayleigh-type periodic oscillation, wellknown for parametric oscillation in pipe organs and distinct from the usual forced quasiperiodic oscillation of a damped nonlinear system where the system is oscillatory even in absence of any external forcing. Our theoretical analysis of the parametric chemical oscillation is corroborated by full numerical simulation of two well known models of chemical dynamics, chlorite-iodine-malonic acid and iodine-clock reactions.
Pattern Generation by Dissipative Parametric Instability.
Perego, A M; Tarasov, N; Churkin, D V; Turitsyn, S K; Staliunas, K
2016-01-15
Nonlinear instabilities are responsible for spontaneous pattern formation in a vast number of natural and engineered systems, ranging from biology to galaxy buildup. We propose a new instability mechanism leading to pattern formation in spatially extended nonlinear systems, which is based on a periodic antiphase modulation of spectrally dependent losses arranged in a zigzag way: an effective filtering is imposed at symmetrically located wave numbers k and -k in alternating order. The properties of the dissipative parametric instability differ from the features of both key classical concepts of modulation instabilities, i.e., the Benjamin-Feir instability and the Faraday instabiltyity. We demonstrate how the dissipative parametric instability can lead to the formation of stable patterns in one- and two-dimensional systems. The proposed instability mechanism is generic and can naturally occur or can be implemented in various physical systems.
Parametrizing modified gravity for cosmological surveys
NASA Astrophysics Data System (ADS)
Gleyzes, Jérôme
2017-09-01
One of the challenges in testing gravity with cosmology is the vast freedom opened when extending General Relativity. For linear perturbations, one solution consists in using the effective field theory of dark energy. Even then, the theory space is described in terms of a handful of free functions of time. This needs to be reduced to a finite number of parameters to be practical for cosmological surveys. We explore in this article how well simple parametrizations, with a small number of parameters, can fit observables computed from complex theories. Imposing the stability of linear perturbations appreciably reduces the theory space we explore. We find that observables are not extremely sensitive to short time-scale variations and that simple, smooth parametrizations are usually sufficient to describe this theory space. Using the Bayesian information criterion, we find that using two parameters for each function (an amplitude and a power-law index) is preferred over complex models for 86% of our theory space.
Parametric Amplification of a Superconducting Plasma Wave.
Rajasekaran, S; Casandruc, E; Laplace, Y; Nicoletti, D; Gu, G D; Clark, S R; Jaksch, D; Cavalleri, A
2016-11-01
Many applications in photonics require all-optical manipulation of plasma waves1, which can concentrate electromagnetic energy on sub-wavelength length scales. This is difficult in metallic plasmas because of their small optical nonlinearities. Some layered superconductors support Josephson plasma waves (JPWs)2,3, involving oscillatory tunneling of the superfluid between capacitively coupled planes. Josephson plasma waves are also highly nonlinear4, and exhibit striking phenomena like cooperative emission of coherent terahertz radiation5,6, superconductor-metal oscillations7 and soliton formation8. We show here that terahertz JPWs can be parametrically amplified through the cubic tunneling nonlinearity in a cuprate superconductor. Parametric amplification is sensitive to the relative phase between pump and seed waves and may be optimized to achieve squeezing of the order parameter phase fluctuations9 or single terahertz-photon devices.
Parametric Amplification of a Superconducting Plasma Wave
Rajasekaran, S.; Casandruc, E.; Laplace, Y.; Nicoletti, D.; Gu, G. D.; Clark, S. R.; Jaksch, D.; Cavalleri, A.
2016-01-01
Many applications in photonics require all-optical manipulation of plasma waves1, which can concentrate electromagnetic energy on sub-wavelength length scales. This is difficult in metallic plasmas because of their small optical nonlinearities. Some layered superconductors support Josephson plasma waves (JPWs)2,3, involving oscillatory tunneling of the superfluid between capacitively coupled planes. Josephson plasma waves are also highly nonlinear4, and exhibit striking phenomena like cooperative emission of coherent terahertz radiation5,6, superconductor-metal oscillations7 and soliton formation8. We show here that terahertz JPWs can be parametrically amplified through the cubic tunneling nonlinearity in a cuprate superconductor. Parametric amplification is sensitive to the relative phase between pump and seed waves and may be optimized to achieve squeezing of the order parameter phase fluctuations9 or single terahertz-photon devices. PMID:27833647
Pattern Generation by Dissipative Parametric Instability
NASA Astrophysics Data System (ADS)
Perego, A. M.; Tarasov, N.; Churkin, D. V.; Turitsyn, S. K.; Staliunas, K.
2016-01-01
Nonlinear instabilities are responsible for spontaneous pattern formation in a vast number of natural and engineered systems, ranging from biology to galaxy buildup. We propose a new instability mechanism leading to pattern formation in spatially extended nonlinear systems, which is based on a periodic antiphase modulation of spectrally dependent losses arranged in a zigzag way: an effective filtering is imposed at symmetrically located wave numbers k and -k in alternating order. The properties of the dissipative parametric instability differ from the features of both key classical concepts of modulation instabilities, i.e., the Benjamin-Feir instability and the Faraday instabiltyity. We demonstrate how the dissipative parametric instability can lead to the formation of stable patterns in one- and two-dimensional systems. The proposed instability mechanism is generic and can naturally occur or can be implemented in various physical systems.
Parametric amplification of a superconducting plasma wave
Rajasekaran, S.; Casandruc, E.; Laplace, Y.; Nicoletti, D.; Gu, G. D.; Clark, S. R.; Jaksch, D.; Cavalleri, A.
2016-07-11
Many applications in photonics require all-optical manipulation of plasma waves, which can concentrate electromagnetic energy on sub-wavelength length scales. This is difficult in metallic plasmas because of their small optical nonlinearities. Some layered superconductors support Josephson plasma waves, involving oscillatory tunnelling of the superfluid between capacitively coupled planes. Josephson plasma waves are also highly nonlinear, and exhibit striking phenomena such as cooperative emission of coherent terahertz radiation, superconductor–metal oscillations and soliton formation. In this paper, we show that terahertz Josephson plasma waves can be parametrically amplified through the cubic tunnelling nonlinearity in a cuprate superconductor. Finally, parametric amplification is sensitive to the relative phase between pump and seed waves, and may be optimized to achieve squeezing of the order-parameter phase fluctuations or terahertz single-photon devices.
Intersection of parametric surfaces using lookup tables
NASA Technical Reports Server (NTRS)
Hanna, S. L.; Abel, J. F.; Greenberg, D. P.
1984-01-01
When primitive structures in the form of parametric surfaces are combined and modified interactively to form complex intersecting surfaces, it becomes important to find the curves of intersection. One must distinguish between finding the shape of the intersection curve, which may only be useful for display purposes, and finding an accurate mathematical representation of the curve, which is important for any meaningful geometric modeling, analysis, design, or manufacturing involving the intersection. The intersection curve between two or more parametric surfaces is important in a variety of computer-aided design and manufacture areas. A few examples are shape design, analysis of groins, design of fillets, and computation of numerically controlled tooling paths. The algorithm presented here provides a mathematical representation of the intersection curve to a specified accuracy. It also provides the database that can simplify operations such as hidden-surface removal, surface rendering, profile identification, and interference or clearance computations.
Dynamics of weakly coupled parametrically forced oscillators.
Salgado Sánchez, P; Porter, J; Tinao, I; Laverón-Simavilla, A
2016-08-01
The dynamics of two weakly coupled parametric oscillators are studied in the neighborhood of the primary subharmonic instability. The nature of both primary and secondary instabilities depends in a critical way on the permutation symmetries, if any, that remain after coupling is considered, and this depends on the relative phases of the parametric forcing terms. Detailed bifurcation sets, revealing a complex series of transitions organized in part by Bogdanov-Takens points, are calculated for representative sets of parameters. In the particular case of out-of-phase forcing the predictions of the coupled oscillator model are compared with direct numerical simulations and with recent experiments on modulated cross waves. Both the initial Hopf bifurcation and the subsequent saddle-node heteroclinic bifurcation are confirmed.
Parametric Model of an Aerospike Rocket Engine
NASA Technical Reports Server (NTRS)
Korte, J. J.
2000-01-01
A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHTI multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.
Parametric Model of an Aerospike Rocket Engine
NASA Technical Reports Server (NTRS)
Korte, J. J.
2000-01-01
A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHT multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.
SEC sensor parametric test and evaluation system
NASA Technical Reports Server (NTRS)
1978-01-01
This system provides the necessary automated hardware required to carry out, in conjunction with the existing 70 mm SEC television camera, the sensor evaluation tests which are described in detail. The Parametric Test Set (PTS) was completed and is used in a semiautomatic data acquisition and control mode to test the development of the 70 mm SEC sensor, WX 32193. Data analysis of raw data is performed on the Princeton IBM 360-91 computer.
Parametric instabilities in large nonuniform laser plasmas
Baldis, H.A.; Montgomery, D.S.; Moody, J.D.; Estabrook, K.G.; Berger, R.L.; Kruer, W.L.; Labaune, C.; Batha, S.H.
1992-09-01
The study of parametric instabilities in laser plasmas is of vital importance for inertial confinement fusion (ICF). The long scale-length plasma encountered in the corona of an ICF target provides ideal conditions for the growth of instabilities such as stimulated Brillouin scattering (SBS), stimulated Raman scattering (SRS), and filamentation. These instabilities can have detrimental effects in ICF and their characterization and understanding is of importance. Scattering instabilities are driven through a feedback loop by which the beating between the electromagnetic EM fields of the laser and the scattered light matches the frequency of a local longitudinal mode of the plasma. Any process which interferes with the coherence of this mechanism can substantially alter the behavior of the instability. Of particular interest is the study of laser beam smoothing techniques on parametric instabilities. These techniques are used to improve irradiation uniformity which can suppress hydrodynamic instabilities. Laser beam smoothing techniques have the potential to control the scattering level from parametric instabilities since they provide not only a smoother laser intensity distribution, but also reduced coherence. Beam smoothing techniques that affect the growth of parametric instabilities include spatial smoothing and temporal smoothing by laser bandwidth. Spatial smoothing modifies the phase fronts and temporal distribution of intensities in the focal volume. The transverse intensity spectrum is shifted towards higher spatial wavenumber and can significantly limit the growth of filamentation. Temporal smoothing reduces the coherence time and consequently limits the growth time. Laser bandwidth is required for most smoothing techniques, and can have an independent effect on the instabilities as well.
Wavelength-doubling optical parametric oscillator
Armstrong, Darrell J.; Smith, Arlee V.
2007-07-24
A wavelength-doubling optical parametric oscillator (OPO) comprising a type II nonlinear optical medium for generating a pair of degenerate waves at twice a pump wavelength and a plurality of mirrors for rotating the polarization of one wave by 90 degrees to produce a wavelength-doubled beam with an increased output energy by coupling both of the degenerate waves out of the OPO cavity through the same output coupler following polarization rotation of one of the degenerate waves.
Parametric study of laser photovoltaic energy converters
NASA Technical Reports Server (NTRS)
Walker, G. H.; Heinbockel, J. H.
1987-01-01
Photovoltaic converters are of interest for converting laser power to electrical power in a space-based laser power system. This paper describes a model for photovoltaic laser converters and the application of this model to a neodymium laser silicon photovoltaic converter system. A parametric study which defines the sensitivity of the photovoltaic parameters is described. An optimized silicon photovoltaic converter has an efficiency greater than 50 percent for 1000 W/sq cm of neodymium laser radiation.
Semi-Parametric Generalized Linear Models.
1985-08-01
is nonsingular, upper triangular, and of full rank r. It is known (Dongarra et al., 1979) that G-1 FT is the Moore - Penrose inverse of L . Therefore... GENERALIZED LINEAR pq Mathematics Research Center University of Wisconsin-Madison 610 Walnut Street Madison, Wisconsin 53705 TI C August 1985 E T NOV 7 8...North Carolina 27709 -. -.. . - -.-. g / 6 O5’o UNIVERSITY OF WISCONSIN-MADISON MATHD4ATICS RESEARCH CENTER SD4I-PARAMETRIC GENERALIZED LINEAR MODELS
Beam splitter coupled CDSE optical parametric oscillator
Levinos, Nicholas J.; Arnold, George P.
1980-01-01
An optical parametric oscillator is disclosed in which the resonant radiation is separated from the pump and output radiation so that it can be manipulated without interfering with them. Thus, for example, very narrow band output may readily be achieved by passing the resonant radiation through a line narrowing device which does not in itself interfere with either the pump radiation or the output radiation.
Energy and momentum entanglement in parametric downconversion
NASA Astrophysics Data System (ADS)
Saldanha, Pablo L.; Monken, C. H.
2013-01-01
We present a simple treatment of the phenomenon of spontaneous parametric downconversion consisting of the coherent scattering of a single pump photon into an entangled photon pair inside a nonlinear crystal. The energy and momentum entanglement of the quantum state of the generated twin photons are seen as a consequence of the fundamental indistinguishability of the time and the position in which the photon pair is created inside the crystal. We also discuss some consequences of photon entanglement.
Degeneracies in parametrized modified gravity models
Hojjati, Alireza
2013-01-01
We study degeneracies between parameters in some of the widely used parametrized modified gravity models. We investigate how different observables from a future photometric weak lensing survey such as LSST, correlate the effects of these parameters and to what extent the degeneracies are broken. We also study the impact of other degenerate effects, namely massive neutrinos and some of the weak lensing systematics, on the correlations.
Parametric identification of human operator models
NASA Technical Reports Server (NTRS)
Ninz, N. R.
1982-01-01
The accurate and efficient identification of the human operator is still a need in human factors engineering especially concerning multivariable control. Control theoretic identification methods need to be tested with human operator models under realistic boundary conditons. The requirements and criteria for the use of parametric methods, selected models as well as the Maximum Likelihood Method and the Extended Kalman Filter are displayed. The experiments and results are comparatively discussed from the point of practical engineering.
Sen, Tanaji
2016-06-01
We discuss the generation of parametric X-rays (PXR) in the photoinjector at the new FAST facility at Fermilab. Detailed calculations of the intensity spectrum, energy and angular widths and spectral brilliance with a diamond crystal are presented. We also report on expected results with PXR generated while the beam is channeling. The low emittance electron beam makes this facility a promising source for creating brilliant X-rays.
Parametrized relativistic dynamical framework for neutrino oscillations
NASA Astrophysics Data System (ADS)
Fanchi, John R.
2017-05-01
Mass state transitions are a key feature of parametrized relativistic dynamics (PRD). PRD is a manifestly covariant quantum theory with invariant evolution parameter. The theory has been applied to neutrino flavor oscillations between two mass states. It is generalized to transitions between three mass states and applied to the survival of electron neutrinos. The analysis shows that significant differences exist between theoretical results of the conventional model and the PRD model.
Non-parametric three-way mixed ANOVA with aligned rank tests.
Oliver-Rodríguez, Juan C; Wang, X T
2015-02-01
Research problems that require a non-parametric analysis of multifactor designs with repeated measures arise in the behavioural sciences. There is, however, a lack of available procedures in commonly used statistical packages. In the present study, a generalization of the aligned rank test for the two-way interaction is proposed for the analysis of the typical sources of variation in a three-way analysis of variance (ANOVA) with repeated measures. It can be implemented in the usual statistical packages. Its statistical properties are tested by using simulation methods with two sample sizes (n = 30 and n = 10) and three distributions (normal, exponential and double exponential). Results indicate substantial increases in power for non-normal distributions in comparison with the usual parametric tests. Similar levels of Type I error for both parametric and aligned rank ANOVA were obtained with non-normal distributions and large sample sizes. Degrees-of-freedom adjustments for Type I error control in small samples are proposed. The procedure is applied to a case study with 30 participants per group where it detects gender differences in linguistic abilities in blind children not shown previously by other methods.
Parametric Cost Models for Space Telescopes
NASA Technical Reports Server (NTRS)
Stahl, H. Philip; Henrichs, Todd; Dollinger, Courtney
2010-01-01
Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data and applying rigorous analytical techniques. Specific cost estimating relationships (CERs) have been developed which show that aperture diameter is the primary cost driver for large space telescopes; technology development as a function of time reduces cost at the rate of 50% per 17 years; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and increasing mass reduces cost.
Parametric energy conversion of thermoacoustic vibrations
NASA Astrophysics Data System (ADS)
Guthy, C.; Van Neste, C. W.; Mitra, S.; Bhattacharjee, S.; Thundat, T.
2012-05-01
We demonstrate a parametric energy conversion method of thermoacoustic (TA) vibrations into electrical oscillations of a LC circuit. The inductance modulation necessary to excite the parametric oscillations is achieved by varying the air gap between two halves of a ferrite E-core coil. As a proof-of-concept, the parametric converter was attached to a Sondhauss tube that converts the heat into acoustic vibrations. The maximum total acoustic power output of this thermoacoustic engine was ˜5.3 mW. A flexible metallic membrane capping the Sondhauss tube connected to the moving half E-core served as a mechanical oscillator. The resonance frequency of the membrane was matched with the operating frequency (130 Hz) of the Sondhauss tube for resonant energy extraction. We have characterized the power output of the complete system as a function of electrical load. The maximum electrical power of 2.3 mW produced by the system corresponds to an acoustic-to-electric conversion efficiency of 44%.
A variable parameter parametric snake method
NASA Astrophysics Data System (ADS)
Marouf, A.; Houacine, A.
2015-12-01
In this paper, we introduce a new approach to parametric snake method by using variable snake parameters. Adopting fixed parameter values for all points of the snake, as usual, constitutes by itself a limitation that leads to poor performances in terms of convergence and tracking properties. A more adapted choice should be the one that allows selection depending on the image region properties as on the contour shape and position. However, such variability is not an easy task in general and a precise method need to be defined to assure contour point dependent tuning at iterations. We were particularly interested in applying this idea to the recently presented parametric method [1]. In the work mentioned, an attraction term is used to improve the convergence of the standard parametric snake without a significant increase in computational load. We show here, that improved performances can ensue from applying variable parameter concepts. For this purpose, the method is first analyzed and then a procedure is developed to assure an automatic variable parameter tuning. The interest of our approach is illustrated through object segmentation results.
Free response approach in a parametric system
NASA Astrophysics Data System (ADS)
Huang, Dishan; Zhang, Yueyue; Shao, Hexi
2017-07-01
In this study, a new approach to predict the free response in a parametric system is investigated. It is proposed in the special form of a trigonometric series with an exponentially decaying function of time, based on the concept of frequency splitting. By applying harmonic balance, the parametric vibration equation is transformed into an infinite set of homogeneous linear equations, from which the principal oscillation frequency can be computed, and all coefficients of harmonic components can be obtained. With initial conditions, arbitrary constants in a general solution can be determined. To analyze the computational accuracy and consistency, an approach error function is defined, which is used to assess the computational error in the proposed approach and in the standard numerical approach based on the Runge-Kutta algorithm. Furthermore, an example of a dynamic model of airplane wing flutter on a turbine engine is given to illustrate the applicability of the proposed approach. Numerical solutions show that the proposed approach exhibits high accuracy in mathematical expression, and it is valuable for theoretical research and engineering applications of parametric systems.
NASA Astrophysics Data System (ADS)
Paine, Gregory Harold
1982-03-01
The primary objective of the thesis is to explore the dynamical properties of small nerve networks by means of the methods of statistical mechanics. To this end, a general formalism is developed and applied to elementary groupings of model neurons which are driven by either constant (steady state) or nonconstant (nonsteady state) forces. Neuronal models described by a system of coupled, nonlinear, first-order, ordinary differential equations are considered. A linearized form of the neuronal equations is studied in detail. A Lagrange function corresponding to the linear neural network is constructed which, through a Legendre transformation, provides a constant of motion. By invoking the Maximum-Entropy Principle with the single integral of motion as a constraint, a probability distribution function for the network in a steady state can be obtained. The formalism is implemented for some simple networks driven by a constant force; accordingly, the analysis focuses on a study of fluctuations about the steady state. In particular, a network composed of N noninteracting neurons, termed Free Thinkers, is considered in detail, with a view to interpretation and numerical estimation of the Lagrange multiplier corresponding to the constant of motion. As an archetypical example of a net of interacting neurons, the classical neural oscillator, consisting of two mutually inhibitory neurons, is investigated. It is further shown that in the case of a network driven by a nonconstant force, the Maximum-Entropy Principle can be applied to determine a probability distribution functional describing the network in a nonsteady state. The above examples are reconsidered with nonconstant driving forces which produce small deviations from the steady state. Numerical studies are performed on simplified models of two physical systems: the starfish central nervous system and the mammalian olfactory bulb. Discussions are given as to how statistical neurodynamics can be used to gain a better
A probabilistic strategy for parametric catastrophe insurance
NASA Astrophysics Data System (ADS)
Figueiredo, Rui; Martina, Mario; Stephenson, David; Youngman, Benjamin
2017-04-01
Economic losses due to natural hazards have shown an upward trend since 1980, which is expected to continue. Recent years have seen a growing worldwide commitment towards the reduction of disaster losses. This requires effective management of disaster risk at all levels, a part of which involves reducing financial vulnerability to disasters ex-ante, ensuring that necessary resources will be available following such events. One way to achieve this is through risk transfer instruments. These can be based on different types of triggers, which determine the conditions under which payouts are made after an event. This study focuses on parametric triggers, where payouts are determined by the occurrence of an event exceeding specified physical parameters at a given location, or at multiple locations, or over a region. This type of product offers a number of important advantages, and its adoption is increasing. The main drawback of parametric triggers is their susceptibility to basis risk, which arises when there is a mismatch between triggered payouts and the occurrence of loss events. This is unavoidable in said programmes, as their calibration is based on models containing a number of different sources of uncertainty. Thus, a deterministic definition of the loss event triggering parameters appears flawed. However, often for simplicity, this is the way in which most parametric models tend to be developed. This study therefore presents an innovative probabilistic strategy for parametric catastrophe insurance. It is advantageous as it recognizes uncertainties and minimizes basis risk while maintaining a simple and transparent procedure. A logistic regression model is constructed here to represent the occurrence of loss events based on certain loss index variables, obtained through the transformation of input environmental variables. Flood-related losses due to rainfall are studied. The resulting model is able, for any given day, to issue probabilities of occurrence of loss
Statistical distributions of site and background soil samples often do not meet the assumptions of statistical tests. This is true even of non-parametric tests. This paper evaluates several statistical tests over a variety of cases involving realistic population distribution scen...
Normality Tests for Statistical Analysis: A Guide for Non-Statisticians
Ghasemi, Asghar; Zahediasl, Saleh
2012-01-01
Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS. PMID:23843808
Scaling laws for parametrizations of subgrid interactions in simulations of oceanic circulations.
