Learning place cells, grid cells and invariances with excitatory and inhibitory plasticity

PubMed Central

2018-01-01

Neurons in the hippocampus and adjacent brain areas show a large diversity in their tuning to location and head direction, and the underlying circuit mechanisms are not yet resolved. In particular, it is unclear why certain cell types are selective to one spatial variable, but invariant to another. For example, place cells are typically invariant to head direction. We propose that all observed spatial tuning patterns – in both their selectivity and their invariance – arise from the same mechanism: Excitatory and inhibitory synaptic plasticity driven by the spatial tuning statistics of synaptic inputs. Using simulations and a mathematical analysis, we show that combined excitatory and inhibitory plasticity can lead to localized, grid-like or invariant activity. Combinations of different input statistics along different spatial dimensions reproduce all major spatial tuning patterns observed in rodents. Our proposed model is robust to changes in parameters, develops patterns on behavioral timescales and makes distinctive experimental predictions. PMID:29465399

Efficient and robust pupil size and blink estimation from near-field video sequences for human-machine interaction.

PubMed

Chen, Siyuan; Epps, Julien

2014-12-01

Monitoring pupil and blink dynamics has applications in cognitive load measurement during human-machine interaction. However, accurate, efficient, and robust pupil size and blink estimation pose significant challenges to the efficacy of real-time applications due to the variability of eye images, hence to date, require manual intervention for fine tuning of parameters. In this paper, a novel self-tuning threshold method, which is applicable to any infrared-illuminated eye images without a tuning parameter, is proposed for segmenting the pupil from the background images recorded by a low cost webcam placed near the eye. A convex hull and a dual-ellipse fitting method are also proposed to select pupil boundary points and to detect the eyelid occlusion state. Experimental results on a realistic video dataset show that the measurement accuracy using the proposed methods is higher than that of widely used manually tuned parameter methods or fixed parameter methods. Importantly, it demonstrates convenience and robustness for an accurate and fast estimate of eye activity in the presence of variations due to different users, task types, load, and environments. Cognitive load measurement in human-machine interaction can benefit from this computationally efficient implementation without requiring a threshold calibration beforehand. Thus, one can envisage a mini IR camera embedded in a lightweight glasses frame, like Google Glass, for convenient applications of real-time adaptive aiding and task management in the future.

Parameter selection in limited data cone-beam CT reconstruction using edge-preserving total variation algorithms

NASA Astrophysics Data System (ADS)

Lohvithee, Manasavee; Biguri, Ander; Soleimani, Manuchehr

2017-12-01

There are a number of powerful total variation (TV) regularization methods that have great promise in limited data cone-beam CT reconstruction with an enhancement of image quality. These promising TV methods require careful selection of the image reconstruction parameters, for which there are no well-established criteria. This paper presents a comprehensive evaluation of parameter selection in a number of major TV-based reconstruction algorithms. An appropriate way of selecting the values for each individual parameter has been suggested. Finally, a new adaptive-weighted projection-controlled steepest descent (AwPCSD) algorithm is presented, which implements the edge-preserving function for CBCT reconstruction with limited data. The proposed algorithm shows significant robustness compared to three other existing algorithms: ASD-POCS, AwASD-POCS and PCSD. The proposed AwPCSD algorithm is able to preserve the edges of the reconstructed images better with fewer sensitive parameters to tune.

Partially natural two Higgs doublet models

DOE PAGES

Draper, Patrick; Haber, Howard E.; Ruderman, Joshua T.

2016-06-21

It is possible that the electroweak scale is low due to the fine-tuning of microscopic parameters, which can result from selection effects. The experimental discovery of new light fundamental scalars other than the Standard Model Higgs boson would seem to disfavor this possibility, since generically such states imply parametrically worse fine-tuning with no compelling connection to selection effects. We discuss counterexamples where the Higgs boson is light because of fine-tuning, and a second scalar doublet is light because a discrete symmetry relates its mass to the mass of the Standard Model Higgs boson. Our examples require new vectorlike fermions atmore » the electroweak scale, and the models possess a rich electroweak vacuum structure. Furthermore, the mechanism that we discuss does not protect a small CP-odd Higgs mass in split or high-scale supersymmetry-breaking scenarios of the MSSM due to an incompatibility between the discrete symmetries and holomorphy.« less

A self-tuning automatic voltage regulator designed for an industrial environment

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

Flynn, D.; Hogg, B.W.; Swidenbank, E.

Examination of the performance of fixed parameter controllers has resulted in the development of self-tuning strategies for excitation control of turbogenerator systems. In conjunction with the advanced control algorithms, sophisticated measurement techniques have previously been adopted on micromachine systems to provide generator terminal quantities. In power stations, however, a minimalist hardware arrangement would be selected leading to relatively simple measurement techniques. The performance of a range of self-tuning schemes is investigated on an industrial test-bed, employing a typical industrial hardware measurement system. Individual controllers are implemented on a standard digital automatic voltage regulator, as installed in power stations. This employsmore » a VME platform, and the self-tuning algorithms are introduced by linking to a transputer network. The AVR includes all normal features, such as field forcing, VAR limiting and overflux protection. Self-tuning controller performance is compared with that of a fixed gain digital AVR.« less

Cross-validation pitfalls when selecting and assessing regression and classification models.