Kitsios, V; Frederiksen, J S; Zidikheri, M J
2014-06-28
Parametrizations of the subgrid eddy-eddy and eddy-meanfield interactions are developed for the simulation of baroclinic ocean circulations representative of an idealized Antarctic Circumpolar Current. Benchmark simulations are generated using a spectral spherical harmonic quasi-geostrophic model with maximum truncation wavenumber of T=504, which is equivalent to a resolution of 0.24° globally. A stochastic parametrization is used for the eddy-eddy interactions, and a linear deterministic parametrization for the eddy-meanfield interactions. The parametrization coefficients are determined from the statistics of benchmark simulations truncated back to the large eddy simulation (LES) truncation wavenumber, TR
Scaling laws for parametrizations of subgrid interactions in simulations of oceanic circulations
Kitsios, V.; Frederiksen, J. S.; Zidikheri, M. J.
2014-01-01
Parametrizations of the subgrid eddy–eddy and eddy–meanfield interactions are developed for the simulation of baroclinic ocean circulations representative of an idealized Antarctic Circumpolar Current. Benchmark simulations are generated using a spectral spherical harmonic quasi-geostrophic model with maximum truncation wavenumber of T=504, which is equivalent to a resolution of 0.24° globally. A stochastic parametrization is used for the eddy–eddy interactions, and a linear deterministic parametrization for the eddy–meanfield interactions. The parametrization coefficients are determined from the statistics of benchmark simulations truncated back to the large eddy simulation (LES) truncation wavenumber, TR
Information-theoretic tools for parametrized coarse-graining of non-equilibrium extended systems
NASA Astrophysics Data System (ADS)
Katsoulakis, Markos A.; Plecháč, Petr
2013-08-01
In this paper, we focus on the development of new methods suitable for efficient and reliable coarse-graining of non-equilibrium molecular systems. In this context, we propose error estimation and controlled-fidelity model reduction methods based on Path-Space Information Theory, combined with statistical parametric estimation of rates for non-equilibrium stationary processes. The approach we propose extends the applicability of existing information-based methods for deriving parametrized coarse-grained models to Non-Equilibrium systems with Stationary States. In the context of coarse-graining it allows for constructing optimal parametrized Markovian coarse-grained dynamics within a parametric family, by minimizing information loss (due to coarse-graining) on the path space. Furthermore, we propose an asymptotically equivalent method—related to maximum likelihood estimators for stochastic processes—where the coarse-graining is obtained by optimizing the information content in path space of the coarse variables, with respect to the projected computational data from a fine-scale simulation. Finally, the associated path-space Fisher Information Matrix can provide confidence intervals for the corresponding parameter estimators. We demonstrate the proposed coarse-graining method in (a) non-equilibrium systems with diffusing interacting particles, driven by out-of-equilibrium boundary conditions, as well as (b) multi-scale diffusions and the corresponding stochastic averaging limits, comparing them to our proposed methodologies.
Parametric-Studies and Data-Plotting Modules for the SOAP
NASA Technical Reports Server (NTRS)
2008-01-01
"Parametric Studies" and "Data Table Plot View" are the names of software modules in the Satellite Orbit Analysis Program (SOAP). Parametric Studies enables parameterization of as many as three satellite or ground-station attributes across a range of values and computes the average, minimum, and maximum of a specified metric, the revisit time, or 21 other functions at each point in the parameter space. This computation produces a one-, two-, or three-dimensional table of data representing statistical results across the parameter space. Inasmuch as the output of a parametric study in three dimensions can be a very large data set, visualization is a paramount means of discovering trends in the data (see figure). Data Table Plot View enables visualization of the data table created by Parametric Studies or by another data source: this module quickly generates a display of the data in the form of a rotatable three-dimensional-appearing plot, making it unnecessary to load the SOAP output data into a separate plotting program. The rotatable three-dimensionalappearing plot makes it easy to determine which points in the parameter space are most desirable. Both modules provide intuitive user interfaces for ease of use.
Heating and thermal squeezing in parametrically driven oscillators with added noise.
Batista, Adriano A
2012-11-01
In this paper we report a theoretical model based on Green's functions, Floquet theory, and averaging techniques up to second order that describes the dynamics of parametrically driven oscillators with added thermal noise. Quantitative estimates for heating and quadrature thermal noise squeezing near and below the transition line of the first parametric instability zone of the oscillator are given. Furthermore, we give an intuitive explanation as to why heating and thermal squeezing occur. For small amplitudes of the parametric pump the Floquet multipliers are complex conjugate of each other with a constant magnitude. As the pump amplitude is increased past a threshold value in the stable zone near the first parametric instability, the two Floquet multipliers become real and have different magnitudes. This creates two different effective dissipation rates (one smaller and the other larger than the real dissipation rate) along the stable manifolds of the first-return Poincaré map. We also show that the statistical average of the input power due to thermal noise is constant and independent of the pump amplitude and frequency. The combination of these effects causes most of heating and thermal squeezing. Very good agreement between analytical and numerical estimates of the thermal fluctuations is achieved.
Parametric and non-parametric estimation of speech formants: application to infant cry.
Fort, A; Ismaelli, A; Manfredi, C; Bruscaglioni, P
1996-12-01
The present paper addresses the issue of correctly estimating the peaks in the speech envelope (formants) occurring in newborn infant cry. Clinical studies have shown that the analysis of such spectral characteristics is a helpful noninvasive diagnostic tool. In fact it can be applied to explore brain function at very early stage of child development, for a timely diagnosis of neonatal disease and malformation. The paper focuses on the performance comparison between some classical parametric and non-parametric estimation techniques particularly well suited for the present application, specifically the LP, ARX and cepstrum approaches. It is shown that, if the model order is correctly chosen, parametric methods are in general more reliable and robust against noise, but exhibit a less uniform behaviour than cepstrum. The methods are compared also in terms of tracking capability, since the signals under study are nonstationary. Both simulated and real signals are used in order to outline the relevant features of the proposed approaches.
Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.
2016-01-01
In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration
NASA Astrophysics Data System (ADS)
Bueno, A.; Velasco, J.
1996-02-01
Available high energy data for both pp and overlinepp total cross sections ( f GeV < s < 1.8 TeV ) are described by means of two well-known distinct parametrizations, characteristic of theoretical (“Regge-like” expression) and experimental (“Froissart-Martin-like” expression) practices, respectively. Both are compared from the statistical point of view. For the whole set of present data statistical analysis ( χ2/d.o.f.) seems to favour a “Froissart-like” ((ln s) γ≈2 ) rise of the total cross section rather than a “Regge-like” ( sɛ) one.
Tellinghuisen, Joel
2008-01-01
The method of least squares is probably the most powerful data analysis tool available to scientists. Toward a fuller appreciation of that power, this work begins with an elementary review of statistics fundamentals, and then progressively increases in sophistication as the coverage is extended to the theory and practice of linear and nonlinear least squares. The results are illustrated in application to data analysis problems important in the life sciences. The review of fundamentals includes the role of sampling and its connection to probability distributions, the Central Limit Theorem, and the importance of finite variance. Linear least squares are presented using matrix notation, and the significance of the key probability distributions-Gaussian, chi-square, and t-is illustrated with Monte Carlo calculations. The meaning of correlation is discussed, including its role in the propagation of error. When the data themselves are correlated, special methods are needed for the fitting, as they are also when fitting with constraints. Nonlinear fitting gives rise to nonnormal parameter distributions, but the 10% Rule of Thumb suggests that such problems will be insignificant when the parameter is sufficiently well determined. Illustrations include calibration with linear and nonlinear response functions, the dangers inherent in fitting inverted data (e.g., Lineweaver-Burk equation), an analysis of the reliability of the van't Hoff analysis, the problem of correlated data in the Guggenheim method, and the optimization of isothermal titration calorimetry procedures using the variance-covariance matrix for experiment design. The work concludes with illustrations on assessing and presenting results.
Likert Scales, Levels of Measurement and the "Laws" of Statistics
ERIC Educational Resources Information Center
Norman, Geoff
2010-01-01
Reviewers of research reports frequently criticize the choice of statistical methods. While some of these criticisms are well-founded, frequently the use of various parametric methods such as analysis of variance, regression, correlation are faulted because: (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The…
ERIC Educational Resources Information Center
Knapp, Thomas R.; Noblitt, Gerald L.; Viragoontavan, Sunanta
2000-01-01
There is a trend toward abandoning traditional parametric approaches to data analysis, with all their restrictive assumptions, in favor of computer-intensive nonparametric inferential statistical procedures, such as the jackknife and the bootstrap that are based on resampling of the sample data. These techniques are compared with the parametric…
Parametric modulation of an atomic magnetometer
Li, Zhimin; Wakai, Ronald T.; Walker, Thad G.
2012-01-01
The authors report on a rubidium atomic magnetometer designed for use in a shielded environment. Operating in the spin-exchange relaxation-free regime, the magnetometer utilizes parametric modulation of the z-magnetic field to suppress noise associated with airflow through the oven and to simultaneously detect x- and y-field components, using a single probe beam, with minimal loss of sensitivity and bandwidth. A white noise level of 60 fT/(Hz)1/2 was achieved. PMID:22942436
Automatic Parametric Testing Of Integrated Circuits
NASA Technical Reports Server (NTRS)
Jennings, Glenn A.; Pina, Cesar A.
1989-01-01
Computer program for parametric testing saves time and effort in research and development of integrated circuits. Software system automatically assembles various types of test structures and lays them out on silicon chip, generates sequency of test instructions, and interprets test data. Employs self-programming software; needs minimum of human intervention. Adapted to needs of different laboratories and readily accommodates new test structures. Program codes designed to be adaptable to most computers and test equipment now in use. Written in high-level languages to enhance transportability.
Parametric uncertain identification of a robotic system
NASA Astrophysics Data System (ADS)
Angel, L.; Viola, J.; Hernández, C.
2016-07-01
This paper presents the parametric uncertainties identification of a robotic system of one degree of freedom. A MSC-ADAMS / MATLAB co-simulation model was built to simulate the uncertainties that affect the robotic system. For a desired trajectory, a set of dynamic models of the system was identified in presence of variations in the mass, length and friction of the system employing least squares method. Using the input-output linearization technique a linearized model plant was defined. Finally, the maximum multiplicative uncertainty of the system was modelled giving the controller desired design conditions to achieve a robust stability and performance of the closed loop system.
A computer application for parametric aircraft design
NASA Astrophysics Data System (ADS)
Fraqueiro, Filipe R.; Albuquerque, Pedro F.; Gamboa, Pedro V.
2016-11-01
The present work describes the development and final result of a graphical user interface tailored for a mission-based parametric aircraft design optimization code which targets the preliminary design phase of unmanned aerial vehicles. This development was built from the XFLR5 open source platform and further benefits from two-dimensional aerodynamic data obtained from XFOIL. For a better understanding, the most important graphical windows are shown. In order to demonstrate the graphical user interface interaction with the aircraft designer, the results of a case study which maximizes payload are presented.
Parametric study of modern airship productivity
NASA Technical Reports Server (NTRS)
Ardema, M. D.; Flaig, K.
1980-01-01
A method for estimating the specific productivity of both hybrid and fully buoyant airships is developed. Various methods of estimating structural weight of deltoid hybrids are discussed and a derived weight estimating relationship is presented. Specific productivity is used as a figure of merit in a parametric study of fully buoyant ellipsoidal and deltoid hybrid semi-buoyant vehicles. The sensitivity of results as a function of assumptions is also determined. No airship configurations were found to have superior specific productivity to transport airplanes.
Bayesian inference and the parametric bootstrap
Efron, Bradley
2013-01-01
The parametric bootstrap can be used for the efficient computation of Bayes posterior distributions. Importance sampling formulas take on an easy form relating to the deviance in exponential families, and are particularly simple starting from Jeffreys invariant prior. Because of the i.i.d. nature of bootstrap sampling, familiar formulas describe the computational accuracy of the Bayes estimates. Besides computational methods, the theory provides a connection between Bayesian and frequentist analysis. Efficient algorithms for the frequentist accuracy of Bayesian inferences are developed and demonstrated in a model selection example. PMID:23843930
Multicutter machining of compound parametric surfaces
NASA Astrophysics Data System (ADS)
Hatna, Abdelmadjid; Grieve, R. J.; Broomhead, P.
2000-10-01
Parametric free forms are used in industries as disparate as footwear, toys, sporting goods, ceramics, digital content creation, and conceptual design. Optimizing tool path patterns and minimizing the total machining time is a primordial issue in numerically controlled (NC) machining of free form surfaces. We demonstrate in the present work that multi-cutter machining can achieve as much as 60% reduction in total machining time for compound sculptured surfaces. The given approach is based upon the pre-processing as opposed to the usual post-processing of surfaces for the detection and removal of interference followed by precise tracking of unmachined areas.
The Parametrized Post-Newtonian Gravitational Redshift
NASA Technical Reports Server (NTRS)
Krisher, T. P.
1993-01-01
A derivation of the gravitational redshift effect to order c ^(-4) is presented. The calculation isperformed within the framework of the parametrized post-Newtonian formalism for analyzing metrictheories of gravity, which includes corrections to second- order in the Newtonian potential,gravitomagnetic contributions, and preferred-frame terms. We briefly discuss how to generalize ourresults to include possible violations of local Lorentz invariance or local position invariance which canarise in nonmetric theories. Our results are useful for analyzing possible new redshift experimentswhich may be sensitive to second-order effects, such as a close solar flyby mission.
Lottery spending: a non-parametric analysis.
Garibaldi, Skip; Frisoli, Kayla; Ke, Li; Lim, Melody
2015-01-01
We analyze the spending of individuals in the United States on lottery tickets in an average month, as reported in surveys. We view these surveys as sampling from an unknown distribution, and we use non-parametric methods to compare properties of this distribution for various demographic groups, as well as claims that some properties of this distribution are constant across surveys. We find that the observed higher spending by Hispanic lottery players can be attributed to differences in education levels, and we dispute previous claims that the top 10% of lottery players consistently account for 50% of lottery sales.
Observation of ultrabroadband, beamlike parametric downconversion.
O'Donnell, Kevin A; U'Ren, Alfred B
2007-04-01
We report spontaneous parametric downconversion having an unusually wide spectral bandwidth. A collinear type 1 phase-matching configuration is employed with degeneracy near the zero group-velocity dispersion frequency. With a spectral width of 1080 nm and degenerate wavelength of 1885 nm, the source also emits a high flux of 3.4 x 10(11) s(-1)W(-1) photon pairs constrained to a cone of only approximately 2 degrees half-angle. A rigorous theoretical approach is developed that confirms the experimental observations. The source properties are consistent with an ultrashort photon-pair correlation time and, for a narrowband pump, extremely high-dimensional spectral entanglement.
SIMULATIONS OF PARAMETRIC-RESONANCE IONIZATION COOLING
David Newsham; Richard Sah; Alex Bogacz; Yu-Chiu Chao; Yaroslav Derbenev
2007-06-01
Parametric-resonance ionization cooling (PIC) is a muon-cooling technique that is useful for low-emittance muon colliders. This method requires a well-tuned focusing channel that is free of chromatic and spherical aberrations. In order to be of practical use in a muon collider, it also necessary that the focusing channel be as short as possible to minimize muon loss due to decay. G4Beamline numerical simulations are presented of a compact PIC focusing channel in which spherical aberrations are minimized by using design symmetry.
Parametric Uncertainty Reduction in Robust Multivariable Control
1993-09-01
presents a method for reducing the Dumber of parametric un- certainties used in the design of a robust Ho, controller. The resulting controller is shown...determining robust stability can be de- duced from Figure 2.9. Stability in the loop containing the perturbation requires that for all frequencies det {I... det (I + MA) = 01 {minAEA(a(A) I det (J + MA) = 0)1’ otherwise 15 It can be shown that the SSV has the following properties (Doyle, 1982): 1. F(oM) =1
Detecting Atlantic herring by parametric sonar.
Godo, Olav Rune; Foote, Kenneth G; Dybedal, Johnny; Tenningen, Eirik; Patel, Ruben
2010-04-01
The difference-frequency band of the Kongsberg TOPAS PS18 parametric sub-bottom profiling sonar, nominally 1-6 kHz, is being used to observe Atlantic herring. Representative TOPAS echograms of herring layers and schools observed in situ in December 2008 and November 2009 are presented. These agree well with echograms of volume backscattering strength derived simultaneously with the narrowband Simrad EK60/18- and 38-kHz scientific echo sounder, also giving insight into herring avoidance behavior in relation to survey vessel passage. Progress in rendering the TOPAS echograms quantitative is described.
Lottery Spending: A Non-Parametric Analysis
Garibaldi, Skip; Frisoli, Kayla; Ke, Li; Lim, Melody
2015-01-01
We analyze the spending of individuals in the United States on lottery tickets in an average month, as reported in surveys. We view these surveys as sampling from an unknown distribution, and we use non-parametric methods to compare properties of this distribution for various demographic groups, as well as claims that some properties of this distribution are constant across surveys. We find that the observed higher spending by Hispanic lottery players can be attributed to differences in education levels, and we dispute previous claims that the top 10% of lottery players consistently account for 50% of lottery sales. PMID:25642699
A Cartesian parametrization for the numerical analysis of material instability
Mota, Alejandro; Chen, Qiushi; Foulk, III, James W.; ...
2016-02-25
We examine four parametrizations of the unit sphere in the context of material stability analysis by means of the singularity of the acoustic tensor. We then propose a Cartesian parametrization for vectors that lie a cube of side length two and use these vectors in lieu of unit normals to test for the loss of the ellipticity condition. This parametrization is then used to construct a tensor akin to the acoustic tensor. It is shown that both of these tensors become singular at the same time and in the same planes in the presence of a material instability. Furthermore, themore » performance of the Cartesian parametrization is compared against the other parametrizations, with the results of these comparisons showing that in general, the Cartesian parametrization is more robust and more numerically efficient than the others.« less
A Cartesian parametrization for the numerical analysis of material instability
Mota, Alejandro; Chen, Qiushi; Foulk, III, James W.; Ostien, Jakob T.; Lai, Zhengshou
2016-02-25
We examine four parametrizations of the unit sphere in the context of material stability analysis by means of the singularity of the acoustic tensor. We then propose a Cartesian parametrization for vectors that lie a cube of side length two and use these vectors in lieu of unit normals to test for the loss of the ellipticity condition. This parametrization is then used to construct a tensor akin to the acoustic tensor. It is shown that both of these tensors become singular at the same time and in the same planes in the presence of a material instability. Furthermore, the performance of the Cartesian parametrization is compared against the other parametrizations, with the results of these comparisons showing that in general, the Cartesian parametrization is more robust and more numerically efficient than the others.
Eisenbrey, John R; Dave, Jaydev K; Merton, Daniel A; Palazzo, Juan P; Hall, Anne L; Forsberg, Flemming
2011-01-01
Parametric maps showing perfusion of contrast media can be useful tools for characterizing lesions in breast tissue. In this study we show the feasibility of parametric subharmonic imaging (SHI), which allows imaging of a vascular marker (the ultrasound contrast agent) while providing near complete tissue suppression. Digital SHI clips of 16 breast lesions from 14 women were acquired. Patients were scanned using a modified LOGIQ 9 scanner (GE Healthcare, Waukesha, WI) transmitting/receiving at 4.4/2.2 MHz. Using motion-compensated cumulative maximum intensity (CMI) sequences, parametric maps were generated for each lesion showing the time to peak (TTP), estimated perfusion (EP), and area under the time-intensity curve (AUC). Findings were grouped and compared according to biopsy results as benign lesions (n = 12, including 5 fibroadenomas and 3 cysts) and carcinomas (n = 4). For each lesion CMI, TTP, EP, and AUC parametric images were generated. No significant variations were detected with CMI (P = .80), TTP (P = .35), or AUC (P = .65). A statistically significant variation was detected for the average pixel EP (P = .002). Especially, differences were seen between carcinoma and benign lesions (mean ± SD, 0.10 ± 0.03 versus 0.05 ± 0.02 intensity units [IU]/s; P = .0014) and between carcinoma and fibroadenoma (0.10 ± 0.03 versus 0.04 ± 0.01 IU/s; P = .0044), whereas differences between carcinomas and cysts were found to be nonsignificant. In conclusion, a parametric imaging method for characterization of breast lesions using the high contrast to tissue signal provided by SHI has been developed. While the preliminary sample size was limited, results show potential for breast lesion characterization based on perfusion flow parameters.
Basic statistical tools in research and data analysis.
Ali, Zulfiqar; Bhaskar, S Bala
2016-09-01
Statistical methods involved in carrying out a study include planning, designing, collecting data, analysing, drawing meaningful interpretation and reporting of the research findings. The statistical analysis gives meaning to the meaningless numbers, thereby breathing life into a lifeless data. The results and inferences are precise only if proper statistical tests are used. This article will try to acquaint the reader with the basic research tools that are utilised while conducting various studies. The article covers a brief outline of the variables, an understanding of quantitative and qualitative variables and the measures of central tendency. An idea of the sample size estimation, power analysis and the statistical errors is given. Finally, there is a summary of parametric and non-parametric tests used for data analysis.
Khan, Asaduzzaman; Chien, Chi-Wen; Bagraith, Karl S
2015-04-01
To investigate whether using a parametric statistic in comparing groups leads to different conclusions when using summative scores from rating scales compared with using their corresponding Rasch-based measures. A Monte Carlo simulation study was designed to examine between-group differences in the change scores derived from summative scores from rating scales, and those derived from their corresponding Rasch-based measures, using 1-way analysis of variance. The degree of inconsistency between the 2 scoring approaches (i.e. summative and Rasch-based) was examined, using varying sample sizes, scale difficulties and person ability conditions. This simulation study revealed scaling artefacts that could arise from using summative scores rather than Rasch-based measures for determining the changes between groups. The group differences in the change scores were statistically significant for summative scores under all test conditions and sample size scenarios. However, none of the group differences in the change scores were significant when using the corresponding Rasch-based measures. This study raises questions about the validity of the inference on group differences of summative score changes in parametric analyses. Moreover, it provides a rationale for the use of Rasch-based measures, which can allow valid parametric analyses of rating scale data.
DVP parametric imaging for characterizing ovarian masses in contrast-enhanced ultrasound.
Sha-sha, H; Li, H; Jie, M; Gui, F; Wen-jun, G; Ming, H; Yang, Z; Qing, Y
2015-01-01
To evaluate whether parametric imaging with contrast-enhanced ultrasound is an approach capable of for the differential diagnosis of ovarian masses. The authors analysed 50 cases of ovarian masses by routine ultrasound and contrast-enhanced ultrasound with a new dedicated parametric image processing software-Sonoliver. The angiogenesis and blood perfusion mode on a digital video recorder were recorded and the morphological characteristics of time-intensity curve (TIC) and dynamic vascular pattern (DVP) curve were subsequently described. The quantity factor, including time to peak (TTP), maximum intensity (IMAX), rise time, (RT), mean transit time (mTT), generated by Sonoliver software were compared in both histological gradings. There were 24 cases (86%) displaying mainly hypo-enhanced with blue imaging in those with benign masses and 15 cases (68%) displaying mainly hyper-enhanced imaging with red in those with malignant masses. The difference was statistically significant (p < 0.05). DVP curves were unipolar below the baseline in 23 cases (82%) of benign masses and unipolar above the baseline in 15 cases (68%) of malignant masses. IMAX, TTP, and mTT were all significantly higher in those with malignant masses than those with benign ones (all p < 0.05), but, no statistical difference in the RT between the two groups was found (p > 0.05). According to the results, DVP parametric imaging is a new approach capable of differential diagnoses of overian masses with contrast-enhanced ultrasound.
Quantiles, Parametric-Select Density Estimations, and Bi-Information Parameter Estimators.
1982-06-01
A non- parametric estimation method forms estimators which are not based on parametric models. Important examples of non-parametric estimators of a...raw descriptive functions F, f, Q, q, fQ. One distinguishes between parametric and non-parametric methods of estimating smooth functions. A parametric ... estimation method : (1) assumes a family F8, fo’ Q0, qo’ foQ8 of functions, called parametric models, which are indexed by a parameter 6 = ( l
Characterization of a multimode coplanar waveguide parametric amplifier
Simoen, M. Krantz, P.; Bylander, Jonas; Shumeiko, V.; Delsing, P.; Chang, C. W. S.; Wilson, C. M.; Wustmann, W.
2015-10-21
We characterize a Josephson parametric amplifier based on a flux-tunable quarter-wavelength resonator. The fundamental resonance frequency is ∼1 GHz, but we use higher modes of the resonator for our measurements. An on-chip tuning line allows for magnetic flux pumping of the amplifier. We investigate and compare degenerate parametric amplification, involving a single mode, and nondegenerate parametric amplification, using a pair of modes. We show that we reach quantum-limited noise performance in both cases.
Cascade frequency generation regime in an optical parametric oscillator
Kolker, D B; Dmitriev, Aleksandr K; Gorelik, P; Vong, Franko; Zondy, J J
2009-05-31
In a parametric oscillator of a special two-sectional design based on a lithium niobate periodic structure, a cascade frequency generation regime was observed in which a signal wave pumped a secondary parametric oscillator, producing secondary signal and idler waves. The secondary parametric oscillator can be tuned in a broad range of {approx}200 nm with respect to a fixed wavelength of the primary idler wave. (nonlinear optical phenomena)
Second order parametric processes in nonlinear silica microspheres.
Xu, Yong; Han, Ming; Wang, Anbo; Liu, Zhiwen; Heflin, James R
2008-04-25
We analyze second order parametric processes in a silica microsphere coated with radially aligned nonlinear optical molecules. In a high-Q nonlinear microsphere, we discover that it is possible to achieve ultralow threshold parametric oscillation that obeys the rule of angular momentum conservation. Based on symmetry considerations, one can also implement parametric processes that naturally generate quantum entangled photon pairs. Practical issues regarding implementation of the nonlinear microsphere are also discussed.
Study of Vertical Sound Image Control Using Parametric Loudspeakers
NASA Astrophysics Data System (ADS)
Shimizu, Kazuhiro; Itou, Kouki; Aoki, Shigeaki
A parametric loudspeaker is known as a super-directivity loudspeaker. So far, the applications have been limited monaural reproduction sound system. We had discussed characteristics of stereo reproduction with two parametric loudspeakers. In this paper, the sound localization in the vertical direction using the parametric loudspeakers was confirmed. The direction of sound localization was able to be controlled. The results were similar as in using ordinary loudspeakers. However, by setting the parametric loudspeaker 5 degrees rightward, the direction of sound localization moved about 20 degrees rightward. The measured ILD (Interaural Level Difference) using a dummy head were analyzed.
Parametric robust control and system identification: Unified approach
NASA Technical Reports Server (NTRS)
Keel, Leehyun
1994-01-01
Despite significant advancement in the area of robust parametric control, the problem of synthesizing such a controller is still a wide open problem. Thus, we attempt to give a solution to this important problem. Our approach captures the parametric uncertainty as an H(sub infinity) unstructured uncertainty so that H(sub infinity) synthesis techniques are applicable. Although the techniques cannot cope with the exact parametric uncertainty, they give a reasonable guideline to model the unstructured uncertainty that contains the parametric uncertainty. An additional loop shaping technique is also introduced to relax its conservatism.
Effects of dispersion on mode locking in optical parametric oscillators
NASA Astrophysics Data System (ADS)
Longhi, S.
1995-08-01
We discuss the role that group-velocity dispersion and cavity detuning play in the onset of mode locking in synchronously pumped optical parametric oscillators. Because of the phase-sensitive character of the parametric gain, it is shown for the degenerate case that dispersion effects associated with off-resonance operation can lead to subpulse structures and spectral splitting of the parametric pulses. This behavior is interpreted on the basis of a dispersion-induced interference phenomenon between the two nearly degenerate parametric photons produced by the conversion of one pump photon in the nonlinear medium.
Optical parametrically gated microscopy in scattering media.
Zhao, Youbo; Adie, Steven G; Tu, Haohua; Liu, Yuan; Graf, Benedikt W; Chaney, Eric J; Marjanovic, Marina; Boppart, Stephen A
2014-09-22
High-resolution imaging in turbid media has been limited by the intrinsic compromise between the gating efficiency (removal of multiply-scattered light background) and signal strength in the existing optical gating techniques. This leads to shallow depths due to the weak ballistic signal, and/or degraded resolution due to the strong multiply-scattering background--the well-known trade-off between resolution and imaging depth in scattering samples. In this work, we employ a nonlinear optics based optical parametric amplifier (OPA) to address this challenge. We demonstrate that both the imaging depth and the spatial resolution in turbid media can be enhanced simultaneously by the OPA, which provides a high level of signal gain as well as an inherent nonlinear optical gate. This technology shifts the nonlinear interaction to an optical crystal placed in the detection arm (image plane), rather than in the sample, which can be used to exploit the benefits given by the high-order parametric process and the use of an intense laser field. The coherent process makes the OPA potentially useful as a general-purpose optical amplifier applicable to a wide range of optical imaging techniques.
Supramodal parametric working memory processing in humans.
Spitzer, Bernhard; Blankenburg, Felix
2012-03-07
Previous studies of delayed-match-to-sample (DMTS) frequency discrimination in animals and humans have succeeded in delineating the neural signature of frequency processing in somatosensory working memory (WM). During retention of vibrotactile frequencies, stimulus-dependent single-cell and population activity in prefrontal cortex was found to reflect the task-relevant memory content, whereas increases in occipital alpha activity signaled the disengagement of areas not relevant for the tactile task. Here, we recorded EEG from human participants to determine the extent to which these mechanisms can be generalized to frequency retention in the visual and auditory domains. Subjects performed analogous variants of a DMTS frequency discrimination task, with the frequency information presented either visually, auditorily, or by vibrotactile stimulation. Examining oscillatory EEG activity during frequency retention, we found characteristic topographical distributions of alpha power over visual, auditory, and somatosensory cortices, indicating systematic patterns of inhibition and engagement of early sensory areas, depending on stimulus modality. The task-relevant frequency information, in contrast, was found to be represented in right prefrontal cortex, independent of presentation mode. In each of the three modality conditions, parametric modulations of prefrontal upper beta activity (20-30 Hz) emerged, in a very similar manner as recently found in vibrotactile tasks. Together, the findings corroborate a view of parametric WM as supramodal internal scaling of abstract quantity information and suggest strong relevance of previous evidence from vibrotactile work for a more general framework of quantity processing in human working memory.
Quantum dynamics of the parametric oscillator
NASA Astrophysics Data System (ADS)
Kinsler, P.; Drummond, P. D.
1991-06-01
We present dynamical calculations for the quantum parametric oscillator using both number-state and coherent-state bases. The coherent-state methods use the positive-P representation, which has a nonclassical phase space-an essential requirement in obtaining an exact stochastic representation of this nonlinear problem. This also provides a way to directly simulate quantum tunneling between the two above-threshold stable states of the oscillator. The coherent-state methods provide both analytic results at large photon numbers, and numerical results for any photon number, while our number-state calculations are restricted to numerical results in the low-photon-number regime. The number-state and coherent-state methods give precise agreement within the accuracy of the numerical calculations. We also compare our results with methods based on a truncated Wigner representation equivalent to stochastic electrodynamics, and find that these are unable to correctly predict the tunneling rate given by the other methods. An interesting feature of the results is the much faster tunneling predicted by the exact quantum-theory methods compared with earlier semiclassical calculations using an approximate potential barrier. This is similar to the faster tunneling found when comparing quantum penetration of a barrier to classical thermal activation. The quantum parametric oscillator, which has an exact steady-state solution, therefore provides a useful and accessible system in which nonlinear quantum effects can be studied far from thermal equilibrium.
Modeling Personnel Turnover in the Parametric Organization
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1991-01-01
A primary issue in organizing a new parametric cost analysis function is to determine the skill mix and number of personnel required. The skill mix can be obtained by a functional decomposition of the tasks required within the organization and a matrixed correlation with educational or experience backgrounds. The number of personnel is a function of the skills required to cover all tasks, personnel skill background and cross training, the intensity of the workload for each task, migration through various tasks by personnel along a career path, personnel hiring limitations imposed by management and the applicant marketplace, personnel training limitations imposed by management and personnel capability, and the rate at which personnel leave the organization for whatever reason. Faced with the task of relating all of these organizational facets in order to grow a parametric cost analysis (PCA) organization from scratch, it was decided that a dynamic model was required in order to account for the obvious dynamics of the forming organization. The challenge was to create such a simple model which would be credible during all phases of organizational development. The model development process was broken down into the activities of determining the tasks required for PCA, determining the skills required for each PCA task, determining the skills available in the applicant marketplace, determining the structure of the dynamic model, implementing the dynamic model, and testing the dynamic model.
Quantum metrology with unitary parametrization processes.
Liu, Jing; Jing, Xiao-Xing; Wang, Xiaoguang
2015-02-24
Quantum Fisher information is a central quantity in quantum metrology. We discuss an alternative representation of quantum Fisher information for unitary parametrization processes. In this representation, all information of parametrization transformation, i.e., the entire dynamical information, is totally involved in a Hermitian operator H. Utilizing this representation, quantum Fisher information is only determined by H and the initial state. Furthermore, H can be expressed in an expanded form. The highlights of this form is that it can bring great convenience during the calculation for the Hamiltonians owning recursive commutations with their partial derivative. We apply this representation in a collective spin system and show the specific expression of H. For a simple case, a spin-half system, the quantum Fisher information is given and the optimal states to access maximum quantum Fisher information are found. Moreover, for an exponential form initial state, an analytical expression of quantum Fisher information by H operator is provided. The multiparameter quantum metrology is also considered and discussed utilizing this representation.
Degenerate parametric oscillation in quantum membrane optomechanics
NASA Astrophysics Data System (ADS)
Benito, Mónica; Sánchez Muñoz, Carlos; Navarrete-Benlloch, Carlos
2016-02-01
The promise of innovative applications has triggered the development of many modern technologies capable of exploiting quantum effects. But in addition to future applications, such quantum technologies have already provided us with the possibility of accessing quantum-mechanical scenarios that seemed unreachable just a few decades ago. With this spirit, in this work we show that modern optomechanical setups are mature enough to implement one of the most elusive models in the field of open system dynamics: degenerate parametric oscillation. Introduced in the eighties and motivated by its alleged implementability in nonlinear optical resonators, it rapidly became a paradigm for the study of dissipative phase transitions whose corresponding spontaneously broken symmetry is discrete. However, it was found that the intrinsic multimode nature of optical cavities makes it impossible to experimentally study the model all the way through its phase transition. In contrast, here we show that this long-awaited model can be implemented in the motion of a mechanical object dispersively coupled to the light contained in a cavity, when the latter is properly driven with multichromatic laser light. We focus on membranes as the mechanical element, showing that the main signatures of the degenerate parametric oscillation model can be studied in state-of-the-art setups, thus opening the possibility of analyzing spontaneous symmetry breaking and enhanced metrology in one of the cleanest dissipative phase transitions. In addition, the ideas put forward in this work would allow for the dissipative preparation of squeezed mechanical states.
Parametric uncertainty in nanoscale optical dimensional measurements.
Potzick, James; Marx, Egon
2012-06-10
Image modeling establishes the relation between an object and its image when an optical microscope is used to measure the dimensions of an object of size comparable to the illumination wavelength. It accounts for the influence of all of the parameters that can affect the image and relates the apparent feature width (FW) in the image to the true FW of the object. The values of these parameters, however, have uncertainties, and these uncertainties propagate through the model and lead to parametric uncertainty in the FW measurement, a key component of the combined measurement uncertainty. The combined uncertainty is required in order to decide if the result is adequate for its intended purpose and to ascertain if it is consistent with other results. The parametric uncertainty for optical photomask measurements derived using an edge intensity threshold approach has been described previously; this paper describes an image library approach to this issue and shows results for optical photomask metrology over a FW range of 10 nm to 8 µm using light of wavelength 365 nm. The principles will be described; a one-dimensional image library will be used; the method of comparing images, along with a simple interpolation method, will be explained; and results will be presented. This method is easily extended to any kind of imaging microscope and to more dimensions in parameter space. It is more general than the edge threshold method and leads to markedly different uncertainties for features smaller than the wavelength.
Ab initio based polarizable force field parametrization
NASA Astrophysics Data System (ADS)
Masia, Marco
2008-05-01
Experimental and simulation studies of anion-water systems have pointed out the importance of molecular polarization for many phenomena ranging from hydrogen-bond dynamics to water interfaces structure. The study of such systems at molecular level is usually made with classical molecular dynamics simulations. Structural and dynamical features are deeply influenced by molecular and ionic polarizability, which parametrization in classical force field has been an object of long-standing efforts. Although when classical models are compared to ab initio calculations at condensed phase, it is found that the water dipole moments are underestimated by ˜30%, while the anion shows an overpolarization at short distances. A model for chloride-water polarizable interaction is parametrized here, making use of Car-Parrinello simulations at condensed phase. The results hint to an innovative approach in polarizable force fields development, based on ab initio simulations, which do not suffer for the mentioned drawbacks. The method is general and can be applied to the modeling of different systems ranging from biomolecular to solid state simulations.
Quantum metrology with unitary parametrization processes
Liu, Jing; Jing, Xiao-Xing; Wang, Xiaoguang
2015-01-01
Quantum Fisher information is a central quantity in quantum metrology. We discuss an alternative representation of quantum Fisher information for unitary parametrization processes. In this representation, all information of parametrization transformation, i.e., the entire dynamical information, is totally involved in a Hermitian operator . Utilizing this representation, quantum Fisher information is only determined by and the initial state. Furthermore, can be expressed in an expanded form. The highlights of this form is that it can bring great convenience during the calculation for the Hamiltonians owning recursive commutations with their partial derivative. We apply this representation in a collective spin system and show the specific expression of . For a simple case, a spin-half system, the quantum Fisher information is given and the optimal states to access maximum quantum Fisher information are found. Moreover, for an exponential form initial state, an analytical expression of quantum Fisher information by operator is provided. The multiparameter quantum metrology is also considered and discussed utilizing this representation. PMID:25708678
Parametric Symmetry Breaking in a Nonlinear Resonator
NASA Astrophysics Data System (ADS)
Leuch, Anina; Papariello, Luca; Zilberberg, Oded; Degen, Christian L.; Chitra, R.; Eichler, Alexander
2016-11-01
Much of the physical world around us can be described in terms of harmonic oscillators in thermodynamic equilibrium. At the same time, the far-from-equilibrium behavior of oscillators is important in many aspects of modern physics. Here, we investigate a resonating system subject to a fundamental interplay between intrinsic nonlinearities and a combination of several driving forces. We have constructed a controllable and robust realization of such a system using a macroscopic doubly clamped string. We experimentally observe a hitherto unseen double hysteresis in both the amplitude and the phase of the resonator's response function and present a theoretical model that is in excellent agreement with the experiment. Our work unveils that the double hysteresis is a manifestation of an out-of-equilibrium symmetry breaking between parametric phase states. Such a fundamental phenomenon, in the most ubiquitous building block of nature, paves the way for the investigation of new dynamical phases of matter in parametrically driven many-body systems and motivates applications ranging from ultrasensitive force detection to low-energy computing memory units.
Quantum transformation limits in multiwave parametric interactions
NASA Astrophysics Data System (ADS)
Saygin, M. Yu
2016-10-01
The possibility to realize multiple nonlinear optical processes in a single crystal as means to produce multicolor quantum states favours stability and compactness of optical settings. Hence, this approach can be advantageous compared to the traditional one based on cascaded arrangement of optical elements. However, it comes with an obstacle—the class of accessible quantum states is narrower than that of the cascade counterpart. In this letter, we study this task using an example of three coupled nonlinear optical processes, namely, one parametric down-conversion and two of sum-frequency generation. To this end, the singular value decomposition has been applied to find the cascade representation of the compound field evolution. We have found the link between the parameters of the multiwave processes and the relevant cascade parameters—beam-splitting and squeezing parameters, by means of which the generated quantum states have been characterized. The relation between the squeezing parameters that has been found in the course of this work shows that the squeezing resource, produced in the parametric down-conversion, is shared among the modes involved in the compound interactions. Moreover, we have shown that the degree of two-mode entanglement carried by the up-converted frequencies cannot exceed that of the down-converted frequencies.
All-optical quantum random bit generation from intrinsically binary phase of parametric oscillators.
Marandi, Alireza; Leindecker, Nick C; Vodopyanov, Konstantin L; Byer, Robert L
2012-08-13
We demonstrate a novel all-optical quantum random number generator (RNG) based on above-threshold binary phase state selection in a degenerate optical parametric oscillator (OPO). Photodetection is not a part of the random process, and no post processing is required for the generated bit sequence. We show that the outcome is statistically random with 99% confidence, and verify that the randomness is due to the phase of initiating photons generated through spontaneous parametric down conversion of the pump, with negligible contribution of classical noise sources. With the use of micro- and nanoscale OPO resonators, this technique offers a promise for simple, robust, and high-speed on-chip all-optical quantum RNGs.
Parametric reduced models for the nonlinear Schrödinger equation.
Harlim, John; Li, Xiantao
2015-05-01
Reduced models for the (defocusing) nonlinear Schrödinger equation are developed. In particular, we develop reduced models that only involve the low-frequency modes given noisy observations of these modes. The ansatz of the reduced parametric models are obtained by employing a rational approximation and a colored-noise approximation, respectively, on the memory terms and the random noise of a generalized Langevin equation that is derived from the standard Mori-Zwanzig formalism. The parameters in the resulting reduced models are inferred from noisy observations with a recently developed ensemble Kalman filter-based parametrization method. The forecasting skill across different temperature regimes are verified by comparing the moments up to order four, a two-time correlation function statistics, and marginal densities of the coarse-grained variables.
Parametric interactions in presence of different size colloids in semiconductor quantum plasmas
Vanshpal, R. Sharma, Uttam; Dubey, Swati
2015-07-31
Present work is an attempt to investigate the effect of different size colloids on parametric interaction in semiconductor quantum plasma. Inclusion of quantum effect is being done in this analysis through quantum correction term in classical hydrodynamic model of homogeneous semiconductor plasma. The effect is associated with purely quantum origin using quantum Bohm potential and quantum statistics. Colloidal size and quantum correction term modify the parametric dispersion characteristics of ion implanted semiconductor plasma medium. It is found that quantum effect on colloids is inversely proportional to their size. Moreover critical size of implanted colloids for the effective quantum correction is determined which is found to be equal to the lattice spacing of the crystal.
The role of parametric linkage methods in complex trait analyses using microsatellites
Badzioch, Michael D; Goode, Ellen L; Jarvik, Gail P
2005-01-01
Many investigators of complexly inherited familial traits bypass classical segregation analysis to perform model-free genome-wide linkage scans. Because model-based or parametric linkage analysis may be the most powerful means to localize genes when a model can be approximated, model-free statistics may result in a loss of power to detect linkage. We performed limited segregation analyses on the electrophysiological measurements that have been collected for the Collaborative Study on the Genetics of Alcoholism. The resulting models are used in whole-genome scans. Four genomic regions provided a model-based LOD > 2 and only 3 of these were detected (p < 0.05) by a model-free approach. We conclude that parametric methods, using even over-simplified models of complex phenotypes, may complement nonparametric methods and decrease false positives. PMID:16451659
Epsilon-optimal non-Bayesian anomaly detection for parametric tomography.
Fillatre, Lionel; Nikiforov, Igor; Retraint, Florent
2008-11-01
The non-Bayesian detection of an anomaly from a single or a few noisy tomographic projections is considered as a statistical hypotheses testing problem. It is supposed that a radiography is composed of an imaged nonanomalous background medium, considered as a deterministic nuisance parameter, with a possibly hidden anomaly. Because the full voxel-by-voxel reconstruction is impossible, an original tomographic method based on the parametric models of the nonanomalous background medium and radiographic process is proposed to fill up the gap in the missing data. Exploiting this "parametric tomography," a new detection scheme with a limited loss of optimality is proposed as an alternative to the nonlinear generalized likelihood ratio test, which is untractable in the context of nondestructive testing for the objects with uncertainties in their physical/geometrical properties. The theoretical results are illustrated by the processing of real radiographies for the nuclear fuel rod inspection.
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Survival Analysis of Patients with Breast Cancer using Weibull Parametric Model.
Baghestani, Ahmad Reza; Moghaddam, Sahar Saeedi; Majd, Hamid Alavi; Akbari, Mohammad Esmaeil; Nafissi, Nahid; Gohari, Kimiya
2015-01-01
The Cox model is known as one of the most frequently-used methods for analyzing survival data. However, in some situations parametric methods may provide better estimates. In this study, a Weibull parametric model was employed to assess possible prognostic factors that may affect the survival of patients with breast cancer. We studied 438 patients with breast cancer who visited and were treated at the Cancer Research Center in Shahid Beheshti University of Medical Sciences during 1992 to 2012; the patients were followed up until October 2014. Patients or family members were contacted via telephone calls to confirm whether they were still alive. Clinical, pathological, and biological variables as potential prognostic factors were entered in univariate and multivariate analyses. The log-rank test and the Weibull parametric model with a forward approach, respectively, were used for univariate and multivariate analyses. All analyses were performed using STATA version 11. A P-value lower than 0.05 was defined as significant. On univariate analysis, age at diagnosis, level of education, type of surgery, lymph node status, tumor size, stage, histologic grade, estrogen receptor, progesterone receptor, and lymphovascular invasion had a statistically significant effect on survival time. On multivariate analysis, lymph node status, stage, histologic grade, and lymphovascular invasion were statistically significant. The one-year overall survival rate was 98%. Based on these data and using Weibull parametric model with a forward approach, we found out that patients with lymphovascular invasion were at 2.13 times greater risk of death due to breast cancer.