PubMed

Krstajic, Damjan; Buturovic, Ljubomir J; Leahy, David E; Thomas, Simon

2014-03-29

We address the problem of selecting and assessing classification and regression models using cross-validation. Current state-of-the-art methods can yield models with high variance, rendering them unsuitable for a number of practical applications including QSAR. In this paper we describe and evaluate best practices which improve reliability and increase confidence in selected models. A key operational component of the proposed methods is cloud computing which enables routine use of previously infeasible approaches. We describe in detail an algorithm for repeated grid-search V-fold cross-validation for parameter tuning in classification and regression, and we define a repeated nested cross-validation algorithm for model assessment. As regards variable selection and parameter tuning we define two algorithms (repeated grid-search cross-validation and double cross-validation), and provide arguments for using the repeated grid-search in the general case. We show results of our algorithms on seven QSAR datasets. The variation of the prediction performance, which is the result of choosing different splits of the dataset in V-fold cross-validation, needs to be taken into account when selecting and assessing classification and regression models. We demonstrate the importance of repeating cross-validation when selecting an optimal model, as well as the importance of repeating nested cross-validation when assessing a prediction error.

Tunable graphene-based mid-infrared plasmonic multispectral and narrow band-stop filter

NASA Astrophysics Data System (ADS)

Wang, Xianjun; Meng, Hongyun; Liu, Shuai; Deng, Shuying; Jiao, Tao; Wei, Zhongchao; Wang, Faqiang; Tan, Chunhua; Huang, Xuguang

2018-04-01

In this paper, we numerically investigate the band-stop properties of single- or few-layers doped graphene ribbon arrays operating in the mid-infrared region by finite-difference time-domain method (FDTD). A perfect band-stop filter with extinction ratio (ER) ∼17 dB, 3 dB bandwidth ∼200 nm and the resonance notch located at 6.64 μm can be achieved. And desired working regions can be obtained by tuning the Fermi level (E f ) of the graphene ribbons and the geometrical parameters of the structure. Besides, by tuning the Fermi level of odd or even graphene ribbons with terminal gate voltage, we can achieve a dual-circuit switch with four states combinations of on-to-off. Furthermore, the multiple filter notches can be achieved by stacking few-layers structure, and the filter dips can be dynamically tuned to achieve the tunability and selective characteristics by tuning the Fermi-level of the graphene ribbons in the system. We believe that our proposal has the potential applications in selective filters and active plasmonic switching in the mid-infrared region.

Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data.

PubMed

Becker, Natalia; Toedt, Grischa; Lichter, Peter; Benner, Axel

2011-05-09

Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net.We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone.Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution. Feature selection methods with combined penalties (Elastic Net and Elastic SCAD SVMs) are more robust to a change of the model complexity than methods using single penalties. Our simulation study showed that Elastic SCAD SVM outperformed LASSO (L1) and SCAD SVMs. Moreover, Elastic SCAD SVM provided sparser classifiers in terms of median number of features selected than Elastic Net SVM and often better predicted than Elastic Net in terms of misclassification error.Finally, we applied the penalization methods described above on four publicly available breast cancer data sets. Elastic SCAD SVM was the only method providing robust classifiers in sparse and non-sparse situations. The proposed Elastic SCAD SVM algorithm provides the advantages of the SCAD penalty and at the same time avoids sparsity limitations for non-sparse data. We were first to demonstrate that the integration of the interval search algorithm and penalized SVM classification techniques provides fast solutions on the optimization of tuning parameters.The penalized SVM classification algorithms as well as fixed grid and interval search for finding appropriate tuning parameters were implemented in our freely available R package 'penalizedSVM'.We conclude that the Elastic SCAD SVM is a flexible and robust tool for classification and feature selection tasks for high-dimensional data such as microarray data sets.

Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data

PubMed Central

2011-01-01

Background Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net. We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone. Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution. Results Feature selection methods with combined penalties (Elastic Net and Elastic SCAD SVMs) are more robust to a change of the model complexity than methods using single penalties. Our simulation study showed that Elastic SCAD SVM outperformed LASSO (L1) and SCAD SVMs. Moreover, Elastic SCAD SVM provided sparser classifiers in terms of median number of features selected than Elastic Net SVM and often better predicted than Elastic Net in terms of misclassification error. Finally, we applied the penalization methods described above on four publicly available breast cancer data sets. Elastic SCAD SVM was the only method providing robust classifiers in sparse and non-sparse situations. Conclusions The proposed Elastic SCAD SVM algorithm provides the advantages of the SCAD penalty and at the same time avoids sparsity limitations for non-sparse data. We were first to demonstrate that the integration of the interval search algorithm and penalized SVM classification techniques provides fast solutions on the optimization of tuning parameters. The penalized SVM classification algorithms as well as fixed grid and interval search for finding appropriate tuning parameters were implemented in our freely available R package 'penalizedSVM'. We conclude that the Elastic SCAD SVM is a flexible and robust tool for classification and feature selection tasks for high-dimensional data such as microarray data sets. PMID:21554689

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Visual coding with a population of direction-selective neurons.

PubMed

Fiscella, Michele; Franke, Felix; Farrow, Karl; Müller, Jan; Roska, Botond; da Silveira, Rava Azeredo; Hierlemann, Andreas

2015-10-01

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions. Copyright © 2015 the American Physiological Society.