Interpretation and use of statistics in nursing research.
Giuliano, Karen K; Polanowicz, Michelle
2008-01-01
A working understanding of the major fundamentals of statistical analysis is required to incorporate the findings of empirical research into nursing practice. The primary focus of this article is to describe common statistical terms, present some common statistical tests, and explain the interpretation of results from inferential statistics in nursing research. An overview of major concepts in statistics, including the distinction between parametric and nonparametric statistics, different types of data, and the interpretation of statistical significance, is reviewed. Examples of some of the most common statistical techniques used in nursing research, such as the Student independent t test, analysis of variance, and regression, are also discussed. Nursing knowledge based on empirical research plays a fundamental role in the development of evidence-based nursing practice. The ability to interpret and use quantitative findings from nursing research is an essential skill for advanced practice nurses to ensure provision of the best care possible for our patients.
Bifurcations and sensitivity in parametric nonlinear programming
NASA Technical Reports Server (NTRS)
Lundberg, Bruce N.; Poore, Aubrey B.
1990-01-01
The parametric nonlinear programming problem is that of determining the behavior of solution(s) as a parameter or vector of parameters alpha belonging to R(sup r) varies over a region of interest for the problem: Minimize over x the set f(x, alpha):h(x, alpha) = 0, g(x, alpha) is greater than or equal to 0, where f:R(sup (n+r)) approaches R, h:R(sup (n+r)) approaches R(sup q) and g:R(sup (n+r)) approaches R(sup p) are assumed to be at least twice continuously differentiable. Some of these parameters may be fixed but not known precisely and others may be varied to enhance the performance of the system. In both cases a fundamentally important problem in the investigation of global sensitivity of the system is to determine the stability boundaries of the regions in parameter space which define regions of qualitatively similar solutions. The objective is to explain how numerical continuation and bifurcation techniques can be used to investigate the parametric nonlinear programming problem in a global sense. Thus, first the problem is converted to a closed system of parameterized nonlinear equations whose solution set contains all local minimizers of the original problem. This system, which will be represented as F(z,alpha) = O, will include all Karush-Kuhn-Tucker and Fritz John points, both feasible and infeasible solutions, and relative minima, maxima, and saddle points of the problem. The local existence and uniqueness of a solution path (z(alpha), alpha) of this system as well as the solution type persist as long as a singularity in the Jacobian D(sub z)F(z,alpha) is not encountered. Thus the nonsingularity of this Jacobian is characterized in terms of conditions on the problem itself. Then, a class of efficient predictor-corrector continuation procedures for tracing solution paths of the system F(z,alpha) = O which are tailored specifically to the parametric programming problem are described. Finally, these procedures and the obtained information are illustrated
Bifurcations and sensitivity in parametric nonlinear programming
NASA Technical Reports Server (NTRS)
Lundberg, Bruce N.; Poore, Aubrey B.
1990-01-01
The parametric nonlinear programming problem is that of determining the behavior of solution(s) as a parameter or vector of parameters alpha belonging to R(sup r) varies over a region of interest for the problem: Minimize over x the set f(x, alpha):h(x, alpha) = 0, g(x, alpha) is greater than or equal to 0, where f:R(sup (n+r)) approaches R, h:R(sup (n+r)) approaches R(sup q) and g:R(sup (n+r)) approaches R(sup p) are assumed to be at least twice continuously differentiable. Some of these parameters may be fixed but not known precisely and others may be varied to enhance the performance of the system. In both cases a fundamentally important problem in the investigation of global sensitivity of the system is to determine the stability boundaries of the regions in parameter space which define regions of qualitatively similar solutions. The objective is to explain how numerical continuation and bifurcation techniques can be used to investigate the parametric nonlinear programming problem in a global sense. Thus, first the problem is converted to a closed system of parameterized nonlinear equations whose solution set contains all local minimizers of the original problem. This system, which will be represented as F(z,alpha) = O, will include all Karush-Kuhn-Tucker and Fritz John points, both feasible and infeasible solutions, and relative minima, maxima, and saddle points of the problem. The local existence and uniqueness of a solution path (z(alpha), alpha) of this system as well as the solution type persist as long as a singularity in the Jacobian D(sub z)F(z,alpha) is not encountered. Thus the nonsingularity of this Jacobian is characterized in terms of conditions on the problem itself. Then, a class of efficient predictor-corrector continuation procedures for tracing solution paths of the system F(z,alpha) = O which are tailored specifically to the parametric programming problem are described. Finally, these procedures and the obtained information are illustrated
Normal dispersion femtosecond fiber optical parametric oscillator.
Nguyen, T N; Kieu, K; Maslov, A V; Miyawaki, M; Peyghambarian, N
2013-09-15
We propose and demonstrate a synchronously pumped fiber optical parametric oscillator (FOPO) operating in the normal dispersion regime. The FOPO generates chirped pulses at the output, allowing significant pulse energy scaling potential without pulse breaking. The output average power of the FOPO at 1600 nm was ∼60 mW (corresponding to 1.45 nJ pulse energy and ∼55% slope power conversion efficiency). The output pulses directly from the FOPO were highly chirped (∼3 ps duration), and they could be compressed outside of the cavity to 180 fs by using a standard optical fiber compressor. Detailed numerical simulation was also performed to understand the pulse evolution dynamics around the laser cavity. We believe that the proposed design concept is useful for scaling up the pulse energy in the FOPO using different pumping wavelengths.
Compact, flexible, frequency agile parametric wavelength converter
Velsko, Stephan P.; Yang, Steven T.
2002-01-01
This improved Frequency Agile Optical Parametric Oscillator provides near on-axis pumping of a single QPMC with a tilted periodically poled grating to overcome the necessity to find a particular crystal that will permit collinear birefringence in order to obtain a desired tuning range. A tilted grating design and the elongation of the transverse profile of the pump beam in the angle tuning plane of the FA-OPO reduces the rate of change of the overlap between the pumped volume in the crystal and the resonated and non-resonated wave mode volumes as the pump beam angle is changed. A folded mirror set relays the pivot point for beam steering from a beam deflector to the center of the FA-OPO crystal. This reduces the footprint of the device by as much as a factor of two over that obtained when using the refractive telescope design.
Hybrid-free Josephson Parametric Converter
NASA Astrophysics Data System (ADS)
Frattini, N. E.; Narla, A.; Sliwa, K. M.; Shankar, S.; Hatridge, M.; Devoret, M. H.
A necessary component for any quantum computation architecture is the ability to perform efficient quantum operations. In the microwave regime of superconducting qubits, these quantum-limited operations can be realized with a non-degenerate Josephson junction based three-wave mixer, the Josephson Parametric Converter (JPC). Currently, the quantum signal of interest must pass through a lossy 180 degree hybrid to be presented as a differential drive to the JPC. This hybrid therefore places a limit on the quantum efficiency of the system and also increases the device footprint. We present a new design for the JPC eliminating the need for any external hybrid. We also show that this design has nominally identical performance to the conventional JPC. Work supported by ARO, AFOSR and YINQE.
Simplifying the circuit of Josephson parametric converters
NASA Astrophysics Data System (ADS)
Abdo, Baleegh; Brink, Markus; Chavez-Garcia, Jose; Keefe, George
Josephson parametric converters (JPCs) are quantum-limited three-wave mixing devices that can play various important roles in quantum information processing in the microwave domain, including amplification of quantum signals, transduction of quantum information, remote entanglement of qubits, nonreciprocal amplification, and circulation of signals. However, the input-output and biasing circuit of a state-of-the-art JPC consists of bulky components, i.e. two commercial off-chip broadband 180-degree hybrids, four phase-matched short coax cables, and one superconducting magnetic coil. Such bulky hardware significantly hinders the integration of JPCs in scalable quantum computing architectures. In my talk, I will present ideas on how to simplify the JPC circuit and show preliminary experimental results
Parametric analysis of open plan offices
NASA Astrophysics Data System (ADS)
Nogueira, Flavia F.; Viveiros, Elvira B.
2002-11-01
The workspace has been undergoing many changes. Open plan offices are being favored instead of ones of traditional design. In such offices, workstations are separated by partial height barriers, which allow a certain degree of visual privacy and some sound insulation. The challenge in these offices is to provide acoustic privacy for the workstations. Computer simulation was used as a tool for this investigation. Two simple models were generated and their results compared to experimental data measured in two real offices. After validating the approach, models with increasing complexity were generated. Lastly, an ideal office with 64 workstations was created and a parametric survey performed. Nine design parameters were taken as variables and the results are discussed in terms of sound pressure level, in octave bands, and intelligibility index.
Parametric phase diffusion analysis of irregular oscillations
NASA Astrophysics Data System (ADS)
Schwabedal, Justus T. C.
2014-09-01
Parametric phase diffusion analysis (ΦDA), a method to determine variability of irregular oscillations, is presented. ΦDA is formulated as an analysis technique for sequences of Poincaré return times found in numerous applications. The method is unbiased by the arbitrary choice of Poincaré section, i.e. isophase, which causes a spurious component in the Poincaré return times. Other return-time variability measures can be biased drastically by these spurious return times, as shown for the Fano factor of chaotic oscillations in the Rössler system. The empirical use of ΦDA is demonstrated in an application to heart rate data from the Fantasia Database, for which ΦDA parameters successfully classify heart rate variability into groups of age and gender.
Ultrafast Airy beam optical parametric oscillator
Apurv Chaitanya, N.; Kumar, S. Chaitanya; Aadhi, A.; Samanta, G. K.; Ebrahim-Zadeh, M.
2016-01-01
We report on the first realization of an ultrafast Airy beam optical parametric oscillator (OPO). By introducing intracavity cubic phase modulation to the resonant Gaussian signal in a synchronously-pumped singly-resonant OPO cavity and its subsequent Fourier transformation, we have generated 2-dimensional Airy beam in the output signal across a 250 nm tuning range in the near-infrared. The generated Airy beam can be tuned continuously from 1477 to 1727 nm, providing an average power of as much as 306 mW at 1632 nm in pulses of ~23 ps duration with a spectral bandwidth of 1.7 nm. PMID:27476910
Ultrafast Airy beam optical parametric oscillator.
Apurv Chaitanya, N; Kumar, S Chaitanya; Aadhi, A; Samanta, G K; Ebrahim-Zadeh, M
2016-08-01
We report on the first realization of an ultrafast Airy beam optical parametric oscillator (OPO). By introducing intracavity cubic phase modulation to the resonant Gaussian signal in a synchronously-pumped singly-resonant OPO cavity and its subsequent Fourier transformation, we have generated 2-dimensional Airy beam in the output signal across a 250 nm tuning range in the near-infrared. The generated Airy beam can be tuned continuously from 1477 to 1727 nm, providing an average power of as much as 306 mW at 1632 nm in pulses of ~23 ps duration with a spectral bandwidth of 1.7 nm.
uvmcmcfit: Parametric models to interferometric data fitter
NASA Astrophysics Data System (ADS)
Bussmann, Shane; Leung, Tsz Kuk (Daisy); Conley, Alexander
2016-06-01
Uvmcmcfit fits parametric models to interferometric data. It is ideally suited to extract the maximum amount of information from marginally resolved observations with interferometers like the Atacama Large Millimeter Array (ALMA), Submillimeter Array (SMA), and Plateau de Bure Interferometer (PdBI). uvmcmcfit uses emcee (ascl:1303.002) to do Markov Chain Monte Carlo (MCMC) and can measure the goodness of fit from visibilities rather than deconvolved images, an advantage when there is strong gravitational lensing and in other situations. uvmcmcfit includes a pure-Python adaptation of Miriad’s (ascl:1106.007) uvmodel task to generate simulated visibilities given observed visibilities and a model image and a simple ray-tracing routine that allows it to account for both strongly lensed systems (where multiple images of the lensed galaxy are detected) and weakly lensed systems (where only a single image of the lensed galaxy is detected).
mu analysis with real parametric uncertainty
NASA Technical Reports Server (NTRS)
Young, Peter M.; Newlin, Matthew P.; Doyle, John C.
1991-01-01
The authors give a broad overview, from a LFT (linear fractional transformation)/mu perspective, of some of the theoretical and practical issues associated with robustness in the presence of real parametric uncertainty, with a focus on computation. Recent results on the properties of mu in the mixed case are reviewed, including issues of NP completeness, continuity, computation of bounds, the equivalence of mu and its bounds, and some direct comparisons with Kharitonov-type analysis methods. In addition, some advances in the computational aspects of the problem, including a novel branch and bound algorithm, are briefly presented together with numerical results. The results suggest that while the mixed mu problem may have inherently combinatoric worst-case behavior, practical algorithms with modest computational requirements can be developed for problems of medium size (less than 100 parameters) that are of engineering interest.
Parametric systems analysis for tandem mirror hybrids
Lee, J.D.; Chapin, D.L.; Chi, J.W.H.
1980-09-01
Fusion fission systems, consisting of fissile producing fusion hybrids combining a tandem mirror fusion driver with various blanket types and net fissile consuming LWR's, have been modeled and analyzed parametrically. Analysis to date indicates that hybrids can be competitive with mined uranium when U/sub 3/O/sub 8/ cost is about 100 $/lb., adding less than 25% to present day cost of power from LWR's. Of the three blanket types considered, uranium fast fission (UFF), thorium fast fission (ThFF), and thorium fission supressed (ThFS), the ThFS blanket has a modest economic advantage under most conditions but has higher support ratios and potential safety advantages under all conditions.
Parametric study of double cellular detonation structure
NASA Astrophysics Data System (ADS)
Khasainov, B.; Virot, F.; Presles, H.-N.; Desbordes, D.
2013-05-01
A parametric numerical study is performed of a detonation cellular structure in a model gaseous explosive mixture whose decomposition occurs in two successive exothermic reaction steps with markedly different characteristic times. Kinetic and energetic parameters of both reactions are varied in a wide range in the case of one-dimensional steady and two-dimensional (2D) quasi-steady self-supported detonations. The range of governing parameters of both exothermic steps is defined where a "marked" double cellular structure exists. It is shown that the two-level cellular structure is completely governed by the kinetic parameters and the local overdrive ratio of the detonation front propagating inside large cells. Furthermore, since it is quite cumbersome to use detailed chemical kinetics in unsteady 2D case, the proposed work should help to identify the mixtures and the domain of their equivalence ratio where double detonation structure could be observed.
Multidimensional Scaling Visualization Using Parametric Entropy
NASA Astrophysics Data System (ADS)
Lopes, António M.; Tenreiro Machado, J. A.; Galhano, Alexandra M.
2015-12-01
This paper studies complex systems using a generalized multidimensional scaling (MDS) technique. Complex systems are characterized by time-series responses, interpreted as a manifestation of their dynamics. Two types of time-series are analyzed, namely 18 stock markets and the gross domestic product per capita of 18 countries. For constructing the MDS charts, indices based on parametric entropies are adopted. Multiparameter entropies allow the variation of the parameters leading to alternative sets of charts. The final MDS maps are then assembled by means of Procrustes’ method that maximizes the fit between the individual charts. Therefore, the proposed method can be interpreted as a generalization to higher dimensions of the standard technique that represents (and discretizes) items by means of single “points” (i.e. zero-dimensional “objects”). The MDS plots, involving one-, two- and three-dimensional “objects”, reveal a good performance in capturing the correlations between data.
Parametric thermal evaluations of waste package emplacement
Bahney, R.H. III; Doering, T.W.
1996-02-01
Parametric thermal evaluations of spent nuclear fuel (SNF) waste packages (WPs) emplaced in the potential repository were performed to determine the impact of thermal loading, WP spacing, drift diameter, SNF aging, backfill, and relocation on the design of the Engineered Barrier System. Temperatures in the WP and near-field host rock are key to radionuclide containment, as they directly affect oxidation rates of the metal barriers and the ability of the rock to impede particle movement which must be demonstrated for a safe and licensable repository. Maximum allowable temperatures are based on material performance criteria and are specified as the following design goals for the WP/EBS design: SNF cladding 350{degrees}C, drift wall 200{degrees}C, and TSw3 rock 115{degrees}C.
Parametric instability of two coupled nonlinear oscillators
NASA Astrophysics Data System (ADS)
Denardo, Bruce; Earwood, John; Sazonova, Vera
1999-03-01
One of the two normal modes of a system of two coupled nonlinear oscillators is subject to an instability. Several demonstration apparatus of weakly coupled oscillators that exhibit the instability are described. The effect is due to one normal mode parametrically driving the other, and occurs for the broad range of systems where the nonlinearity has a cubic contribution to the restoring force of each oscillator, which includes pendulums. The instability has an amplitude threshold that increases as the coupling is increased. A naive physical approach predicts that the mode opposite to that observed should be unstable. This is resolved by a weakly nonlinear analysis which reveals that the nonlinearity causes the linear frequency of a normal mode to depend upon the finite amplitude of the other mode. Numerical simulations confirm the theory, and extend the existence of the instability and the accuracy of the theoretical amplitude threshold beyond the regime of weak nonlinearity and weak coupling.
Lensed: Forward parametric modelling of strong lenses
NASA Astrophysics Data System (ADS)
Tessore, Nicolas; Bellagamba, Fabio; Metcalf, R. Benton
2015-05-01
Lensed performs forward parametric modelling of strong lenses. Using a provided model, Lensed renders the expected image of the lensing event for a large number of parameter settings, thereby exploring the space of possible realizations of the observation. It compares the expectation to the observed image by calculating the likelihood that the observation was indeed produced by the assumed model, thus reconstructing the probability distribution over the parameter space of the model. Written in C, the code uses a massively parallel ray-tracing kernel to perform the necessary calculations on a graphics processing unit (GPU), making the precise rendering of the background lensed sources fast and allowing the simultaneous optimization of tens of parameters for the selected model.
Parametric study on propulsion performance of microtubes
NASA Astrophysics Data System (ADS)
Tantos, Ch.; Valougeorgis, D.
2017-06-01
The pressure-driven rarefied gas §ow of polyatomic gases through short tubes in a wide range of the Knudsen number is numerically investigated. The downstream over the upstream pressure ratio is taken very close to zero. Such flows are characterized by low Reynolds numbers and high viscous losses and, therefore, short circular microtubes may be used instead of typical micronozzles. The main computed quantities include the flow rate, the discharge coefficient, the thrust, and the impulse factor which are provided in terms of the gas rarefaction and the tube dimensionless length. Based on the above, a parametric study on the propulsion characteristics of microtubes is provided. Furthermore, a comparison between corresponding polyatomic and monoatomic results is performed and the effect of the internal degrees of freedom on the results is investigated.
Parametric reconstruction method in optical tomography.
Gu, Xuejun; Ren, Kui; Masciotti, James; Hielscher, Andreas H
2006-01-01
Optical tomography consists of reconstructing the spatial of a medium's optical properties from measurements of transmitted light on the boundary of the medium. Mathematically this problem amounts to parameter identification for the radiative transport equation (ERT) or diffusion approximation (DA). However, this type of boundary-value problem is highly ill-posed and the image reconstruction process is often unstable and non-unique. To overcome this problem, we present a parametric inverse method that considerably reduces the number of variables being reconstructed. In this way the amount of measured data is equal or larger than the number of unknowns. Using synthetic data, we show examples that demonstrate how this approach leads to improvements in imaging quality.
Spherical parametrization of the Higgs boson candidate.
Gainer, James S; Lykken, Joseph; Matchev, Konstantin T; Mrenna, Stephen; Park, Myeonghun
2013-07-26
The latest results from the ATLAS and CMS experiments at the CERN Large Hadron Collider unequivocally confirm the existence of a resonance X with mass near 125 GeV which could be the Higgs boson of the standard model. Measuring the properties (quantum numbers and couplings) of this resonance is of paramount importance. Initial analyses by the LHC Collaborations disfavor specific alternative benchmark hypotheses, e.g., pure pseudoscalars or gravitons. However, this is just the first step in a long-term program of detailed measurements. We consider the most general set of operators in the decay channels X→ZZ, WW, Zγ, γγ, and derive the constraint implied by the measured rate. This allows us to provide a useful parametrization of the orthogonal independent Higgs coupling degrees of freedom as coordinates on a suitably defined sphere.
A parametric approach to irregular fatigue prediction
NASA Technical Reports Server (NTRS)
Erismann, T. H.
1972-01-01
A parametric approach to irregular fatigue protection is presented. The method proposed consists of two parts: empirical determination of certain characteristics of a material by means of a relatively small number of well-defined standard tests, and arithmetical application of the results obtained to arbitrary loading histories. The following groups of parameters are thus taken into account: (1) the variations of the mean stress, (2) the interaction of these variations and the superposed oscillating stresses, (3) the spectrum of the oscillating-stress amplitudes, and (4) the sequence of the oscillating-stress amplitudes. It is pointed out that only experimental verification can throw sufficient light upon possibilities and limitations of this (or any other) prediction method.
Ultrafast Airy beam optical parametric oscillator
NASA Astrophysics Data System (ADS)
Apurv Chaitanya, N.; Kumar, S. Chaitanya; Aadhi, A.; Samanta, G. K.; Ebrahim-Zadeh, M.
2016-08-01
We report on the first realization of an ultrafast Airy beam optical parametric oscillator (OPO). By introducing intracavity cubic phase modulation to the resonant Gaussian signal in a synchronously-pumped singly-resonant OPO cavity and its subsequent Fourier transformation, we have generated 2-dimensional Airy beam in the output signal across a 250 nm tuning range in the near-infrared. The generated Airy beam can be tuned continuously from 1477 to 1727 nm, providing an average power of as much as 306 mW at 1632 nm in pulses of ~23 ps duration with a spectral bandwidth of 1.7 nm.
Parametric and experimental analysis using a power flow approach
NASA Technical Reports Server (NTRS)
Cuschieri, J. M.
1988-01-01
Having defined and developed a structural power flow approach for the analysis of structure-borne transmission of structural vibrations, the technique is used to perform an analysis of the influence of structural parameters on the transmitted energy. As a base for comparison, the parametric analysis is first performed using a Statistical Energy Analysis approach and the results compared with those obtained using the power flow approach. The advantages of using structural power flow are thus demonstrated by comparing the type of results obtained by the two methods. Additionally, to demonstrate the advantages of using the power flow method and to show that the power flow results represent a direct physical parameter that can be measured on a typical structure, an experimental investigation of structural power flow is also presented. Results are presented for an L-shaped beam for which an analytical solution has already been obtained. Furthermore, the various methods available to measure vibrational power flow are compared to investigate the advantages and disadvantages of each method.
Semiautomated Workflow for Clinically Streamlined Glioma Parametric Response Mapping
Keith, Lauren; Ross, Brian D.; Galbán, Craig J.; Luker, Gary D.; Galbán, Stefanie; Zhao, Binsheng; Guo, Xiaotao; Chenevert, Thomas L.; Hoff, Benjamin A.
2017-01-01
Management of glioblastoma multiforme remains a challenging problem despite recent advances in targeted therapies. Timely assessment of therapeutic agents is hindered by the lack of standard quantitative imaging protocols for determining targeted response. Clinical response assessment for brain tumors is determined by volumetric changes assessed at 10 weeks post-treatment initiation. Further, current clinical criteria fail to use advanced quantitative imaging approaches, such as diffusion and perfusion magnetic resonance imaging. Development of the parametric response mapping (PRM) applied to diffusion-weighted magnetic resonance imaging has provided a sensitive and early biomarker of successful cytotoxic therapy in brain tumors while maintaining a spatial context within the tumor. Although PRM provides an earlier readout than volumetry and sometimes greater sensitivity compared with traditional whole-tumor diffusion statistics, it is not routinely used for patient management; an automated and standardized software for performing the analysis and for the generation of a clinical report document is required for this. We present a semiautomated and seamless workflow for image coregistration, segmentation, and PRM classification of glioblastoma multiforme diffusion-weighted magnetic resonance imaging scans. The software solution can be integrated using local hardware or performed remotely in the cloud while providing connectivity to existing picture archive and communication systems. This is an important step toward implementing PRM analysis of solid tumors in routine clinical practice. PMID:28286871
Parametric estimation of the orientation of textured planar surfaces.
Francos, J M; Permuter, H H
2001-01-01
This paper presents a parametric solution to the problem of estimating the orientation in space of a planar textured surface, from a single, noisy, observed image of it. The coordinate transformation from surface to image coordinates, due to the perspective projection, transforms each homogeneous sinusoidal component of the surface texture into a sinusoid whose frequency is a function of location. The functional dependence of the sinusoid phase in location is uniquely determined by the tilt and slant angles of the surface. Using the phase differencing algorithm we fit a polynomial phase model to a sinusoidal component of the observed texture. Assuming the estimated polynomial coefficients are the coefficients of a Taylor series expansion of the phase, we establish a linear recursive relation between the model parameters and the unknown slant and tilt. A linear least squares solution of the resulting system provides the slant and tilt estimates. To improve accuracy, an iterative refinement procedure is applied in a small neighborhood of these estimates. The performance of the proposed algorithms is evaluated by applying them to images of different planar surfaces, and by comparing their statistical performance with the Cramer-Rao bound. The combined two-stage algorithm is shown to produce estimates that are close to the bound.
A parametric estimation approach to instantaneous spectral imaging.
Oktem, Figen S; Kamalabadi, Farzad; Davila, Joseph M
2014-12-01
Spectral imaging, the simultaneous imaging and spectroscopy of a radiating scene, is a fundamental diagnostic technique in the physical sciences with widespread application. Due to the intrinsic limitation of two-dimensional (2D) detectors in capturing inherently three-dimensional (3D) data, spectral imaging techniques conventionally rely on a spatial or spectral scanning process, which renders them unsuitable for dynamic scenes. In this paper, we present a nonscanning (instantaneous) spectral imaging technique that estimates the physical parameters of interest by combining measurements with a parametric model and solving the resultant inverse problem computationally. The associated inverse problem, which can be viewed as a multiframe semiblind deblurring problem (with shift-variant blur), is formulated as a maximum a posteriori (MAP) estimation problem since in many such experiments prior statistical knowledge of the physical parameters can be well estimated. Subsequently, an efficient dynamic programming algorithm is developed to find the global optimum of the nonconvex MAP problem. Finally, the algorithm and the effectiveness of the spectral imaging technique are illustrated for an application in solar spectral imaging. Numerical simulation results indicate that the physical parameters can be estimated with the same order of accuracy as state-of-the-art slit spectroscopy but with the added benefit of an instantaneous, 2D field-of-view. This technique will be particularly useful for studying the spectra of dynamic scenes encountered in space remote sensing.
Mechanism for an absolute parametric instability of an inhomogeneous plasma
NASA Astrophysics Data System (ADS)
Arkhipenko, V. I.; Budnikov, V. N.; Gusakov, E. Z.; Romanchuk, I. A.; Simonchik, L. V.
1984-05-01
The structure of plasma oscillations in a region of parametric spatial amplification has been studied experimentally for the first time. A new mechanism for an absolute parametric instability has been observed. This mechanism operates when a pump wave with a spatial structure more complicated than a plane wave propagates through a plasma which is inhomogeneous along more than one dimension.
Using a Parametric Solid Modeler as an Instructional Tool
ERIC Educational Resources Information Center
Devine, Kevin L.
2008-01-01
This paper presents the results of a quasi-experimental study that brought 3D constraint-based parametric solid modeling technology into the high school mathematics classroom. This study used two intact groups; a control group and an experimental group, to measure the extent to which using a parametric solid modeler during instruction affects…
Parametrization of the SCC-DFTB Method for Halogens.
Kubař, Tomáš; Bodrog, Zoltán; Gaus, Michael; Köhler, Christof; Aradi, Bálint; Frauenheim, Thomas; Elstner, Marcus
2013-07-09
Parametrization of the approximative DFT method SCC-DFTB for halogen elements is presented. The new parameter set is intended to describe halogenated organic as well as inorganic molecules, and it is compatible with the established parametrization of SCC-DFTB for carbon, hydrogen, oxygen, and nitrogen. The performance of the parameter set is tested on a representative set of molecules and discussed.
Injection-seeded optical parametric oscillator and system
Lucht, Robert P.; Kulatilaka, Waruna D.; Anderson, Thomas N.; Bougher, Thomas L.
2007-10-09
Optical parametric oscillators (OPO) and systems are provided. The OPO has a non-linear optical material located between two optical elements where the product of the reflection coefficients of the optical elements are higher at the output wavelength than at either the pump or idler wavelength. The OPO output may be amplified using an additional optical parametric amplifier (OPA) stage.
Parametric Equations: Push 'Em Back, Push 'Em Back, Way Back!
ERIC Educational Resources Information Center
Cieply, Joseph F.
1993-01-01
Stresses using the features of graphing calculators to teach parametric equations much earlier in the curriculum than is presently done. Examples using parametric equations to teach slopes and lines in beginning algebra, inverse functions in advanced algebra, the wrapping function, and simulations of physical phenomena are presented. (MAZ)
Using a Parametric Solid Modeler as an Instructional Tool
ERIC Educational Resources Information Center
Devine, Kevin L.
2008-01-01
This paper presents the results of a quasi-experimental study that brought 3D constraint-based parametric solid modeling technology into the high school mathematics classroom. This study used two intact groups; a control group and an experimental group, to measure the extent to which using a parametric solid modeler during instruction affects…
Concomitant information in bioassay and semi-parametric estimation.
Kim, Peter T; Lee, Christine H
2005-05-15
This paper presents a flexible modern approach to handling concomitant information for estimating the relative potency parameter in quantitative bioassays. This is accomplished in a semi-parametric framework where the concomitant variable is included non-parametrically. Estimation is then performed using smoothing splines where the point and interval estimators of the relative potency parameter exhibits desirable asymptotic properties.
Tuneable, non-degenerated, nonlinear, parametrically-excited amplifier
NASA Astrophysics Data System (ADS)
Dolev, Amit; Bucher, Izhak
2016-01-01
The proposed parametric amplifier scheme can be tuned to amplify a wide range of input frequencies by altering the parametric excitation with no need to physically modify the oscillator. Parametric amplifiers had been studied extensively, although most of the work focused on amplifiers that are parametrically excited at a frequency twice the amplifier's natural frequency. These amplifiers are confined to amplifying predetermined frequencies. The proposed parametric amplifier's bandwidth is indeed tuneable to nearly any input frequency, not bound to be an integer multiple of a natural frequency. In order to tune the stiffness and induce a variable frequency parametric excitation, a digitally controlled electromechanical element must be incorporated in the realization. We introduce a novel parametric amplifier with nonlinearity, Duffing type hardening, that bounds the otherwise unlimited amplitude. Moreover, we present a multi degree of freedom system in which a utilization of the proposed method enables the projection of low frequency vector forces on any eigenvector and corresponding natural frequency of the system, and thus to transform external excitations to a frequency band where signal levels are considerably higher. Using the method of multiple scales, analytical expressions for the responses have been retrieved and verified numerically. Parametric studies of the amplifiers' gain, sensitivities and spatial projection of the excitation on the system eigenvectors were carried out analytically. The results demonstrate the advantage of the proposed approach over existing schemes. Practical applications envisaged for the proposed method will be outlined.
Schwinger-type parametrization of open string worldsheets
NASA Astrophysics Data System (ADS)
Playle, Sam; Sciuto, Stefano
2017-03-01
A parametrization of (super) moduli space near the corners corresponding to bosonic or Neveu-Schwarz open string degenerations is introduced for worldsheets of arbitrary topology. With this parametrization, Feynman graph polynomials arise as the α‧ → 0 limit of objects on moduli space. Furthermore, the integration measures of string theory take on a very simple and elegant form.
Evaluation of Two Energy Balance Closure Parametrizations
NASA Astrophysics Data System (ADS)
Eder, Fabian; De Roo, Frederik; Kohnert, Katrin; Desjardins, Raymond L.; Schmid, Hans Peter; Mauder, Matthias
2014-05-01
A general lack of energy balance closure indicates that tower-based eddy-covariance (EC) measurements underestimate turbulent heat fluxes, which calls for robust correction schemes. Two parametrization approaches that can be found in the literature were tested using data from the Canadian Twin Otter research aircraft and from tower-based measurements of the German Terrestrial Environmental Observatories (TERENO) programme. Our analysis shows that the approach of Huang et al. (Boundary-Layer Meteorol 127:273-292, 2008), based on large-eddy simulation, is not applicable to typical near-surface flux measurements because it was developed for heights above the surface layer and over homogeneous terrain. The biggest shortcoming of this parametrization is that the grid resolution of the model was too coarse so that the surface layer, where EC measurements are usually made, is not properly resolved. The empirical approach of Panin and Bernhofer (Izvestiya Atmos Oceanic Phys 44:701-716, 2008) considers landscape-level roughness heterogeneities that induce secondary circulations and at least gives a qualitative estimate of the energy balance closure. However, it does not consider any feature of landscape-scale heterogeneity other than surface roughness, such as surface temperature, surface moisture or topography. The failures of both approaches might indicate that the influence of mesoscale structures is not a sufficient explanation for the energy balance closure problem. However, our analysis of different wind-direction sectors shows that the upwind landscape-scale heterogeneity indeed influences the energy balance closure determined from tower flux data. We also analyzed the aircraft measurements with respect to the partitioning of the "missing energy" between sensible and latent heat fluxes and we could confirm the assumption of scalar similarity only for Bowen ratios 1.
Parametrization of turbulent fluxes over inhomogeneous landscapes
NASA Astrophysics Data System (ADS)
Panin, G. N.; Bernhofer, Ch.
2008-12-01
Reasons for the nonclosure of the heat balance in the atmospheric boundary layers over natural land surfaces are analyzed. Results of measuring the heat-balance components over different land surfaces are used. The Cabauw (Netherlands) data (obtained throughout 1996 over a grass surface with intermittent shrubs and single trees) and the data from the Anchor station in Germany (measured over coniferous forest in 2000-2001) are analyzed. In all, the analysis involves about fifty thousand independent values of the heat-balance components measured in the experiments, which should be indicative of the reliability of the results obtained in the paper. The data have shown that the heat balance is not closed and the imbalance is 50-250 W/m2. The sum of the latent and sensible heat fluxes λ E + H = STF is found to be systematically smaller than the difference between the net radiation and the heat flux into the ground R n - G. It is shown that the main cause of a systematic heat imbalance in the atmospheric boundary layers over inhomogeneous land surfaces is that the methods of surface-flux measurement and estimation are based on the theory that requires the hypothesis of stationarity and horizontal homogeneity. Direct data analysis has shown that the heat imbalance increases with landscape inhomogeneity. In the paper, a parametrization of the heat imbalance is carried out and the coefficient k f ( z {0/ ef }/ L ef ) is introduced as a measure of inhomogeneity. For this, data from the experiments FIFE, KUREX, TARTEX, SADE, etc., are also used. Empirical formulas are presented to refine the results of direct measurements and calculations of surface fluxes over natural (inhomogeneous) land surfaces from profile and standard (using bulk parametrizations) data. These formulas can also be used to determine surface fluxes over inhomogeneous underlying land surfaces in order to take into account so-called subgrid-scale effects in constructing prediction models.
Parametric cost estimation for space science missions
NASA Astrophysics Data System (ADS)
Lillie, Charles F.; Thompson, Bruce E.
2008-07-01
Cost estimation for space science missions is critically important in budgeting for successful missions. The process requires consideration of a number of parameters, where many of the values are only known to a limited accuracy. The results of cost estimation are not perfect, but must be calculated and compared with the estimates that the government uses for budgeting purposes. Uncertainties in the input parameters result from evolving requirements for missions that are typically the "first of a kind" with "state-of-the-art" instruments and new spacecraft and payload technologies that make it difficult to base estimates on the cost histories of previous missions. Even the cost of heritage avionics is uncertain due to parts obsolescence and the resulting redesign work. Through experience and use of industry best practices developed in participation with the Aerospace Industries Association (AIA), Northrop Grumman has developed a parametric modeling approach that can provide a reasonably accurate cost range and most probable cost for future space missions. During the initial mission phases, the approach uses mass- and powerbased cost estimating relationships (CER)'s developed with historical data from previous missions. In later mission phases, when the mission requirements are better defined, these estimates are updated with vendor's bids and "bottoms- up", "grass-roots" material and labor cost estimates based on detailed schedules and assigned tasks. In this paper we describe how we develop our CER's for parametric cost estimation and how they can be applied to estimate the costs for future space science missions like those presented to the Astronomy & Astrophysics Decadal Survey Study Committees.
A Methodology for the Parametric Reconstruction of Non-Steady and Noisy Meteorological Time Series
NASA Astrophysics Data System (ADS)
Rovira, F.; Palau, J. L.; Millán, M.
2009-09-01
Climatic and meteorological time series often show some persistence (in time) in the variability of certain features. One could regard annual, seasonal and diurnal time variability as trivial persistence in the variability of some meteorological magnitudes (as, e.g., global radiation, air temperature above surface, etc.). In these cases, the traditional Fourier transform into frequency space will show the principal harmonics as the components with the largest amplitude. Nevertheless, meteorological measurements often show other non-steady (in time) variability. Some fluctuations in measurements (at different time scales) are driven by processes that prevail on some days (or months) of the year but disappear on others. By decomposing a time series into time-frequency space through the continuous wavelet transformation, one is able to determine both the dominant modes of variability and how those modes vary in time. This study is based on a numerical methodology to analyse non-steady principal harmonics in noisy meteorological time series. This methodology combines both the continuous wavelet transform and the development of a parametric model that includes the time evolution of the principal and the most statistically significant harmonics of the original time series. The parameterisation scheme proposed in this study consists of reproducing the original time series by means of a statistically significant finite sum of sinusoidal signals (waves), each defined by using the three usual parameters: amplitude, frequency and phase. To ensure the statistical significance of the parametric reconstruction of the original signal, we propose a standard statistical t-student analysis of the confidence level of the amplitude in the parametric spectrum for the different wave components. Once we have assured the level of significance of the different waves composing the parametric model, we can obtain the statistically significant principal harmonics (in time) of the original
Scaling of preferential flow in biopores by parametric or non parametric transfer functions
NASA Astrophysics Data System (ADS)
Zehe, E.; Hartmann, N.; Klaus, J.; Palm, J.; Schroeder, B.
2009-04-01
Rapid flow in connected macropores - often worm burrows or sometimes shrinkage cracks - is today accepted to play a key role for transport of agro chemicals in cohesive soils. Nevertheless, we still struggle to come up with reliable predictions at the field or even the catchment scale, also because crucial information on the spatial distribution of connected subsurface structures is most difficult to access. Assessing the environmental risk of pesticides transport in earthworm burrows requires the development of an integrated eco-hydrological model that allows predictions of a) the spatiotemporal distribution and population dynamics of anecic earthworms, b) the related pattern of connective preferential flow pathways (i.e., earthworm burrows), and c) the space-time pattern of infiltration and travel times distribution of solutes considering short and long term feedbacks. The suggested paper will present the first steps towards this long term goal of the so called BIOPORE project. The first step is to assess statistical data on the spatial distribution of worm burrows in the study area. Deep digging earthworms create mainly vertical semi-permanent burrows of moderate tortuosity down to a depth of 3m (Shipitalo and Butt, 1999). Data on the spatial density of worm burrows and their depth is gathered by preparing horizontal soil profiles (Zehe and Fluehler, 2001). Hydraulic properties of worm burrows are straightforward to measure either by means of a special permeameter (Shipitalo and Butt, 1999) or by taking macroporous samples to the lab. The next step is to establish a link between the distribution of travel depths of a tracer/pesticide that occurs during events and the depth distribution of connected flow paths that link the surface continuously to the subsoils. To this end we generate a population of macropores using a Poisson process for the number of macropores per model element, a normal process compared with an anisotropic random walk for pore lengths and
Time reversal of parametrical driving and the stability of the parametrically excited pendulum
NASA Astrophysics Data System (ADS)
Stannarius, Ralf
2009-02-01
It is well known that the periodic driving of a parametrically excited pendulum can stabilize or destabilize its stationary states, depending upon the frequency, wave form, and amplitude of the parameter modulations. We discuss the effect of time reversal of the periodic driving function for the parametric pendulum at small elongations. Such a time reversal usually leads to different solutions of the equations of motion and to different stability properties of the system. Two interesting exceptions are discussed, and two conditions are formulated for which the character of the solutions of the system is not influenced by a time reversal of the driving function, even though the trajectories of the dynamic variables are different.
Aniolek, K W; Schmitt, R L; Kulp, T J; Richman, B A; Bisson, S E; Powers, P E
2000-04-15
For what is believed to be the first time, a single-longitudinal-mode passively Q-switched Nd:YAG microlaser is used to pump a narrow-bandwidth periodically poled lithium niobate (PPLN) optical parametric generator-optical parametric amplifier (OPG-OPA). Before amplification in the OPA, the output of the OPG stage was spectrally filtered with an air-spaced etalon, resulting in spectroscopically useful radiation (bandwidth, ~0.05 cm(-1) FWHM) that was tunable in 15-cm(-1) segments anywhere in the signal range 6820-6220 cm(-1) and the idler range 2580-3180 cm(-1). The ability to pump an OPG-OPA with compact, high-repetition-rate, intrinsically narrow-bandwidth microlasers is made possible by the high gain of PPLN. The result is a tunable light source that is well suited for use in portable spectroscopic gas sensors.
Tollenaar, Nikolaj; Mooijaart, Ab
2003-11-01
In sparse tables for categorical data well-known goodness-of-fit statistics are not chi-square distributed. A consequence is that model selection becomes a problem. It has been suggested that a way out of this problem is the use of the parametric bootstrap. In this paper, the parametric bootstrap goodness-of-fit test is studied by means of an extensive simulation study; the Type I error rates and power of this test are studied under several conditions of sparseness. In the presence of sparseness, models were used that were likely to violate the regularity conditions. Besides bootstrapping the goodness-of-fit usually used (full information statistics), corrected versions of these statistics and a limited information statistic are bootstrapped. These bootstrap tests were also compared to an asymptotic test using limited information. Results indicate that bootstrapping the usual statistics fails because these tests are too liberal, and that bootstrapping or asymptotically testing the limited information statistic works better with respect to Type I error and outperforms the other statistics by far in terms of statistical power. The properties of all tests are illustrated using categorical Markov models.
A new parametrization and minimal model for glacier calving
NASA Astrophysics Data System (ADS)
Lüthi, Martin; Vieli, Andreas; Mercenier, Rémy
2017-04-01
The iceberg calving process influences the geometry of a tidewater glacier, and is in turn controlled by the terminus geometry through the stress field which controls damage and fracture of the ice. A simple parametrization of the stress field at the glacier terminus is obtained from the results of a Finite Element model with varying water depths. Using this stress field in an isotropic damage evolution equation yields calving rates in dependence of calving front thickness and water depth. These parametrized calving rates compare favorably with observations, and extend well established parametrizations. The proposed calving parametrization is easy to implement in numerical ice sheet models. Using these parametrized calving rates in a minimal calving model allows us to analyze the intricate feedbacks of the calving process, to reproduce observed tidewater glacier dynamics, and to analyze the stability of glacier termini.
Non-parametric approach to the study of phenotypic stability.
Ferreira, D F; Fernandes, S B; Bruzi, A T; Ramalho, M A P
2016-02-19
The aim of this study was to undertake the theoretical derivations of non-parametric methods, which use linear regressions based on rank order, for stability analyses. These methods were extension different parametric methods used for stability analyses and the result was compared with a standard non-parametric method. Intensive computational methods (e.g., bootstrap and permutation) were applied, and data from the plant-breeding program of the Biology Department of UFLA (Minas Gerais, Brazil) were used to illustrate and compare the tests. The non-parametric stability methods were effective for the evaluation of phenotypic stability. In the presence of variance heterogeneity, the non-parametric methods exhibited greater power of discrimination when determining the phenotypic stability of genotypes.
Image interpolation by two-dimensional parametric cubic convolution.
Shi, Jiazheng; Reichenbach, Stephen E
2006-07-01
Cubic convolution is a popular method for image interpolation. Traditionally, the piecewise-cubic kernel has been derived in one dimension with one parameter and applied to two-dimensional (2-D) images in a separable fashion. However, images typically are statistically nonseparable, which motivates this investigation of nonseparable cubic convolution. This paper derives two new nonseparable, 2-D cubic-convolution kernels. The first kernel, with three parameters (designated 2D-3PCC), is the most general 2-D, piecewise-cubic interpolator defined on [-2, 2] x [-2, 2] with constraints for biaxial symmetry, diagonal (or 90 degrees rotational) symmetry, continuity, and smoothness. The second kernel, with five parameters (designated 2D-5PCC), relaxes the constraint of diagonal symmetry, based on the observation that many images have rotationally asymmetric statistical properties. This paper also develops a closed-form solution for determining the optimal parameter values for parametric cubic-convolution kernels with respect to ensembles of scenes characterized by autocorrelation (or power spectrum). This solution establishes a practical foundation for adaptive interpolation based on local autocorrelation estimates. Quantitative fidelity analyses and visual experiments indicate that these new methods can outperform several popular interpolation methods. An analysis of the error budgets for reconstruction error associated with blurring and aliasing illustrates that the methods improve interpolation fidelity for images with aliased components. For images with little or no aliasing, the methods yield results similar to other popular methods. Both 2D-3PCC and 2D-5PCC are low-order polynomials with small spatial support and so are easy to implement and efficient to apply.