Visual coding with a population of direction-selective neurons

PubMed Central

Farrow, Karl; Müller, Jan; Roska, Botond; Azeredo da Silveira, Rava; Hierlemann, Andreas

2015-01-01

The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions. PMID:26289471

Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness

PubMed Central

Samonds, Jason M.; Potetz, Brian R.; Lee, Tai Sing

2014-01-01

We propose using the statistical measurement of the sample skewness of the distribution of mean firing rates of a tuning curve to quantify sharpness of tuning. For some features, like binocular disparity, tuning curves are best described by relatively complex and sometimes diverse functions, making it difficult to quantify sharpness with a single function and parameter. Skewness provides a robust nonparametric measure of tuning curve sharpness that is invariant with respect to the mean and variance of the tuning curve and is straightforward to apply to a wide range of tuning, including simple orientation tuning curves and complex object tuning curves that often cannot even be described parametrically. Because skewness does not depend on a specific model or function of tuning, it is especially appealing to cases of sharpening where recurrent interactions among neurons produce sharper tuning curves that deviate in a complex manner from the feedforward function of tuning. Since tuning curves for all neurons are not typically well described by a single parametric function, this model independence additionally allows skewness to be applied to all recorded neurons, maximizing the statistical power of a set of data. We also compare skewness with other nonparametric measures of tuning curve sharpness and selectivity. Compared to these other nonparametric measures tested, skewness is best used for capturing the sharpness of multimodal tuning curves defined by narrow peaks (maximum) and broad valleys (minima). Finally, we provide a more formal definition of sharpness using a shape-based information gain measure and derive and show that skewness is correlated with this definition. PMID:24555451

A variant of sparse partial least squares for variable selection and data exploration.

PubMed

Olson Hunt, Megan J; Weissfeld, Lisa; Boudreau, Robert M; Aizenstein, Howard; Newman, Anne B; Simonsick, Eleanor M; Van Domelen, Dane R; Thomas, Fridtjof; Yaffe, Kristine; Rosano, Caterina

2014-01-01

When data are sparse and/or predictors multicollinear, current implementation of sparse partial least squares (SPLS) does not give estimates for non-selected predictors nor provide a measure of inference. In response, an approach termed "all-possible" SPLS is proposed, which fits a SPLS model for all tuning parameter values across a set grid. Noted is the percentage of time a given predictor is chosen, as well as the average non-zero parameter estimate. Using a "large" number of multicollinear predictors, simulation confirmed variables not associated with the outcome were least likely to be chosen as sparsity increased across the grid of tuning parameters, while the opposite was true for those strongly associated. Lastly, variables with a weak association were chosen more often than those with no association, but less often than those with a strong relationship to the outcome. Similarly, predictors most strongly related to the outcome had the largest average parameter estimate magnitude, followed by those with a weak relationship, followed by those with no relationship. Across two independent studies regarding the relationship between volumetric MRI measures and a cognitive test score, this method confirmed a priori hypotheses about which brain regions would be selected most often and have the largest average parameter estimates. In conclusion, the percentage of time a predictor is chosen is a useful measure for ordering the strength of the relationship between the independent and dependent variables, serving as a form of inference. The average parameter estimates give further insight regarding the direction and strength of association. As a result, all-possible SPLS gives more information than the dichotomous output of traditional SPLS, making it useful when undertaking data exploration and hypothesis generation for a large number of potential predictors.

Cation Selectivity in Biological Cation Channels Using Experimental Structural Information and Statistical Mechanical Simulation.

PubMed

Finnerty, Justin John; Peyser, Alexander; Carloni, Paolo

2015-01-01

Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores.

Constraining ecosystem model with adaptive Metropolis algorithm using boreal forest site eddy covariance measurements

NASA Astrophysics Data System (ADS)

Mäkelä, Jarmo; Susiluoto, Jouni; Markkanen, Tiina; Aurela, Mika; Järvinen, Heikki; Mammarella, Ivan; Hagemann, Stefan; Aalto, Tuula

2016-12-01

We examined parameter optimisation in the JSBACH (Kaminski et al., 2013; Knorr and Kattge, 2005; Reick et al., 2013) ecosystem model, applied to two boreal forest sites (Hyytiälä and Sodankylä) in Finland. We identified and tested key parameters in soil hydrology and forest water and carbon-exchange-related formulations, and optimised them using the adaptive Metropolis (AM) algorithm for Hyytiälä with a 5-year calibration period (2000-2004) followed by a 4-year validation period (2005-2008). Sodankylä acted as an independent validation site, where optimisations were not made. The tuning provided estimates for full distribution of possible parameters, along with information about correlation, sensitivity and identifiability. Some parameters were correlated with each other due to a phenomenological connection between carbon uptake and water stress or other connections due to the set-up of the model formulations. The latter holds especially for vegetation phenology parameters. The least identifiable parameters include phenology parameters, parameters connecting relative humidity and soil dryness, and the field capacity of the skin reservoir. These soil parameters were masked by the large contribution from vegetation transpiration. In addition to leaf area index and the maximum carboxylation rate, the most effective parameters adjusting the gross primary production (GPP) and evapotranspiration (ET) fluxes in seasonal tuning were related to soil wilting point, drainage and moisture stress imposed on vegetation. For daily and half-hourly tunings the most important parameters were the ratio of leaf internal CO2 concentration to external CO2 and the parameter connecting relative humidity and soil dryness. Effectively the seasonal tuning transferred water from soil moisture into ET, and daily and half-hourly tunings reversed this process. The seasonal tuning improved the month-to-month development of GPP and ET, and produced the most stable estimates of water use efficiency. When compared to the seasonal tuning, the daily tuning is worse on the seasonal scale. However, daily parametrisation reproduced the observations for average diurnal cycle best, except for the GPP for Sodankylä validation period, where half-hourly tuned parameters were better. In general, the daily tuning provided the largest reduction in model-data mismatch. The models response to drought was unaffected by our parametrisations and further studies are needed into enhancing the dry response in JSBACH.

A Novel Flexible Inertia Weight Particle Swarm Optimization Algorithm.

PubMed

Amoshahy, Mohammad Javad; Shamsi, Mousa; Sedaaghi, Mohammad Hossein

2016-01-01

Particle swarm optimization (PSO) is an evolutionary computing method based on intelligent collective behavior of some animals. It is easy to implement and there are few parameters to adjust. The performance of PSO algorithm depends greatly on the appropriate parameter selection strategies for fine tuning its parameters. Inertia weight (IW) is one of PSO's parameters used to bring about a balance between the exploration and exploitation characteristics of PSO. This paper proposes a new nonlinear strategy for selecting inertia weight which is named Flexible Exponential Inertia Weight (FEIW) strategy because according to each problem we can construct an increasing or decreasing inertia weight strategy with suitable parameters selection. The efficacy and efficiency of PSO algorithm with FEIW strategy (FEPSO) is validated on a suite of benchmark problems with different dimensions. Also FEIW is compared with best time-varying, adaptive, constant and random inertia weights. Experimental results and statistical analysis prove that FEIW improves the search performance in terms of solution quality as well as convergence rate.

A Novel Flexible Inertia Weight Particle Swarm Optimization Algorithm

PubMed Central

Shamsi, Mousa; Sedaaghi, Mohammad Hossein

2016-01-01

Particle swarm optimization (PSO) is an evolutionary computing method based on intelligent collective behavior of some animals. It is easy to implement and there are few parameters to adjust. The performance of PSO algorithm depends greatly on the appropriate parameter selection strategies for fine tuning its parameters. Inertia weight (IW) is one of PSO’s parameters used to bring about a balance between the exploration and exploitation characteristics of PSO. This paper proposes a new nonlinear strategy for selecting inertia weight which is named Flexible Exponential Inertia Weight (FEIW) strategy because according to each problem we can construct an increasing or decreasing inertia weight strategy with suitable parameters selection. The efficacy and efficiency of PSO algorithm with FEIW strategy (FEPSO) is validated on a suite of benchmark problems with different dimensions. Also FEIW is compared with best time-varying, adaptive, constant and random inertia weights. Experimental results and statistical analysis prove that FEIW improves the search performance in terms of solution quality as well as convergence rate. PMID:27560945

Parameter Tuning and Calibration of RegCM3 with MIT-Emanuel Cumulus Parameterization Scheme over CORDEX East Asian Domain

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

Zou, Liwei; Qian, Yun; Zhou, Tianjun

2014-10-01

In this study, we calibrated the performance of regional climate model RegCM3 with Massachusetts Institute of Technology (MIT)-Emanuel cumulus parameterization scheme over CORDEX East Asia domain by tuning the selected seven parameters through multiple very fast simulated annealing (MVFSA) sampling method. The seven parameters were selected based on previous studies, which customized the RegCM3 with MIT-Emanuel scheme through three different ways by using the sensitivity experiments. The responses of model results to the seven parameters were investigated. Since the monthly total rainfall is constrained, the simulated spatial pattern of rainfall and the probability density function (PDF) distribution of daily rainfallmore » rates are significantly improved in the optimal simulation. Sensitivity analysis suggest that the parameter “relative humidity criteria” (RH), which has not been considered in the default simulation, has the largest effect on the model results. The responses of total rainfall over different regions to RH were examined. Positive responses of total rainfall to RH are found over northern equatorial western Pacific, which are contributed by the positive responses of explicit rainfall. Followed by an increase of RH, the increases of the low-level convergence and the associated increases in cloud water favor the increase of the explicit rainfall. The identified optimal parameters constrained by the total rainfall have positive effects on the low-level circulation and the surface air temperature. Furthermore, the optimized parameters based on the extreme case are suitable for a normal case and the model’s new version with mixed convection scheme.« less

Capsule implosion optimization during the indirect-drive National Ignition Campaign

NASA Astrophysics Data System (ADS)

Landen, O. L.; Edwards, J.; Haan, S. W.; Robey, H. F.; Milovich, J.; Spears, B. K.; Weber, S. V.; Clark, D. S.; Lindl, J. D.; MacGowan, B. J.; Moses, E. I.; Atherton, J.; Amendt, P. A.; Boehly, T. R.; Bradley, D. K.; Braun, D. G.; Callahan, D. A.; Celliers, P. M.; Collins, G. W.; Dewald, E. L.; Divol, L.; Frenje, J. A.; Glenzer, S. H.; Hamza, A.; Hammel, B. A.; Hicks, D. G.; Hoffman, N.; Izumi, N.; Jones, O. S.; Kilkenny, J. D.; Kirkwood, R. K.; Kline, J. L.; Kyrala, G. A.; Marinak, M. M.; Meezan, N.; Meyerhofer, D. D.; Michel, P.; Munro, D. H.; Olson, R. E.; Nikroo, A.; Regan, S. P.; Suter, L. J.; Thomas, C. A.; Wilson, D. C.