NASA Technical Reports Server (NTRS)
Coverse, G. L.
1984-01-01
A turbine modeling technique has been developed which will enable the user to obtain consistent and rapid off-design performance from design point input. This technique is applicable to both axial and radial flow turbine with flow sizes ranging from about one pound per second to several hundred pounds per second. The axial flow turbines may or may not include variable geometry in the first stage nozzle. A user-specified option will also permit the calculation of design point cooling flow levels and corresponding changes in efficiency for the axial flow turbines. The modeling technique has been incorporated into a time-sharing program in order to facilitate its use. Because this report contains a description of the input output data, values of typical inputs, and example cases, it is suitable as a user's manual. This report is the second of a three volume set. The titles of the three volumes are as follows: (1) Volume 1 CMGEN USER's Manual (Parametric Compressor Generator); (2) Volume 2 PART USER's Manual (Parametric Turbine); (3) Volume 3 MODFAN USER's Manual (Parametric Modulation Flow Fan).
Photon Statistics of Propagating Thermal Microwaves
NASA Astrophysics Data System (ADS)
Goetz, J.; Pogorzalek, S.; Deppe, F.; Fedorov, K. G.; Eder, P.; Fischer, M.; Wulschner, F.; Xie, E.; Marx, A.; Gross, R.
2017-03-01
In experiments with superconducting quantum circuits, characterizing the photon statistics of propagating microwave fields is a fundamental task. We quantify the n2+n photon number variance of thermal microwave photons emitted from a blackbody radiator for mean photon numbers, 0.05 ≲n ≲1.5 . We probe the fields using either correlation measurements or a transmon qubit coupled to a microwave resonator. Our experiments provide a precise quantitative characterization of weak microwave states and information on the noise emitted by a Josephson parametric amplifier.
Statistical variation in progressive scrambling
NASA Astrophysics Data System (ADS)
Clark, Robert D.; Fox, Peter C.
2004-07-01
The two methods most often used to evaluate the robustness and predictivity of partial least squares (PLS) models are cross-validation and response randomization. Both methods may be overly optimistic for data sets that contain redundant observations, however. The kinds of perturbation analysis widely used for evaluating model stability in the context of ordinary least squares regression are only applicable when the descriptors are independent of each other and errors are independent and normally distributed; neither assumption holds for QSAR in general and for PLS in particular. Progressive scrambling is a novel, non-parametric approach to perturbing models in the response space in a way that does not disturb the underlying covariance structure of the data. Here, we introduce adjustments for two of the characteristic values produced by a progressive scrambling analysis - the deprecated predictivity (Q_s^{ast^2}) and standard error of prediction (SDEP s * ) - that correct for the effect of introduced perturbation. We also explore the statistical behavior of the adjusted values (Q_0^{ast^2} and SDEP 0 * ) and the sensitivity to perturbation (d q 2/d r yy ' 2). It is shown that the three statistics are all robust for stable PLS models, in terms of the stochastic component of their determination and of their variation due to sampling effects involved in training set selection.
Statistical properties of cosmological billiards
NASA Astrophysics Data System (ADS)
Damour, Thibault; Lecian, Orchidea Maria
2011-02-01
Belinski, Khalatnikov, and Lifshitz pioneered the study of the statistical properties of the never-ending oscillatory behavior (among successive Kasner epochs) of the geometry near a spacelike singularity. We show how the use of a “cosmological billiard” description allows one to refine and deepen the understanding of these statistical properties. Contrary to previous treatments, we do not quotient the dynamics by its discrete symmetry group (of order 6), thereby uncovering new phenomena, such as correlations between the successive billiard corners in which the oscillations take place. Starting from the general integral invariants of Hamiltonian systems, we show how to construct invariant measures for various projections of the cosmological-billiard dynamics. In particular, we exhibit, for the first time, a (non-normalizable) invariant measure on the “Kasner circle” which parametrizes the exponents of successive Kasner epochs. Finally, we discuss the relation between: (i) the unquotiented dynamics of the Bianchi-IX (a, b, c or mixmaster) model; (ii) its quotienting by the group of permutations of (a, b, c); and (iii) the billiard dynamics that arose in recent studies suggesting the hidden presence of Kac-Moody symmetries in cosmological billiards.
Application of Transformations in Parametric Inference
ERIC Educational Resources Information Center
Brownstein, Naomi; Pensky, Marianna
2008-01-01
The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…
Application of Transformations in Parametric Inference
ERIC Educational Resources Information Center
Brownstein, Naomi; Pensky, Marianna
2008-01-01
The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…
Tatarinova, Tatiana; Neely, Michael; Bartroff, Jay; van Guilder, Michael; Yamada, Walter; Bayard, David; Jelliffe, Roger; Leary, Robert; Chubatiuk, Alyona; Schumitzky, Alan
2013-04-01
Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian (B) approaches. In this paper we discuss the nonparametric case using both maximum likelihood and Bayesian approaches. We present two nonparametric methods for estimating the unknown joint population distribution of model parameter values in a pharmacokinetic/pharmacodynamic (PK/PD) dataset. The first method is the NP Adaptive Grid (NPAG). The second is the NP Bayesian (NPB) algorithm with a stick-breaking process to construct a Dirichlet prior. Our objective is to compare the performance of these two methods using a simulated PK/PD dataset. Our results showed excellent performance of NPAG and NPB in a realistically simulated PK study. This simulation allowed us to have benchmarks in the form of the true population parameters to compare with the estimates produced by the two methods, while incorporating challenges like unbalanced sample times and sample numbers as well as the ability to include the covariate of patient weight. We conclude that both NPML and NPB can be used in realistic PK/PD population analysis problems. The advantages of one versus the other are discussed in the paper. NPAG and NPB are implemented in R and freely available for download within the Pmetrics package from www.lapk.org.
Neely, Michael; Bartroff, Jay; van Guilder, Michael; Yamada, Walter; Bayard, David; Jelliffe, Roger; Leary, Robert; Chubatiuk, Alyona; Schumitzky, Alan
2013-01-01
Population pharmacokinetic (PK) modeling methods can be statistically classified as either parametric or nonparametric (NP). Each classification can be divided into maximum likelihood (ML) or Bayesian (B) approazches. In this paper we discuss the nonparametric case using both maximum likelihood and Bayesian approaches. We present two nonparametric methods for estimating the unknown joint population distribution of model parameter values in a pharmacokinetic/pharmacodynamic (PK/PD) dataset. The first method is the NP Adaptive Grid (NPAG). The second is the NP Bayesian (NPB) algorithm with a stick-breaking process to construct a Dirichlet prior. Our objective is to compare the performance of these two methods using a simulated PK/PD dataset. Our results showed excellent performance of NPAG and NPB in a realistically simulated PK study. This simulation allowed us to have benchmarks in the form of the true population parameters to compare with the estimates produced by the two methods, while incorporating challenges like unbalanced sample times and sample numbers as well as the ability to include the covariate of patient weight. We conclude that both NPML and NPB can be used in realistic PK/PD population analysis problems. The advantages of one versus the other are discussed in the paper. NPAG and NPB are implemented in R and freely available for download within the Pmetrics package from www.lapk.org. PMID:23404393
Comparison of Three Statistical Classification Techniques for Maser Identification
NASA Astrophysics Data System (ADS)
Manning, Ellen M.; Holland, Barbara R.; Ellingsen, Simon P.; Breen, Shari L.; Chen, Xi; Humphries, Melissa
2016-04-01
We applied three statistical classification techniques-linear discriminant analysis (LDA), logistic regression, and random forests-to three astronomical datasets associated with searches for interstellar masers. We compared the performance of these methods in identifying whether specific mid-infrared or millimetre continuum sources are likely to have associated interstellar masers. We also discuss the interpretability of the results of each classification technique. Non-parametric methods have the potential to make accurate predictions when there are complex relationships between critical parameters. We found that for the small datasets the parametric methods logistic regression and LDA performed best, for the largest dataset the non-parametric method of random forests performed with comparable accuracy to parametric techniques, rather than any significant improvement. This suggests that at least for the specific examples investigated here accuracy of the predictions obtained is not being limited by the use of parametric models. We also found that for LDA, transformation of the data to match a normal distribution led to a significant improvement in accuracy. The different classification techniques had significant overlap in their predictions; further astronomical observations will enable the accuracy of these predictions to be tested.
... Standards Act and Program MQSA Insights MQSA National Statistics Share Tweet Linkedin Pin it More sharing options ... but should level off with time. Archived Scorecard Statistics 2017 Scorecard Statistics 2016 Scorecard Statistics (Archived) 2015 ...
Robust parametric bootstrap test with MOM estimator: An alternative to independent sample t-test
NASA Astrophysics Data System (ADS)
Harun, Nurul Hanis; Yusof, Zahayu Md
2014-12-01
Normality and homogeneity are two major assumptions that need to be fulfilled when using independent sample t-test. However, not all data encompassed with these assumptions. Consequently, the result produced by independent sample t-test becomes invalid. Therefore, the alternative is to use robust statistical procedure in handling the problems of nonnormality and variances heterogeneity. This study proposed to use Parametric Bootstrap test with popular robust estimators, MADn and Tn which empirically determines the amount of trimming. The Type I error rates produced by each procedure were examined and compared with classical parametric test and nonparametric test namely independent sample t-test and Mann Whitney test, respectively. 5000 simulated data sets are used in this study in order to generate the Type I error for each procedure. The findings of this study indicate that the Parametric Bootstrap test with MADn and Tn produces the best Type I error control compared to the independent sample t-test and the Mann Whitney test under nonnormal distribution, heterogeneous variances and unbalanced design. Then, the performance of each procedure was demonstrated using real data.
Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne
2012-01-01
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models. PMID:23275882
NASA Astrophysics Data System (ADS)
Doutriaux-Boucher, M.; Quaas, J.
2004-03-01
Realistic simulations of clouds are of uppermost importance for climate modelling using general circulation models. Satellite data are well suited to evaluate model parametrizations. In this study we use the Laboratoire de Météorologie Dynamique general circulation model (LMDZ). We evaluate the current LMDZ cloud phase parametrization, in which the repartition of condensed cloud water between liquid and ice is a function of the local temperature. Three parameters are used to derive a relation between liquid cloud water content and temperature, two of which are not physically based. We use the POLDER-1 satellite data to infer more realistic parameters by establishing statistical relationships between cloud top thermodynamical phase and cloud top temperature, consistently in both satellite data and model results. We then perform a multitude of short model integrations and derive a best estimate for the lowest local temperature where liquid water can exist in a cloud (Tice = -32°C in our parametrization). The other parameter which describes the shape of the transition between ice and liquid water is also estimated. A longer simulation has then been performed with the new parameters, resulting in an improvement in the representation of the shortwave cloud radiative forcing.
Analysis of survival in breast cancer patients by using different parametric models
NASA Astrophysics Data System (ADS)
Enera Amran, Syahila; Asrul Afendi Abdullah, M.; Kek, Sie Long; Afiqah Muhamad Jamil, Siti
2017-09-01
In biomedical applications or clinical trials, right censoring was often arising when studying the time to event data. In this case, some individuals are still alive at the end of the study or lost to follow up at a certain time. It is an important issue to handle the censoring data in order to prevent any bias information in the analysis. Therefore, this study was carried out to analyze the right censoring data with three different parametric models; exponential model, Weibull model and log-logistic models. Data of breast cancer patients from Hospital Sultan Ismail, Johor Bahru from 30 December 2008 until 15 February 2017 was used in this study to illustrate the right censoring data. Besides, the covariates included in this study are the time of breast cancer infection patients survive t, age of each patients X1 and treatment given to the patients X2 . In order to determine the best parametric models in analysing survival of breast cancer patients, the performance of each model was compare based on Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and log-likelihood value using statistical software R. When analysing the breast cancer data, all three distributions were shown consistency of data with the line graph of cumulative hazard function resembles a straight line going through the origin. As the result, log-logistic model was the best fitted parametric model compared with exponential and Weibull model since it has the smallest value in AIC and BIC, also the biggest value in log-likelihood.
Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne
2012-12-01
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.
A comparison of parametric and nonparametric methods for normalising cDNA microarray data.
Khondoker, Mizanur R; Glasbey, Chris A; Worton, Bruce J
2007-12-01
Normalisation is an essential first step in the analysis of most cDNA microarray data, to correct for effects arising from imperfections in the technology. Loess smoothing is commonly used to correct for trends in log-ratio data. However, parametric models, such as the additive plus multiplicative variance model, have been preferred for scale normalisation, though the variance structure of microarray data may be of a more complex nature than can be accommodated by a parametric model. We propose a new nonparametric approach that incorporates location and scale normalisation simultaneously using a Generalised Additive Model for Location, Scale and Shape (GAMLSS, Rigby and Stasinopoulos, 2005, Applied Statistics, 54, 507-554). We compare its performance in inferring differential expression with Huber et al.'s (2002, Bioinformatics, 18, 96-104) arsinh variance stabilising transformation (AVST) using real and simulated data. We show GAMLSS to be as powerful as AVST when the parametric model is correct, and more powerful when the model is wrong. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Impact of signal scattering and parametric uncertainties on receiver operating characteristics
NASA Astrophysics Data System (ADS)
Wilson, D. Keith; Breton, Daniel J.; Hart, Carl R.; Pettit, Chris L.
2017-05-01
The receiver operating characteristic (ROC curve), which is a plot of the probability of detection as a function of the probability of false alarm, plays a key role in the classical analysis of detector performance. However, meaningful characterization of the ROC curve is challenging when practically important complications such as variations in source emissions, environmental impacts on the signal propagation, uncertainties in the sensor response, and multiple sources of interference are considered. In this paper, a relatively simple but realistic model for scattered signals is employed to explore how parametric uncertainties impact the ROC curve. In particular, we show that parametric uncertainties in the mean signal and noise power substantially raise the tails of the distributions; since receiver operation with a very low probability of false alarm and a high probability of detection is normally desired, these tails lead to severely degraded performance. Because full a priori knowledge of such parametric uncertainties is rarely available in practice, analyses must typically be based on a finite sample of environmental states, which only partially characterize the range of parameter variations. We show how this effect can lead to misleading assessments of system performance. For the cases considered, approximately 64 or more statistically independent samples of the uncertain parameters are needed to accurately predict the probabilities of detection and false alarm. A connection is also described between selection of suitable distributions for the uncertain parameters, and Bayesian adaptive methods for inferring the parameters.
Applications of non-parametric statistics and analysis of variance on sample variances
NASA Technical Reports Server (NTRS)
Myers, R. H.
1981-01-01
Nonparametric methods that are available for NASA-type applications are discussed. An attempt will be made here to survey what can be used, to attempt recommendations as to when each would be applicable, and to compare the methods, when possible, with the usual normal-theory procedures that are avavilable for the Gaussion analog. It is important here to point out the hypotheses that are being tested, the assumptions that are being made, and limitations of the nonparametric procedures. The appropriateness of doing analysis of variance on sample variances are also discussed and studied. This procedure is followed in several NASA simulation projects. On the surface this would appear to be reasonably sound procedure. However, difficulties involved center around the normality problem and the basic homogeneous variance assumption that is mase in usual analysis of variance problems. These difficulties discussed and guidelines given for using the methods.
Evaluation of cerebral 31-P chemical shift images utilizing statistical parametric mapping
NASA Astrophysics Data System (ADS)
Riehemann, Stefan; Gaser, Christian; Volz, Hans-Peter; Sauer, Heinrich
1999-05-01
We present an evaluation technique of two dimensional (2D) nuclear magnetic resonance (NMR) chemical shift images (CSI) to analyze spatial differences of metabolite distributions and/or concentrations between groups of probands. Thus, chemical shift imaging is not only used as localization technique for NMR-spectroscopy, but the information of the complete spectroscopic image is used for the evaluation process. 31P CSI of the human brain were acquired with a Philips Gyroscan ACSII whole-body scanner at 1.5 T. CSI for different phosphorus metabolites were generated, all representing the same anatomical location. For each metabolite the CSI of two groups of subjects were compared with each other using the general linear model implemented in the widely distributed SPM96 software package. With this approach, even covariates or confounding variables like age or medication can be considered. As an example for the application of this technique, variations in the distribution of the 31P metabolite phosphocreatin between unmedicated schizophrenic patients and healthy controls were visualized. To our knowledge, this is the first approach to analyze spatial variations in metabolite concentrations between groups of subjects on the basis of chemical shift images. The presented technique opens a new perspective in the evaluation of 2D NMR spectroscopic data.
Statistical aspects of the 1980 solar flares. Part 3: Parametric comparison and final comments
NASA Technical Reports Server (NTRS)
Wilson, R. M.
1983-01-01
The 1349 study flares are considered addressing relationships between pairs of specific study paremeters; namely, H alpha rise time versus H alpha importance, X-ray class and H alpha decay time; H alpha decay time versus H alpha importance and X-ray class; and H alpha importance versus X-ray class. Mean H alpha rise time and decay time versus X-ray class and H alpha importance will also be discussed, and some final comments regarding the study flares are given.
Reduction of non-native accents through statistical parametric articulatory synthesis.
Aryal, Sandesh; Gutierrez-Osuna, Ricardo
2015-01-01
This paper presents an articulatory synthesis method to transform utterances from a second language (L2) learner to appear as if they had been produced by the same speaker but with a native (L1) accent. The approach consists of building a probabilistic articulatory synthesizer (a mapping from articulators to acoustics) for the L2 speaker, then driving the model with articulatory gestures from a reference L1 speaker. To account for differences in the vocal tract of the two speakers, a Procrustes transform is used to bring their articulatory spaces into registration. In a series of listening tests, accent conversions were rated as being more intelligible and less accented than L2 utterances while preserving the voice identity of the L2 speaker. No significant effect was found between the intelligibility of accent-converted utterances and the proportion of phones outside the L2 inventory. Because the latter is a strong predictor of pronunciation variability in L2 speech, these results suggest that articulatory resynthesis can decouple those aspects of an utterance that are due to the speaker's physiology from those that are due to their linguistic gestures.
2014-10-02
Mokhtar et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits...the identification of the changes to the distribution, which signifies when a change in the sys - tem’s conditions have occurred, i.e. the measured...line disruption. The system operates in a harsh environment where high temperatures and fuel impurities can lead to sys - tem degradation and functional
Multi-Channel and Multi-Dimensional Sensors Parametric Statistics Estimation
2009-06-01
simulating signals to use for testing algorithms. The TDOA and FDOA are coupled kinematic parameters, so one cannot independently simulate them without...4 APPENDIX A KINEMATIC AND CYCLOSTATIONARY PARAMETER ESTIMATION FOR CO-CHANNEL EMITTER LOCATION APPLICATIONS PhD...RELATIONSHIP BETWEEN FDOA AND TDOA . . . . . . . . . . . . . 145 B THE SIMULATED BPSK SIGNAL . . . . . . . . . . . . . . . . . . . . . . 148 C LIST
Parametric study of the swimming performance of a fish robot propelled by a flexible caudal fin.
Low, K H; Chong, C W
2010-12-01
In this paper, we aim to study the swimming performance of fish robots by using a statistical approach. A fish robot employing a carangiform swimming mode had been used as an experimental platform for the performance study. The experiments conducted aim to investigate the effect of various design parameters on the thrust capability of the fish robot with a flexible caudal fin. The controllable parameters associated with the fin include frequency, amplitude of oscillation, aspect ratio and the rigidity of the caudal fin. The significance of these parameters was determined in the first set of experiments by using a statistical approach. A more detailed parametric experimental study was then conducted with only those significant parameters. As a result, the parametric study could be completed with a reduced number of experiments and time spent. With the obtained experimental result, we were able to understand the relationship between various parameters and a possible adjustment of parameters to obtain a higher thrust. The proposed statistical method for experimentation provides an objective and thorough analysis of the effects of individual or combinations of parameters on the swimming performance. Such an efficient experimental design helps to optimize the process and determine factors that influence variability.
Optimal parametrization of electrodynamical battery model using model selection criteria
NASA Astrophysics Data System (ADS)
Suárez-García, Andrés; Alfonsín, Víctor; Urréjola, Santiago; Sánchez, Ángel
2015-07-01
This paper describes the mathematical parametrization of an electrodynamical battery model using different model selection criteria. A good modeling technique is needed by the battery management units in order to increase battery lifetime. The elements of battery models can be mathematically parametrized to enhance their implementation in simulation environments. In this work, the best mathematical parametrizations are selected using three model selection criteria: the coefficient of determination (R2), the Akaike Information Criterion (AIC) and the Bayes Information Criterion (BIC). The R2 criterion only takes into account the error of the mathematical parametrizations, whereas AIC and BIC consider complexity. A commercial 40 Ah lithium iron phosphate (LiFePO4) battery is modeled and then simulated for contrasting. The OpenModelica open-source modeling and simulation environment is used for doing the battery simulations. The mean percent error of the simulations is 0.0985% for the models parametrized with R2 , 0.2300% for the AIC ones, and 0.3756% for the BIC ones. As expected, the R2 selected the most precise, complex and slowest mathematical parametrizations. The AIC criterion chose parametrizations with similar accuracy, but simpler and faster than the R2 ones.