2011-05-01

Capsule performance optimization campaigns will be conducted at the National Ignition Facility [G. H. Miller, E. I. Moses, and C. R. Wuest, Nucl. Fusion 44, 228 (2004)] to substantially increase the probability of ignition. The campaigns will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models using a variety of ignition capsule surrogates before proceeding to cryogenic-layered implosions and ignition experiments. The quantitative goals and technique options and down selections for the tuning campaigns are first explained. The computationally derived sensitivities to key laser and target parameters are compared to simple analytic models to gain further insight into the physics of the tuning techniques. The results of the validation of the tuning techniques at the OMEGA facility [J. M. Soures et al., Phys. Plasmas 3, 2108 (1996)] under scaled hohlraum and capsule conditions relevant to the ignition design are shown to meet the required sensitivity and accuracy. A roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget. Finally, we show how the tuning precision will be improved after a number of shots and iterations to meet an acceptable level of residual uncertainty.

The feasibility of manual parameter tuning for deformable breast MR image registration from a multi-objective optimization perspective.

PubMed

Pirpinia, Kleopatra; Bosman, Peter A N; Loo, Claudette E; Winter-Warnars, Gonneke; Janssen, Natasja N Y; Scholten, Astrid N; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

2017-06-23

Deformable image registration is typically formulated as an optimization problem involving a linearly weighted combination of terms that correspond to objectives of interest (e.g. similarity, deformation magnitude). The weights, along with multiple other parameters, need to be manually tuned for each application, a task currently addressed mainly via trial-and-error approaches. Such approaches can only be successful if there is a sensible interplay between parameters, objectives, and desired registration outcome. This, however, is not well established. To study this interplay, we use multi-objective optimization, where multiple solutions exist that represent the optimal trade-offs between the objectives, forming a so-called Pareto front. Here, we focus on weight tuning. To study the space a user has to navigate during manual weight tuning, we randomly sample multiple linear combinations. To understand how these combinations relate to desirability of registration outcome, we associate with each outcome a mean target registration error (TRE) based on expert-defined anatomical landmarks. Further, we employ a multi-objective evolutionary algorithm that optimizes the weight combinations, yielding a Pareto front of solutions, which can be directly navigated by the user. To study how the complexity of manual weight tuning changes depending on the registration problem, we consider an easy problem, prone-to-prone breast MR image registration, and a hard problem, prone-to-supine breast MR image registration. Lastly, we investigate how guidance information as an additional objective influences the prone-to-supine registration outcome. Results show that the interplay between weights, objectives, and registration outcome makes manual weight tuning feasible for the prone-to-prone problem, but very challenging for the harder prone-to-supine problem. Here, patient-specific, multi-objective weight optimization is needed, obtaining a mean TRE of 13.6 mm without guidance information reduced to 7.3 mm with guidance information, but also providing a Pareto front that exhibits an intuitively sensible interplay between weights, objectives, and registration outcome, allowing outcome selection.

The feasibility of manual parameter tuning for deformable breast MR image registration from a multi-objective optimization perspective

NASA Astrophysics Data System (ADS)

Pirpinia, Kleopatra; Bosman, Peter A. N.; E Loo, Claudette; Winter-Warnars, Gonneke; Y Janssen, Natasja N.; Scholten, Astrid N.; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

2017-07-01

Deformable image registration is typically formulated as an optimization problem involving a linearly weighted combination of terms that correspond to objectives of interest (e.g. similarity, deformation magnitude). The weights, along with multiple other parameters, need to be manually tuned for each application, a task currently addressed mainly via trial-and-error approaches. Such approaches can only be successful if there is a sensible interplay between parameters, objectives, and desired registration outcome. This, however, is not well established. To study this interplay, we use multi-objective optimization, where multiple solutions exist that represent the optimal trade-offs between the objectives, forming a so-called Pareto front. Here, we focus on weight tuning. To study the space a user has to navigate during manual weight tuning, we randomly sample multiple linear combinations. To understand how these combinations relate to desirability of registration outcome, we associate with each outcome a mean target registration error (TRE) based on expert-defined anatomical landmarks. Further, we employ a multi-objective evolutionary algorithm that optimizes the weight combinations, yielding a Pareto front of solutions, which can be directly navigated by the user. To study how the complexity of manual weight tuning changes depending on the registration problem, we consider an easy problem, prone-to-prone breast MR image registration, and a hard problem, prone-to-supine breast MR image registration. Lastly, we investigate how guidance information as an additional objective influences the prone-to-supine registration outcome. Results show that the interplay between weights, objectives, and registration outcome makes manual weight tuning feasible for the prone-to-prone problem, but very challenging for the harder prone-to-supine problem. Here, patient-specific, multi-objective weight optimization is needed, obtaining a mean TRE of 13.6 mm without guidance information reduced to 7.3 mm with guidance information, but also providing a Pareto front that exhibits an intuitively sensible interplay between weights, objectives, and registration outcome, allowing outcome selection.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5

NASA Astrophysics Data System (ADS)

Ogura, Tomoo; Shiogama, Hideo; Watanabe, Masahiro; Yoshimori, Masakazu; Yokohata, Tokuta; Annan, James D.; Hargreaves, Julia C.; Ushigami, Naoto; Hirota, Kazuya; Someya, Yu; Kamae, Youichi; Tatebe, Hiroaki; Kimoto, Masahide

2017-12-01

This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used output of a perturbed parameter ensemble (PPE) experiment conducted with an atmosphere-ocean general circulation model (AOGCM) without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5) was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitude-longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.

Differential-Evolution Control Parameter Optimization for Unmanned Aerial Vehicle Path Planning

PubMed Central

Kok, Kai Yit; Rajendran, Parvathy

2016-01-01

The differential evolution algorithm has been widely applied on unmanned aerial vehicle (UAV) path planning. At present, four random tuning parameters exist for differential evolution algorithm, namely, population size, differential weight, crossover, and generation number. These tuning parameters are required, together with user setting on path and computational cost weightage. However, the optimum settings of these tuning parameters vary according to application. Instead of trial and error, this paper presents an optimization method of differential evolution algorithm for tuning the parameters of UAV path planning. The parameters that this research focuses on are population size, differential weight, crossover, and generation number. The developed algorithm enables the user to simply define the weightage desired between the path and computational cost to converge with the minimum generation required based on user requirement. In conclusion, the proposed optimization of tuning parameters in differential evolution algorithm for UAV path planning expedites and improves the final output path and computational cost. PMID:26943630

Temporal Tuning of Word- and Face-selective Cortex.

PubMed

Yeatman, Jason D; Norcia, Anthony M

2016-11-01

Sensitivity to temporal change places fundamental limits on object processing in the visual system. An emerging consensus from the behavioral and neuroimaging literature suggests that temporal resolution differs substantially for stimuli of different complexity and for brain areas at different levels of the cortical hierarchy. Here, we used steady-state visually evoked potentials to directly measure three fundamental parameters that characterize the underlying neural response to text and face images: temporal resolution, peak temporal frequency, and response latency. We presented full-screen images of text or a human face, alternated with a scrambled image, at temporal frequencies between 1 and 12 Hz. These images elicited a robust response at the first harmonic that showed differential tuning, scalp topography, and delay for the text and face images. Face-selective responses were maximal at 4 Hz, but text-selective responses, by contrast, were maximal at 1 Hz. The topography of the text image response was strongly left-lateralized at higher stimulation rates, whereas the response to the face image was slightly right-lateralized but nearly bilateral at all frequencies. Both text and face images elicited steady-state activity at more than one apparent latency; we observed early (141-160 msec) and late (>250 msec) text- and face-selective responses. These differences in temporal tuning profiles are likely to reflect differences in the nature of the computations performed by word- and face-selective cortex. Despite the close proximity of word- and face-selective regions on the cortical surface, our measurements demonstrate substantial differences in the temporal dynamics of word- versus face-selective responses.

Cation Selectivity in Biological Cation Channels Using Experimental Structural Information and Statistical Mechanical Simulation

PubMed Central

Finnerty, Justin John

2015-01-01

Cation selective channels constitute the gate for ion currents through the cell membrane. Here we present an improved statistical mechanical model based on atomistic structural information, cation hydration state and without tuned parameters that reproduces the selectivity of biological Na+ and Ca2+ ion channels. The importance of the inclusion of step-wise cation hydration in these results confirms the essential role partial dehydration plays in the bacterial Na+ channels. The model, proven reliable against experimental data, could be straightforwardly used for designing Na+ and Ca2+ selective nanopores. PMID:26460827

Structural tuning of photoluminescence in nanoporous anodic alumina by hard anodization in oxalic and malonic acids

PubMed Central

2012-01-01

We report on an exhaustive and systematic study about the photoluminescent properties of nanoporous anodic alumina membranes fabricated by the one-step anodization process under hard conditions in oxalic and malonic acids. This optical property is analysed as a function of several parameters (i.e. hard anodization voltage, pore diameter, membrane thickness, annealing temperature and acid electrolyte). This analysis makes it possible to tune the photoluminescent behaviour at will simply by modifying the structural characteristics of these membranes. This structural tuning ability is of special interest in such fields as optoelectronics, in which an accurate design of the basic nanostructures (e.g. microcavities, resonators, filters, supports, etc.) yields the control over their optical properties and, thus, upon the performance of the nanodevices derived from them (biosensors, interferometers, selective filters, etc.) PMID:22515214

Tuning Parameters in Heuristics by Using Design of Experiments Methods

NASA Technical Reports Server (NTRS)

Arin, Arif; Rabadi, Ghaith; Unal, Resit

2010-01-01

With the growing complexity of today's large scale problems, it has become more difficult to find optimal solutions by using exact mathematical methods. The need to find near-optimal solutions in an acceptable time frame requires heuristic approaches. In many cases, however, most heuristics have several parameters that need to be "tuned" before they can reach good results. The problem then turns into "finding best parameter setting" for the heuristics to solve the problems efficiently and timely. One-Factor-At-a-Time (OFAT) approach for parameter tuning neglects the interactions between parameters. Design of Experiments (DOE) tools can be instead employed to tune the parameters more effectively. In this paper, we seek the best parameter setting for a Genetic Algorithm (GA) to solve the single machine total weighted tardiness problem in which n jobs must be scheduled on a single machine without preemption, and the objective is to minimize the total weighted tardiness. Benchmark instances for the problem are available in the literature. To fine tune the GA parameters in the most efficient way, we compare multiple DOE models including 2-level (2k ) full factorial design, orthogonal array design, central composite design, D-optimal design and signal-to-noise (SIN) ratios. In each DOE method, a mathematical model is created using regression analysis, and solved to obtain the best parameter setting. After verification runs using the tuned parameter setting, the preliminary results for optimal solutions of multiple instances were found efficiently.