NASA Astrophysics Data System (ADS)
Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto; Marrocu, Marino
2017-04-01
Among different approaches to bias correct climate model (CM) results, distribution mapping has been identified as the most efficient one in reproducing the statistics of rainfall at regional scales, and at temporal resolutions suitable to run hydrologic models (e.g. daily). Yet, its implementation remains at a basic level, based on empirical distributions derived from control samples (referred to as non-parametric, or empirical distribution mapping), which makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of CM results, and may lead to significant biases, especially when focus is on extreme rainfall estimation. In an effort to address these shortcomings, we use a two component theoretical distribution model (i.e. a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates) to propose a parametric bias correction procedure suited for regional frequency analysis. The latter is implemented by proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data (KUD). To assess the performance of the suggested parametric approach relative to non-parametric distribution mapping, we use daily raingauge measurements from a dense network in the island of Sardinia (Italy), and climate model rainfall data from 4 CMs of the ENSEMBLES project, to apply both methods to different combinations of control and validation periods. The obtained results shed light on the competitive advantages of the parametric approach relative to the non-parametric one, with the former being more accurate and considerably less sensitive to the characteristics of the control period, independent of the climate model used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available
2011-01-01
Background When the mortality among a cancer patient group returns to the same level as in the general population, that is, the patients no longer experience excess mortality, the patients still alive are considered "statistically cured". Cure models can be used to estimate the cure proportion as well as the survival function of the "uncured". One limitation of parametric cure models is that the functional form of the survival of the "uncured" has to be specified. It can sometimes be hard to find a survival function flexible enough to fit the observed data, for example, when there is high excess hazard within a few months from diagnosis, which is common among older age groups. This has led to the exclusion of older age groups in population-based cancer studies using cure models. Methods Here we have extended the flexible parametric survival model to incorporate cure as a special case to estimate the cure proportion and the survival of the "uncured". Flexible parametric survival models use splines to model the underlying hazard function, and therefore no parametric distribution has to be specified. Results We have compared the fit from standard cure models to our flexible cure model, using data on colon cancer patients in Finland. This new method gives similar results to a standard cure model, when it is reliable, and better fit when the standard cure model gives biased estimates. Conclusions Cure models within the framework of flexible parametric models enables cure modelling when standard models give biased estimates. These flexible cure models enable inclusion of older age groups and can give stage-specific estimates, which is not always possible from parametric cure models. PMID:21696598
Predict! Teaching Statistics Using Informational Statistical Inference
ERIC Educational Resources Information Center
Makar, Katie
2013-01-01
Statistics is one of the most widely used topics for everyday life in the school mathematics curriculum. Unfortunately, the statistics taught in schools focuses on calculations and procedures before students have a chance to see it as a useful and powerful tool. Researchers have found that a dominant view of statistics is as an assortment of tools…
Statistics Poker: Reinforcing Basic Statistical Concepts
ERIC Educational Resources Information Center
Leech, Nancy L.
2008-01-01
Learning basic statistical concepts does not need to be tedious or dry; it can be fun and interesting through cooperative learning in the small-group activity of Statistics Poker. This article describes a teaching approach for reinforcing basic statistical concepts that can help students who have high anxiety and makes learning and reinforcing…
Parametric generation of quadrature squeezing of mirrors in cavity optomechanics
Liao, Jie-Qiao; Law, C. K.
2011-03-15
We propose a method to generate quadrature-squeezed states of a moving mirror in a Fabry-Perot cavity. This is achieved by exploiting the fact that when the cavity is driven by an external field with a large detuning, the moving mirror behaves as a parametric oscillator. We show that parametric resonance can be reached approximately by modulating the driving field amplitude at a frequency matching the frequency shift of the mirror. The parametric resonance leads to an efficient generation of squeezing, which is limited by the thermal noise of the environment.
Average power effects in parametric oscillators and amplifiers
NASA Technical Reports Server (NTRS)
Barnes, Norman P.; Williams-Byrd, Julie A.
1995-01-01
Average power effects relative to the operation of parametric oscillators and amplifiers have been calculated. Temperature gradients have been calculated for both radial and longitudinal heat extraction. In many instances, the thermal load on a parametric oscillator is higher than the thermal load on a parametric amplifier with the same pump power. Having one or both these wavelengths resonant increases the chances that a generated photon will be absorbed by the nonlinear crystal. Temperature profiles and thermal diffusion time constants have been calculated for Gaussian beams, given the heat-deposition rate. With radical heat extraction the temperature profile can be expressed in a power series or approximated by a Gaussian distribution function.
Parametric interaction of coronal loops with p modes
NASA Astrophysics Data System (ADS)
Stepanov, A. V.; Zaitsev, V. V.; Kisliakov, A. G.; Urpo, S.
2009-03-01
Parametric resonance between p modes and eigenoscillations of coronal loops is studied. Observations of solar radio bursts revealed this effect in simultaneous excitation of loop oscillations with periods corresponding to the pumping-up frequency (5 min), subharmonic (10 min), and to the first upper frequency of parametric resonance (3.3 min). An interpretation in terms of a coronal magnetic loop as an equivalent electric circuit is given. Parametric resonance can work as a channel for transfer of energy from photospheric motions to stellar coronae.
Variable selection in semi-parametric models
Zhang, Hongmei; Maity, Arnab; Arshad, Hasan; Holloway, John; Karmaus, Wilfried
2014-01-01
We propose Bayesian variable selection methods in semi-parametric models in the framework of partially linear Gaussian and problit regressions. Reproducing kernels are utilized to evaluate possibly non-linear joint effect of a set of variables. Indicator variables are introduced into the reproducing kernels for the inclusion or exclusion of a variable. Different scenarios based on posterior probabilities of including a variable are proposed to select important variables. Simulations are used to demonstrate and evaluate the methods. It was found that the proposed methods can efficiently select the correct variables regardless of the feature of the effects, linear or non-linear in an unknown form. The proposed methods are applied to two real data sets to identify cytosine phosphate guanine methylation sites associated with maternal smoking and cytosine phosphate guanine sites associated with cotinine levels with creatinine levels adjusted. The selected methylation sites have the potential to advance our understanding of the underlying mechanism for the impact of smoking exposure on health outcomes, and consequently benefit medical research in disease intervention. PMID:23990355
Strain-Gage Loads Calibration Parametric Study
NASA Technical Reports Server (NTRS)
Lokos, William A.; Stauf, Rick
2004-01-01
This paper documents a parametric study of various aircraft wing-load test features that affect the quality of the resultant derived shear, bending-moment, and torque strain-gage load equations. The effect of the following on derived strain-gage equation accuracy are compared: single-point loading compared with distributed loading, variation in applied test load magnitude, number of applied load cases, and wing-box-only compared with control-surface loading. The subject of this study is an extensive wing-load calibration test of the Active Aeroelastic Wing F/A-18 airplane. Selected subsets of the available test data were used to derive load equations using the linear regression method. Results show the benefit of distributed loading and the diminishing-return benefits of test load magnitudes and number of load cases. The use of independent check cases as a quality metric for the derived load equations is shown to overcome blind extrapolating beyond the load data used to derive the load equations.
Design criteria for ultrafast optical parametric amplifiers
NASA Astrophysics Data System (ADS)
Manzoni, C.; Cerullo, G.
2016-10-01
Optical parametric amplifiers (OPAs) exploit second-order nonlinearity to transfer energy from a fixed frequency pump pulse to a variable frequency signal pulse, and represent an easy way of tuning over a broad range the frequency of an otherwise fixed femtosecond laser system. OPAs can also act as broadband amplifiers, transferring energy from a narrowband pump to a broadband signal and thus considerably shortening the duration of the pump pulse. Due to these unique properties, OPAs are nowadays ubiquitous in ultrafast laser laboratories, and are employed by many users, such as solid state physicists, atomic/molecular physicists, chemists and biologists, who are not experts in ultrafast optics. This tutorial paper aims at providing the non-specialist reader with a self-consistent guide to the physical foundations of OPAs, deriving the main equations describing their performance and discussing how they can be used to understand their most important working parameters (frequency tunability, bandwidth, pulse energy/repetition rate scalability, control over the carrier-envelope phase of the generated pulses). Based on this analysis, we derive practical design criteria for OPAs, showing how their performance depends on the type of the nonlinear interaction (crystal type, phase-matching configuration, crystal length), on the characteristics of the pump pulse (frequency, duration, energy, repetition rate) and on the OPA architecture.
Optical parametric osicllators with improved beam quality
Smith, Arlee V.; Alford, William J.
2003-11-11
An optical parametric oscillator (OPO) having an optical pump, which generates a pump beam at a pump frequency greater than a desired signal frequency, a nonlinear optical medium oriented so that a signal wave at the desired signal frequency and a corresponding idler wave are produced when the pump beam (wave) propagates through the nonlinear optical medium, resulting in beam walk off of the signal and idler waves, and an optical cavity which directs the signal wave to repeatedly pass through the nonlinear optical medium, said optical cavity comprising an equivalently even number of non-planar mirrors that produce image rotation on each pass through the nonlinear optical medium. Utilizing beam walk off where the signal wave and said idler wave have nonparallel Poynting vectors in the nonlinear medium and image rotation, a correlation zone of distance equal to approximately .rho.L.sub.crystal is created which, through multiple passes through the nonlinear medium, improves the beam quality of the OPO output.
Visual to Parametric Interaction (V2PI)
Maiti, Dipayan; Endert, Alex; North, Chris
2013-01-01
Typical data visualizations result from linear pipelines that start by characterizing data using a model or algorithm to reduce the dimension and summarize structure, and end by displaying the data in a reduced dimensional form. Sensemaking may take place at the end of the pipeline when users have an opportunity to observe, digest, and internalize any information displayed. However, some visualizations mask meaningful data structures when model or algorithm constraints (e.g., parameter specifications) contradict information in the data. Yet, due to the linearity of the pipeline, users do not have a natural means to adjust the displays. In this paper, we present a framework for creating dynamic data displays that rely on both mechanistic data summaries and expert judgement. The key is that we develop both the theory and methods of a new human-data interaction to which we refer as “ Visual to Parametric Interaction” (V2PI). With V2PI, the pipeline becomes bi-directional in that users are embedded in the pipeline; users learn from visualizations and the visualizations adjust to expert judgement. We demonstrate the utility of V2PI and a bi-directional pipeline with two examples. PMID:23555552
Selected Parametric Effects on Materials Flammability Limits
NASA Technical Reports Server (NTRS)
Hirsch, David B.; Juarez, Alfredo; Peyton, Gary J.; Harper, Susana A.; Olson, Sandra L.
2011-01-01
NASA-STD-(I)-6001B Test 1 is currently used to evaluate the flammability of materials intended for use in habitable environments of U.S. spacecraft. The method is a pass/fail upward flame propagation test conducted in the worst case configuration, which is defined as a combination of a material s thickness, test pressure, oxygen concentration, and temperature that make the material most flammable. Although simple parametric effects may be intuitive (such as increasing oxygen concentrations resulting in increased flammability), combinations of multi-parameter effects could be more complex. In addition, there are a variety of material configurations used in spacecraft. Such configurations could include, for example, exposed free edges where fire propagation may be different when compared to configurations commonly employed in standard testing. Studies involving combined oxygen concentration, pressure, and temperature on flammability limits have been conducted and are summarized in this paper. Additional effects on flammability limits of a material s thickness, mode of ignition, burn-length criteria, and exposed edges are presented. The information obtained will allow proper selection of ground flammability test conditions, support further studies comparing flammability in 1-g with microgravity and reduced gravity environments, and contribute to persuasive scientific cases for rigorous space system fire risk assessments.
Parametric Study of Variable Emissivity Radiator Surfaces
NASA Technical Reports Server (NTRS)
Grob, Lisa M.; Swanson, Theodore D.
2000-01-01
The goal of spacecraft thermal design is to accommodate a high function satellite in a low weight and real estate package. The extreme environments that the satellite is exposed during its orbit are handled using passive and active control techniques. Heritage passive heat rejection designs are sized for the hot conditions and augmented for the cold end with heaters. The active heat rejection designs to date are heavy, expensive and/or complex. Incorporating an active radiator into the design that is lighter, cheaper and more simplistic will allow designers to meet the previously stated goal of thermal spacecraft design Varying the radiator's surface properties without changing the radiating area (as with VCHP), or changing the radiators' views (traditional louvers) is the objective of the variable emissivity (vary-e) radiator technologies. A parametric evaluation of the thermal performance of three such technologies is documented in this paper. Comparisons of the Micro-Electromechanical Systems (MEMS), Electrochromics, and Electrophoretics radiators to conventional radiators, both passive and active are quantified herein. With some noted limitations, the vary-e radiator surfaces provide significant advantages over traditional radiators and a promising alternative design technique for future spacecraft thermal systems.
Program Predicts Performance of Optical Parametric Oscillators
NASA Technical Reports Server (NTRS)
Cross, Patricia L.; Bowers, Mark
2006-01-01
A computer program predicts the performances of solid-state lasers that operate at wavelengths from ultraviolet through mid-infrared and that comprise various combinations of stable and unstable resonators, optical parametric oscillators (OPOs), and sum-frequency generators (SFGs), including second-harmonic generators (SHGs). The input to the program describes the signal, idler, and pump beams; the SFG and OPO crystals; and the laser geometry. The program calculates the electric fields of the idler, pump, and output beams at three locations (inside the laser resonator, just outside the input mirror, and just outside the output mirror) as functions of time for the duration of the pump beam. For each beam, the electric field is used to calculate the fluence at the output mirror, plus summary parameters that include the centroid location, the radius of curvature of the wavefront leaving through the output mirror, the location and size of the beam waist, and a quantity known, variously, as a propagation constant or beam-quality factor. The program provides a typical Windows interface for entering data and selecting files. The program can include as many as six plot windows, each containing four graphs.
Action Quantization, Energy Quantization, and Time Parametrization
NASA Astrophysics Data System (ADS)
Floyd, Edward R.
2017-03-01
The additional information within a Hamilton-Jacobi representation of quantum mechanics is extra, in general, to the Schrödinger representation. This additional information specifies the microstate of ψ that is incorporated into the quantum reduced action, W. Non-physical solutions of the quantum stationary Hamilton-Jacobi equation for energies that are not Hamiltonian eigenvalues are examined to establish Lipschitz continuity of the quantum reduced action and conjugate momentum. Milne quantization renders the eigenvalue J. Eigenvalues J and E mutually imply each other. Jacobi's theorem generates a microstate-dependent time parametrization t-τ =partial _E W even where energy, E, and action variable, J, are quantized eigenvalues. Substantiating examples are examined in a Hamilton-Jacobi representation including the linear harmonic oscillator numerically and the square well in closed form. Two byproducts are developed. First, the monotonic behavior of W is shown to ease numerical and analytic computations. Second, a Hamilton-Jacobi representation, quantum trajectories, is shown to develop the standard energy quantization formulas of wave mechanics.
Parametric Cost Analysis: A Design Function
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1989-01-01
Parametric cost analysis uses equations to map measurable system attributes into cost. The measures of the system attributes are called metrics. The equations are called cost estimating relationships (CER's), and are obtained by the analysis of cost and technical metric data of products analogous to those to be estimated. Examples of system metrics include mass, power, failure_rate, mean_time_to_repair, energy _consumed, payload_to_orbit, pointing_accuracy, manufacturing_complexity, number_of_fasteners, and percent_of_electronics_weight. The basic assumption is that a measurable relationship exists between system attributes and the cost of the system. If a function exists, the attributes are cost drivers. Candidates for metrics include system requirement metrics and engineering process metrics. Requirements are constraints on the engineering process. From optimization theory we know that any active constraint generates cost by not permitting full optimization of the objective. Thus, requirements are cost drivers. Engineering processes reflect a projection of the requirements onto the corporate culture, engineering technology, and system technology. Engineering processes are an indirect measure of the requirements and, hence, are cost drivers.
A Parametric Study of Spur Gear Dynamics
NASA Technical Reports Server (NTRS)
Lin, Hsiang Hsi; Liou, Chuen-Huei
1998-01-01
A parametric study of a spur gear system was performed through a numerical analysis approach. This study used the gear dynamic program DANST, a computer simulator, to determine the dynamic behavior of a spur gear system. The analytical results have taken the deflection of shafts and bearings into consideration for static analysis, and the influence of these deflections on gear dynamics was investigated. Damping in the gear system usually is an unknown quantity, but it has an important effect in resonance vibration. Typical values as reported in the literature were used in the present analysis. The dynamic response due to different damping factors was evaluated and compared. The effect of the contact ratio on spur gear dynamic load and dynamic stress was investigated through a parameter study. The contact ratio was varied over the range of 1.26 to 2.46 by adjusting the tooth addendum. Gears with contact ratio near 2.0 were found to have the most favorable dynamic performance.
Parametric probability distributions for anomalous change detection
Theiler, James P; Foy, Bernard R; Wohlberg, Brendt E; Scovel, James C
2010-01-01
The problem of anomalous change detection arises when two (or possibly more) images are taken of the same scene, but at different times. The aim is to discount the 'pervasive differences' that occur thoughout the imagery, due to the inevitably different conditions under which the images were taken (caused, for instance, by differences in illumination, atmospheric conditions, sensor calibration, or misregistration), and to focus instead on the 'anomalous changes' that actually take place in the scene. In general, anomalous change detection algorithms attempt to model these normal or pervasive differences, based on data taken directly from the imagery, and then identify as anomalous those pixels for which the model does not hold. For many algorithms, these models are expressed in terms of probability distributions, and there is a class of such algorithms that assume the distributions are Gaussian. By considering a broader class of distributions, however, a new class of anomalous change detection algorithms can be developed. We consider several parametric families of such distributions, derive the associated change detection algorithms, and compare the performance with standard algorithms that are based on Gaussian distributions. We find that it is often possible to significantly outperform these standard algorithms, even using relatively simple non-Gaussian models.
Parametric investigation of scalable tactile sensors
NASA Astrophysics Data System (ADS)
Saadatzi, Mohammad Nasser; Yang, Zhong; Baptist, Joshua R.; Sahasrabuddhe, Ritvij R.; Wijayasinghe, Indika B.; Popa, Dan O.
2017-05-01
In the near future, robots and humans will share the same environment and perform tasks cooperatively. For intuitive, safe, and reliable physical human-robot interaction (pHRI), sensorized robot skins for tactile measurements of contact are necessary. In a previous study, we presented skins consisting of strain gauge arrays encased in silicone encapsulants. Although these structures could measure normal forces applied directly onto the sensing elements, they also exhibited blind spots and response asymmetry to certain loading patterns. This study presents a parametric investigation of piezoresistive polymeric strain gauge that exhibits a symmetric omniaxial response thanks to its novel star-shaped structure. This strain gauge relies on the use of gold micro-patterned star-shaped structures with a thin layer of PEDOT:PSS which is a flexible polymer with piezoresistive properties. In this paper, the sensor is first modeled and comprehensively analyzed in the finite-element simulation environment COMSOL. Simulations include stress-strain loading for a variety of structure parameters such as gauge lengths, widths, and spacing, as well as multiple load locations relative to the gauge. Subsequently, sensors with optimized configurations obtained through simulations were fabricated using cleanroom photolithographic and spin-coating processes, and then experimentally tested. Results show a trend-wise agreement between experiments and simulations.
Parametric analysis of a magnetized cylindrical plasma
Ahedo, Eduardo
2009-11-15
The relevant macroscopic model, the spatial structure, and the parametric regimes of a low-pressure plasma confined by a cylinder and an axial magnetic field is discussed for the small-Debye length limit, making use of asymptotic techniques. The plasma response is fully characterized by three-dimensionless parameters, related to the electron gyroradius, and the electron and ion collision mean-free-paths. There are the unmagnetized regime, the main magnetized regime, and, for a low electron-collisionality plasma, an intermediate-magnetization regime. In the magnetized regimes, electron azimuthal inertia is shown to be a dominant phenomenon in part of the quasineutral plasma region and to set up before ion radial inertia. In the main magnetized regime, the plasma structure consists of a bulk diffusive region, a thin layer governed by electron inertia, a thinner sublayer controlled by ion inertia, and the non-neutral Debye sheath. The solution of the main inertial layer yields that the electron azimuthal energy near the wall is larger than the electron thermal energy, making electron resistivity effects non-negligible. The electron Boltzmann relation is satisfied only in the very vicinity of the Debye sheath edge. Ion collisionality effects are irrelevant in the magnetized regime. Simple scaling laws for plasma production and particle and energy fluxes to the wall are derived.
Parametric optimization of inverse trapezoid oleophobic surfaces.
Cavalli, Andrea; Bøggild, Peter; Okkels, Fridolin
2012-12-18
In this paper, we introduce a comprehensive and versatile approach to the parametric shape optimization of oleophobic surfaces. We evaluate the performance of inverse trapezoid microstructures in terms of three objective parameters: apparent contact angle, maximum sustainable hydrostatic pressure, and mechanical robustness (Im, M.; Im, H:; Lee, J.H.; Yoon, J.B.; Choi, Y.K. A robust superhydrophobic and superoleophobic surface with inverse-trapezoidal microstructures on a large transparent flexible substrate. Soft Matter 2010, 6, 1401-1404; Im, M.; Im, H:; Lee, J.H.; Yoon, J.B.; Choi, Y.K. Analytical Modeling and Thermodynamic Analysis of Robust Superhydrophobic Surfaces with Inverse-Trapezoidal Microstructures. Langmuir 2010, 26, 17389-17397). We find that each of these parameters, if considered alone, would give trivial optima, while their interplay provides a well-defined optimal shape and aspect ratio. The inclusion of mechanical robustness in combination with conventional performance characteristics favors solutions relevant for practical applications, as mechanical stability is a critical issue not often addressed in idealized models.
Parametric instabilities in picosecond time scales
Baldis, H.A.; Rozmus, W.; Labaune, C.; Mounaix, Ph.; Pesme, D.; Baton, S.; Tikhonchuk, V.T.
1993-03-01
The coupling of intense laser light with plasmas is a rich field of plasma physics, with many applications. Among these are inertial confinement fusion (ICF), x-ray lasers, particle acceleration, and x-ray sources. Parametric instabilities have been studied for many years because of their importance to ICF; with laser pulses with duration of approximately a nanosecond, and laser intensities in the range 10{sup 14}--10{sup 15}W/cm{sup 2} these instabilities are of crucial concern because of a number of detrimental effects. Although the laser pulse duration of interest for these studies are relatively long, it has been evident in the past years that to reach an understanding of these instabilities requires their characterization and analysis in picosecond time scales. At the laser intensities of interest, the growth rate for stimulated Brillouin scattering (SBS) is of the order of picoseconds, and of an order of magnitude shorter for stimulated Raman scattering (SRS). In this paper the authors discuss SBS and SRS in the context of their evolution in picosecond time scales. They describe the fundamental concepts associated with their growth and saturation, and recent work on the nonlinear treatment required for the modeling of these instabilities at high laser intensities.
Optical parametric oscillators for medical applications
NASA Astrophysics Data System (ADS)
Gloster, Lawrie A. W.; Golding, Paul S.; King, Terence A.
1996-04-01
In recent years optical parametric oscillators (OPOs) have undergone a renaissance largely due to the discovery of new nonlinear materials capable of wide continuous tuning ranges spanning from the UV to the near-infrared spectral regions. To date, however, OPOs have not been exploited in the medical field despite their advantages over the dye laser in terms of tuning range and solid state structure. We consider the development of an OPO based on barium borate (BBO) which can be tailored to suit applications in medicine. Converting the maximum number of pump photons to tunable signal and idler photons is of great importance to secure high-fluence radiation necessary for many treatments. With this in mind, we report on an all- solid-state system using BBO which has been optimized by computer modeling with the potential of delivering amplification factors of typically up to 20 over a continuous tuning range of 700 nm to 1000 nm. As an example of its biomedical application, we describe the selective excitation of biomolecules and chromophores for cell destruction using malachite green isothiocyanate labelled bacteria. The potential for development is reviewed towards other medical applications such as diagnostic sensing and phototherapy.