Robust local search for spacecraft operations using adaptive noise

NASA Technical Reports Server (NTRS)

Fukunaga, Alex S.; Rabideau, Gregg; Chien, Steve

2004-01-01

Randomization is a standard technique for improving the performance of local search algorithms for constraint satisfaction. However, it is well-known that local search algorithms are constraints satisfaction. However, it is well-known that local search algorithms are to the noise values selected. We investigate the use of an adaptive noise mechanism in an iterative repair-based planner/scheduler for spacecraft operations. Preliminary results indicate that adaptive noise makes the use of randomized repair moves safe and robust; that is, using adaptive noise makes it possible to consistently achieve, performance comparable with the best tuned noise setting without the need for manually tuning the noise parameter.

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

DOEpatents

Johnstone, Carol J [Warrenville, IL

2011-02-01

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

Well-tempered metadynamics: a smoothly-converging and tunable free-energy method

NASA Astrophysics Data System (ADS)

Barducci, Alessandro; Bussi, Giovanni; Parrinello, Michele

2008-03-01

We present [1] a method for determining the free energy dependence on a selected number of order parameters using an adaptive bias. The formalism provides a unified description which has metadynamics and canonical sampling as limiting cases. Convergence and errors can be rigorously and easily controlled. The parameters of the simulation can be tuned so as to focus the computational effort only on the physically relevantregions of the order parameter space. The algorithm is tested on the reconstruction of alanine dipeptide free energy landscape. [1] A. Barducci, G. Bussi and M. Parrinello, Phys. Rev. Lett., accepted (2007).

Design and parametric study on energy harvesting from bridge vibration using tuned dual-mass damper systems

NASA Astrophysics Data System (ADS)

Takeya, Kouichi; Sasaki, Eiichi; Kobayashi, Yusuke

2016-01-01

A bridge vibration energy harvester has been proposed in this paper using a tuned dual-mass damper system, named hereafter Tuned Mass Generator (TMG). A linear electromagnetic transducer has been applied to harvest and make use of the unused reserve of energy the aforementioned damper system absorbs. The benefits of using dual-mass systems over single-mass systems for power generation have been clarified according to the theory of vibrations. TMG parameters have been determined considering multi-domain parameters, and TMG has been tuned using a newly proposed parameter design method. Theoretical analysis results have shown that for effective energy harvesting, it is essential that TMG has robustness against uncertainties in bridge vibrations and tuning errors, and the proposed parameter design method for TMG has demonstrated this feature.

Capsule implosion optimization during the indirect-drive National Ignition Campaign

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

Landen, O. L.; Edwards, J.; Haan, S. W.

2011-05-15

Capsule performance optimization campaigns will be conducted at the National Ignition Facility [G. H. Miller, E. I. Moses, and C. R. Wuest, Nucl. Fusion 44, 228 (2004)] to substantially increase the probability of ignition. The campaigns will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models using a variety of ignition capsule surrogates before proceeding to cryogenic-layered implosions and ignition experiments. The quantitative goals and technique options and down selections for the tuning campaigns are first explained. The computationally derived sensitivities to key laser and target parameters are compared to simple analyticmore » models to gain further insight into the physics of the tuning techniques. The results of the validation of the tuning techniques at the OMEGA facility [J. M. Soures et al., Phys. Plasmas 3, 2108 (1996)] under scaled hohlraum and capsule conditions relevant to the ignition design are shown to meet the required sensitivity and accuracy. A roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget. Finally, we show how the tuning precision will be improved after a number of shots and iterations to meet an acceptable level of residual uncertainty.« less

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-05-01

Physical parameterizations in General Circulation Models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.

Optimization of PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Azmi, Nur Iffah Mohamed; Arifin Mat Piah, Kamal; Yusoff, Wan Azhar Wan; Romlay, Fadhlur Rahman Mohd

2018-03-01

Controller that uses PID parameters requires a good tuning method in order to improve the control system performance. Tuning PID control method is divided into two namely the classical methods and the methods of artificial intelligence. Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. Previously, researchers had integrated PSO algorithms in the PID parameter tuning process. This research aims to improve the PSO-PID tuning algorithms by integrating the tuning process with the Variable Weight Grey- Taguchi Design of Experiment (DOE) method. This is done by conducting the DOE on the two PSO optimizing parameters: the particle velocity limit and the weight distribution factor. Computer simulations and physical experiments were conducted by using the proposed PSO- PID with the Variable Weight Grey-Taguchi DOE and the classical Ziegler-Nichols methods. They are implemented on the hydraulic positioning system. Simulation results show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE has reduced the rise time by 48.13% and settling time by 48.57% compared to the Ziegler-Nichols method. Furthermore, the physical experiment results also show that the proposed PSO-PID with the Variable Weight Grey-Taguchi DOE tuning method responds better than Ziegler-Nichols tuning. In conclusion, this research has improved the PSO-PID parameter by applying the PSO-PID algorithm together with the Variable Weight Grey-Taguchi DOE method as a tuning method in the hydraulic positioning system.