Parametric approach to linear induction accelerator design
Bresie, D.A.; Andrews, J.A.; Ingram, S.W. . Center for Electromechanics)
1991-01-01
Past work on the design of linear induction accelerators has centered on the development of computer codes to analyze accelerator designs, using the current filament method. While these filament models are a very valuable tool for evaluating the performance of an induction launcher design, they provide little insight into the selection of dimensions, materials, and operation points for accelerators with interesting performance. Described in this paper is a parametric approach to defining effective accelerator designs. This method uses a computer optimization routine to iteratively seek out effective designs. The optimization routine is forced to search within a parameter space restricted to interesting and realistic parameters such as size, weight, voltage, and temperature rises. A filament model is used as the filter for the optimizer. Several linear induction accelerators have been designed using this method. The accelerators designed all used a switched capacitor power supply. While the run time of this code on The University of Texas' CRAY XMP-24 computer is moderately long, the resulting designs have good predicted performance. With realistic power supplies and materials, accelerator efficiencies in the 20 to 40% range were easily obtained. This paper describes the effect of armature diameter, length-to-diameter ratio, and weight, as well as other parameters, on the optimum accelerator design.
Visual to Parametric Interaction (V2PI).
Leman, Scotland C; House, Leanna; Maiti, Dipayan; Endert, Alex; North, Chris
2013-01-01
Typical data visualizations result from linear pipelines that start by characterizing data using a model or algorithm to reduce the dimension and summarize structure, and end by displaying the data in a reduced dimensional form. Sensemaking may take place at the end of the pipeline when users have an opportunity to observe, digest, and internalize any information displayed. However, some visualizations mask meaningful data structures when model or algorithm constraints (e.g., parameter specifications) contradict information in the data. Yet, due to the linearity of the pipeline, users do not have a natural means to adjust the displays. In this paper, we present a framework for creating dynamic data displays that rely on both mechanistic data summaries and expert judgement. The key is that we develop both the theory and methods of a new human-data interaction to which we refer as " Visual to Parametric Interaction" (V2PI). With V2PI, the pipeline becomes bi-directional in that users are embedded in the pipeline; users learn from visualizations and the visualizations adjust to expert judgement. We demonstrate the utility of V2PI and a bi-directional pipeline with two examples.
Parametric Testing of Launch Vehicle FDDR Models
NASA Technical Reports Server (NTRS)
Schumann, Johann; Bajwa, Anupa; Berg, Peter; Thirumalainambi, Rajkumar
2011-01-01
For the safe operation of a complex system like a (manned) launch vehicle, real-time information about the state of the system and potential faults is extremely important. The on-board FDDR (Failure Detection, Diagnostics, and Response) system is a software system to detect and identify failures, provide real-time diagnostics, and to initiate fault recovery and mitigation. The ERIS (Evaluation of Rocket Integrated Subsystems) failure simulation is a unified Matlab/Simulink model of the Ares I Launch Vehicle with modular, hierarchical subsystems and components. With this model, the nominal flight performance characteristics can be studied. Additionally, failures can be injected to see their effects on vehicle state and on vehicle behavior. A comprehensive test and analysis of such a complicated model is virtually impossible. In this paper, we will describe, how parametric testing (PT) can be used to support testing and analysis of the ERIS failure simulation. PT uses a combination of Monte Carlo techniques with n-factor combinatorial exploration to generate a small, yet comprehensive set of parameters for the test runs. For the analysis of the high-dimensional simulation data, we are using multivariate clustering to automatically find structure in this high-dimensional data space. Our tools can generate detailed HTML reports that facilitate the analysis.
Parametric Studies of Flow Separation using Air Injection
NASA Technical Reports Server (NTRS)
Zhang, Wei
2004-01-01
Boundary Layer separation causes the airfoil to stall and therefore imposes dramatic performance degradation on the airfoil. In recent years, flow separation control has been one of the active research areas in the field of aerodynamics due to its promising performance improvements on the lifting device. These active flow separation control techniques include steady and unsteady air injection as well as suction on the airfoil surface etc. This paper will be focusing on the steady and unsteady air injection on the airfoil. Although wind tunnel experiments revealed that the performance improvements on the airfoil using injection techniques, the details of how the key variables such as air injection slot geometry and air injection angle etc impact the effectiveness of flow separation control via air injection has not been studied. A parametric study of both steady and unsteady air injection active flow control will be the main objective for this summer. For steady injection, the key variables include the slot geometry, orientation, spacing, air injection velocity as well as the injection angle. For unsteady injection, the injection frequency will also be investigated. Key metrics such as lift coefficient, drag coefficient, total pressure loss and total injection mass will be used to measure the effectiveness of the control technique. A design of experiments using the Box-Behnken Design is set up in order to determine how each of the variables affects each of the key metrics. Design of experiment is used so that the number of experimental runs will be at minimum and still be able to predict which variables are the key contributors to the responses. The experiments will then be conducted in the 1ft by 1ft wind tunnel according to the design of experiment settings. The data obtained from the experiments will be imported into JMP, statistical software, to generate sets of response surface equations which represent the statistical empirical model for each of the metrics as
Parametric Studies of Flow Separation using Air Injection
NASA Technical Reports Server (NTRS)
Zhang, Wei
2004-01-01
Boundary Layer separation causes the airfoil to stall and therefore imposes dramatic performance degradation on the airfoil. In recent years, flow separation control has been one of the active research areas in the field of aerodynamics due to its promising performance improvements on the lifting device. These active flow separation control techniques include steady and unsteady air injection as well as suction on the airfoil surface etc. This paper will be focusing on the steady and unsteady air injection on the airfoil. Although wind tunnel experiments revealed that the performance improvements on the airfoil using injection techniques, the details of how the key variables such as air injection slot geometry and air injection angle etc impact the effectiveness of flow separation control via air injection has not been studied. A parametric study of both steady and unsteady air injection active flow control will be the main objective for this summer. For steady injection, the key variables include the slot geometry, orientation, spacing, air injection velocity as well as the injection angle. For unsteady injection, the injection frequency will also be investigated. Key metrics such as lift coefficient, drag coefficient, total pressure loss and total injection mass will be used to measure the effectiveness of the control technique. A design of experiments using the Box-Behnken Design is set up in order to determine how each of the variables affects each of the key metrics. Design of experiment is used so that the number of experimental runs will be at minimum and still be able to predict which variables are the key contributors to the responses. The experiments will then be conducted in the 1ft by 1ft wind tunnel according to the design of experiment settings. The data obtained from the experiments will be imported into JMP, statistical software, to generate sets of response surface equations which represent the statistical empirical model for each of the metrics as
Kalicka, Renata; Pietrenko-Dabrowska, Anna
2007-03-01
In the paper MRI measurements are used for assessment of brain tissue perfusion and other features and functions of the brain (cerebral blood flow - CBF, cerebral blood volume - CBV, mean transit time - MTT). Perfusion is an important indicator of tissue viability and functioning as in pathological tissue blood flow, vascular and tissue structure are altered with respect to normal tissue. MRI enables diagnosing diseases at an early stage of their course. The parametric and non-parametric approaches to the identification of MRI models are presented and compared. The non-parametric modeling adopts gamma variate functions. The parametric three-compartmental catenary model, based on the general kinetic model, is also proposed. The parameters of the models are estimated on the basis of experimental data. The goodness of fit of the gamma variate and the three-compartmental models to the data and the accuracy of the parameter estimates are compared. Kalman filtering, smoothing the measurements, was adopted to improve the estimate accuracy of the parametric model. Parametric modeling gives a better fit and better parameter estimates than non-parametric and allows an insight into the functioning of the system. To improve the accuracy optimal experiment design related to the input signal was performed.
NASA Astrophysics Data System (ADS)
Verrelst, Jochem; Rivera, Juan Pablo; Veroustraete, Frank; Muñoz-Marí, Jordi; Clevers, Jan G. P. W.; Camps-Valls, Gustau; Moreno, José
2015-10-01
Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC), collected at the agricultural site of Barrax (Spain), was used to evaluate different retrieval methods on their ability to estimate leaf area index (LAI). With regard to parametric methods, all possible band combinations for several two-band and three-band index formulations and a linear regression fitting function have been evaluated. From a set of over ten thousand indices evaluated, the best performing one was an optimized three-band combination according to (ρ560 -ρ1610 -ρ2190) / (ρ560 +ρ1610 +ρ2190) with a 10-fold cross-validation RCV2 of 0.82 (RMSECV : 0.62). This family of methods excel for their fast processing speed, e.g., 0.05 s to calibrate and validate the regression function, and 3.8 s to map a simulated S2 image. With regard to non-parametric methods, 11 machine learning regression algorithms (MLRAs) have been evaluated. This methodological family has the advantage of making use of the full optical spectrum as well as flexible, nonlinear fitting. Particularly kernel-based MLRAs lead to excellent results, with variational heteroscedastic (VH) Gaussian Processes regression (GPR) as the best performing method, with a RCV2 of 0.90 (RMSECV : 0.44). Additionally, the model is trained and validated relatively fast (1.70 s) and the processed image (taking 73.88 s) includes associated uncertainty estimates. More challenging is the inversion of a PROSAIL based radiative transfer model (RTM). After the generation of a look-up table (LUT), a multitude of cost functions and regularization options were evaluated. The best performing cost function is Pearson's χ -square. It led to a R2 of 0.74 (RMSE: 0.80) against the validation dataset. While its validation went fast
Statistical detection of systematic election irregularities.
Klimek, Peter; Yegorov, Yuri; Hanel, Rudolf; Thurner, Stefan
2012-10-09
Democratic societies are built around the principle of free and fair elections, and that each citizen's vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons.
Statistical detection of systematic election irregularities
Klimek, Peter; Yegorov, Yuri; Hanel, Rudolf; Thurner, Stefan
2012-01-01
Democratic societies are built around the principle of free and fair elections, and that each citizen’s vote should count equally. National elections can be regarded as large-scale social experiments, where people are grouped into usually large numbers of electoral districts and vote according to their preferences. The large number of samples implies statistical consequences for the polling results, which can be used to identify election irregularities. Using a suitable data representation, we find that vote distributions of elections with alleged fraud show a kurtosis substantially exceeding the kurtosis of normal elections, depending on the level of data aggregation. As an example, we show that reported irregularities in recent Russian elections are, indeed, well-explained by systematic ballot stuffing. We develop a parametric model quantifying the extent to which fraudulent mechanisms are present. We formulate a parametric test detecting these statistical properties in election results. Remarkably, this technique produces robust outcomes with respect to the resolution of the data and therefore, allows for cross-country comparisons. PMID:23010929
NASA Astrophysics Data System (ADS)
Reed, P. M.; Urban, R. L.; Wagener, T.; van Werkhoven, K. L.
2009-12-01
This study uses interactive visualization to investigate the common assumption that parametric screening using sensitivity analysis simplifies hydrologic calibration. Put simply, do we make calibration easier by eliminating model parameters from the optimization problem? Traditional approaches for parametric screening focus on model evaluation metrics that seek to minimize statistical error. We demonstrate in this study that additional hydrology relevant metrics (e.g., water balance) are essential to properly screening parameters and producing search problems that do not degenerate into random walks (a severe case of equifinality). This work highlights that we should move beyond a focus on optimality in a traditional error sense and instead focus on enhancing our evaluative metrics and formulations to include hydrology relevant information. Building on the prior work by van Werkhoven et al. 2009, this study utilizes parameter screening results based on Sobol sensitivity analysis to reduce the size of hydrologic calibration problems for the Sacramento Soil Moisture Accounting model (SAC SMA). Our study was conducted across four hydroclimatically diverse watersheds, and we distinguish various sets of parametric screenings, including a full parameter search, as well as parameter screenings based on 5%, 10%, 20%, and 30% Sobol sensitivity levels. For each Sobol sensitivity level there are two subcases: (1) parameters are screened based on statistical metrics alone, and (2) parameters are screened based on statistical and hydrological metrics. The reduced parameter sets were searched using a multiobjective evolutionary algorithm to determine the tradeoff surfaces of optimal parameter settings. Our results contribute detailed interactive visualizations of the 4-objective tradeoff surfaces for all of the parametric screening cases evaluated. For almost all of problem formulations that result from parametric screening, the combined use of statistical and hydrological
Direct Estimation of Kinetic Parametric Images for Dynamic PET
Wang, Guobao; Qi, Jinyi
2013-01-01
Dynamic positron emission tomography (PET) can monitor spatiotemporal distribution of radiotracer in vivo. The spatiotemporal information can be used to estimate parametric images of radiotracer kinetics that are of physiological and biochemical interests. Direct estimation of parametric images from raw projection data allows accurate noise modeling and has been shown to offer better image quality than conventional indirect methods, which reconstruct a sequence of PET images first and then perform tracer kinetic modeling pixel-by-pixel. Direct reconstruction of parametric images has gained increasing interests with the advances in computing hardware. Many direct reconstruction algorithms have been developed for different kinetic models. In this paper we review the recent progress in the development of direct reconstruction algorithms for parametric image estimation. Algorithms for linear and nonlinear kinetic models are described and their properties are discussed. PMID:24396500
Nondegenerate Parametric Resonance in a Tunable Superconducting Cavity
NASA Astrophysics Data System (ADS)
Wustmann, Waltraut; Shumeiko, Vitaly
2017-08-01
We develop a theory for nondegenerate parametric resonance in a tunable superconducting cavity. We focus on nonlinear effects that are caused by nonlinear Josephson elements connected to the cavity. We analyze parametric amplification in a strong nonlinear regime at the parametric-instability threshold, and we calculate maximum gain values. Above the threshold, in the parametric-oscillator regime, the cavity linear response diverges at the oscillator frequency at all pump strengths. We show that this divergence is related to the continuous degeneracy of the free oscillator state with respect to the phase. Applying on-resonance input lifts the degeneracy and removes the divergence. We also investigate quantum noise squeezing. It is shown that in the strong amplification regime, the noise undergoes four-mode squeezing, and that, in this regime, the output signal-to-noise ratio can significantly exceed the input value. We also analyze the intermode frequency conversion and identify the parameters at which full conversion is achieved.
Forecasting Marine Corps Enlisted Attrition Through Parametric Modeling
2009-03-01
OF PAGES 85 14. SUBJECT TERMS Forecasting, Attrition, Marine Corps NEAS losses, Gompertz Model, Survival Analysis 16. PRICE CODE 17. SECURITY...18 1. Parametric Proportional Hazards Models ......................................18 2. Gompertz Models...19 a. Gompertz Hazard Function....................................................19 b. Gompertz Cumulative
Evaluating forest management policies by parametric linear programing
Daniel I. Navon; Richard J. McConnen
1967-01-01
An analytical and simulation technique, parametric linear programing explores alternative conditions and devises an optimal management plan for each condition. Its application in solving policy-decision problems in the management of forest lands is illustrated in an example.
Applications of quantum entropy to statistics
Silver, R.N.; Martz, H.F.
1994-07-01
This paper develops two generalizations of the maximum entropy (ME) principle. First, Shannon classical entropy is replaced by von Neumann quantum entropy to yield a broader class of information divergences (or penalty functions) for statistics applications. Negative relative quantum entropy enforces convexity, positivity, non-local extensivity and prior correlations such as smoothness. This enables the extension of ME methods from their traditional domain of ill-posed in-verse problems to new applications such as non-parametric density estimation. Second, given a choice of information divergence, a combination of ME and Bayes rule is used to assign both prior and posterior probabilities. Hyperparameters are interpreted as Lagrange multipliers enforcing constraints. Conservation principles are proposed to act statistical regularization and other hyperparameters, such as conservation of information and smoothness. ME provides an alternative to heirarchical Bayes methods.
Optimal Parametric Discrete Event Control: Problem and Solution
Griffin, Christopher H
2008-01-01
We present a novel optimization problem for discrete event control, similar in spirit to the optimal parametric control problem common in statistical process control. In our problem, we assume a known finite state machine plant model $G$ defined over an event alphabet $\\Sigma$ so that the plant model language $L = \\LanM(G)$ is prefix closed. We further assume the existence of a \\textit{base control structure} $M_K$, which may be either a finite state machine or a deterministic pushdown machine. If $K = \\LanM(M_K)$, we assume $K$ is prefix closed and that $K \\subseteq L$. We associate each controllable transition of $M_K$ with a binary variable $X_1,\\dots,X_n$ indicating whether the transition is enabled or not. This leads to a function $M_K(X_1,\\dots,X_n)$, that returns a new control specification depending upon the values of $X_1,\\dots,X_n$. We exhibit a branch-and-bound algorithm to solve the optimization problem $\\min_{X_1,\\dots,X_n}\\max_{w \\in K} C(w)$ such that $M_K(X_1,\\dots,X_n) \\models \\Pi$ and $\\LanM(M_K(X_1,\\dots,X_n)) \\in \\Con(L)$. Here $\\Pi$ is a set of logical assertions on the structure of $M_K(X_1,\\dots,X_n)$, and $M_K(X_1,\\dots,X_n) \\models \\Pi$ indicates that $M_K(X_1,\\dots,X_n)$ satisfies the logical assertions; and, $\\Con(L)$ is the set of controllable sublanguages of $L$.
Design and evaluation of a parametric model for cardiac sounds.
Ibarra-Hernández, Roilhi F; Alonso-Arévalo, Miguel A; Cruz-Gutiérrez, Alejandro; Licona-Chávez, Ana L; Villarreal-Reyes, Salvador
2017-08-09
Heart sound analysis plays an important role in the auscultative diagnosis process to detect the presence of cardiovascular diseases. In this paper we propose a novel parametric heart sound model that accurately represents normal and pathological cardiac audio signals, also known as phonocardiograms (PCG). The proposed model considers that the PCG signal is formed by the sum of two parts: one of them is deterministic and the other one is stochastic. The first part contains most of the acoustic energy. This part is modeled by the Matching Pursuit (MP) algorithm, which performs an analysis-synthesis procedure to represent the PCG signal as a linear combination of elementary waveforms. The second part, also called residual, is obtained after subtracting the deterministic signal from the original heart sound recording and can be accurately represented as an autoregressive process using the Linear Predictive Coding (LPC) technique. We evaluate the proposed heart sound model by performing subjective and objective tests using signals corresponding to different pathological cardiac sounds. The results of the objective evaluation show an average Percentage of Root-Mean-Square Difference of approximately 5% between the original heart sound and the reconstructed signal. For the subjective test we conducted a formal methodology for perceptual evaluation of audio quality with the assistance of medical experts. Statistical results of the subjective evaluation show that our model provides a highly accurate approximation of real heart sound signals. We are not aware of any previous heart sound model rigorously evaluated as our proposal. Copyright © 2017 Elsevier Ltd. All rights reserved.
Higher Order Crossings from a Parametric Family of Linear Filters
1989-09-01
HIGHER ORDER CROSSINGS FROM A PARAMETRIC FAMILY OF LINEAR FILTERS DTIC DTC Benjamin Kedem and Ta-hsin Li E! U 4C99 Department of MathematicsS4 9...NUMBER 4. TITLE (and Subtitle) 5. TYPE OF REPORT & PERIOD COVERED Higher order crossings from a parametric family Technical Report of linear filters...corresponding family of zero-crossing counts. The resulting family of counts is referred to as higher order crossings or HOC. Thus, HOC are zero-crossing
Finding Rational Parametric Curves of Relative Degree One or Two
ERIC Educational Resources Information Center
Boyles, Dave
2010-01-01
A plane algebraic curve, the complete set of solutions to a polynomial equation: f(x, y) = 0, can in many cases be drawn using parametric equations: x = x(t), y = y(t). Using algebra, attempting to parametrize by means of rational functions of t, one discovers quickly that it is not the degree of f but the "relative degree," that describes how…
Finding Rational Parametric Curves of Relative Degree One or Two
ERIC Educational Resources Information Center
Boyles, Dave
2010-01-01
A plane algebraic curve, the complete set of solutions to a polynomial equation: f(x, y) = 0, can in many cases be drawn using parametric equations: x = x(t), y = y(t). Using algebra, attempting to parametrize by means of rational functions of t, one discovers quickly that it is not the degree of f but the "relative degree," that describes how…
The Performance of a Parametric Receiver in an Inhomogeneous Medium.
1980-08-18
subject considered in this thesis is the performance of a parametric acoustic receiving array in an inhomogeneous medium. Develop- ment of this subject... ment presented. Of necessity, topics have been treated briefly. Some 42 topics, such as the use of arrays of parametric receivers, the phase mod- 41...that the agree- ment of the Kolmogorov theory with their experimental results was a conse- quence of the ’freezing’ of the thermal patches after their
Two-parametric PT-symmetric quartic family
NASA Astrophysics Data System (ADS)
Eremenko, Alexandre; Gabrielov, Andrei
2012-05-01
We describe a parametrization of the real spectral locus of the two-parametric family of PT-symmetric quartic oscillators. For this family, we find a parameter region where all eigenvalues are real, extending the results of Dorey et al (2007 J. Phys. A: Math Theor. 40 R205-83) and Shin (2005 J. Phys. A: Math. Gen. 38 6147-66 2002 Commun. Math. Phys. 229 543-64).
CFD parametric study of consortium impeller
NASA Astrophysics Data System (ADS)
Cheng, Gary C.; Chen, Y. S.; Garcia, Roberto; Williams, Robert W.
1993-07-01
Current design of high performance turbopumps for rocket engines requires effective and robust analytical tools to provide design impact in a productive manner. The main goal of this study is to develop a robust and effective computational fluid dynamics (CFD) pump model for general turbopump design and analysis applications. A Finite Difference Navier-Stokes flow solver, FDNS, which includes the extended k-epsilon turbulence model and appropriate moving interface boundary conditions, was developed to analyze turbulent flows in turbomachinery devices. A second-order central difference scheme plus adaptive dissipation terms was employed in the FDNS code, along with a predictor plus multi-corrector pressure-based solution procedure. The multi-zone, multi-block capability allows the FDNS code to efficiently solve flow fields with complicated geometry. The FDNS code has been benchmarked by analyzing the pump consortium inducer, and it provided satisfactory results. In the present study, a CFD parametric study of the pump consortium impeller was conducted using the FDNS code. The pump consortium impeller, with partial blades, is a new design concept of the advanced rocket engines. The parametric study was to analyze the baseline design of the consortium impeller and its modification which utilizes TANDEM blades. In the present study, the TANDEM blade configuration of the consortium impeller considers cut full blades for about one quarter chord length from the leading edge and clocks the leading edge portion with an angle of 7.5 or 22.5 degrees. The purpose of the present study is to investigate the effect and trend of the TANDEM blade modification and provide the result as a design guideline. A 3-D flow analysis, with a 103 x 23 x 30 mesh grid system and with the inlet flow conditions measured by Rocketdyne, was performed for the baseline consortium impeller. The numerical result shows that the mass flow rate splits through various blade passages are relatively uniform