Parameters-tuning of PID controller for automatic voltage regulators using the African buffalo optimization.

PubMed

Odili, Julius Beneoluchi; Mohmad Kahar, Mohd Nizam; Noraziah, A

2017-01-01

In this paper, an attempt is made to apply the African Buffalo Optimization (ABO) to tune the parameters of a PID controller for an effective Automatic Voltage Regulator (AVR). Existing metaheuristic tuning methods have been proven to be quite successful but there were observable areas that need improvements especially in terms of the system's gain overshoot and steady steady state errors. Using the ABO algorithm where each buffalo location in the herd is a candidate solution to the Proportional-Integral-Derivative parameters was very helpful in addressing these two areas of concern. The encouraging results obtained from the simulation of the PID Controller parameters-tuning using the ABO when compared with the performance of Genetic Algorithm PID (GA-PID), Particle-Swarm Optimization PID (PSO-PID), Ant Colony Optimization PID (ACO-PID), PID, Bacteria-Foraging Optimization PID (BFO-PID) etc makes ABO-PID a good addition to solving PID Controller tuning problems using metaheuristics.

Tuning of active vibration controllers for ACTEX by genetic algorithm

NASA Astrophysics Data System (ADS)

Kwak, Moon K.; Denoyer, Keith K.

1999-06-01

This paper is concerned with the optimal tuning of digitally programmable analog controllers on the ACTEX-1 smart structures flight experiment. The programmable controllers for each channel include a third order Strain Rate Feedback (SRF) controller, a fifth order SRF controller, a second order Positive Position Feedback (PPF) controller, and a fourth order PPF controller. Optimal manual tuning of several control parameters can be a difficult task even though the closed-loop control characteristics of each controller are well known. Hence, the automatic tuning of individual control parameters using Genetic Algorithms is proposed in this paper. The optimal control parameters of each control law are obtained by imposing a constraint on the closed-loop frequency response functions using the ACTEX mathematical model. The tuned control parameters are then uploaded to the ACTEX electronic control electronics and experiments on the active vibration control are carried out in space. The experimental results on ACTEX will be presented.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2007-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine's performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2007-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least-squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2005-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs such as thrust. The engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends upon knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined which accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

A tuning algorithm for model predictive controllers based on genetic algorithms and fuzzy decision making.

PubMed

van der Lee, J H; Svrcek, W Y; Young, B R

2008-01-01

Model Predictive Control is a valuable tool for the process control engineer in a wide variety of applications. Because of this the structure of an MPC can vary dramatically from application to application. There have been a number of works dedicated to MPC tuning for specific cases. Since MPCs can differ significantly, this means that these tuning methods become inapplicable and a trial and error tuning approach must be used. This can be quite time consuming and can result in non-optimum tuning. In an attempt to resolve this, a generalized automated tuning algorithm for MPCs was developed. This approach is numerically based and combines a genetic algorithm with multi-objective fuzzy decision-making. The key advantages to this approach are that genetic algorithms are not problem specific and only need to be adapted to account for the number and ranges of tuning parameters for a given MPC. As well, multi-objective fuzzy decision-making can handle qualitative statements of what optimum control is, in addition to being able to use multiple inputs to determine tuning parameters that best match the desired results. This is particularly useful for multi-input, multi-output (MIMO) cases where the definition of "optimum" control is subject to the opinion of the control engineer tuning the system. A case study will be presented in order to illustrate the use of the tuning algorithm. This will include how different definitions of "optimum" control can arise, and how they are accounted for in the multi-objective decision making algorithm. The resulting tuning parameters from each of the definition sets will be compared, and in doing so show that the tuning parameters vary in order to meet each definition of optimum control, thus showing the generalized automated tuning algorithm approach for tuning MPCs is feasible.

Analysis of filter tuning techniques for sequential orbit determination

NASA Technical Reports Server (NTRS)

Lee, T.; Yee, C.; Oza, D.

1995-01-01

This paper examines filter tuning techniques for a sequential orbit determination (OD) covariance analysis. Recently, there has been a renewed interest in sequential OD, primarily due to the successful flight qualification of the Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) using Doppler data extracted onboard the Extreme Ultraviolet Explorer (EUVE) spacecraft. TONS computes highly accurate orbit solutions onboard the spacecraft in realtime using a sequential filter. As the result of the successful TONS-EUVE flight qualification experiment, the Earth Observing System (EOS) AM-1 Project has selected TONS as the prime navigation system. In addition, sequential OD methods can be used successfully for ground OD. Whether data are processed onboard or on the ground, a sequential OD procedure is generally favored over a batch technique when a realtime automated OD system is desired. Recently, OD covariance analyses were performed for the TONS-EUVE and TONS-EOS missions using the sequential processing options of the Orbit Determination Error Analysis System (ODEAS). ODEAS is the primary covariance analysis system used by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD). The results of these analyses revealed a high sensitivity of the OD solutions to the state process noise filter tuning parameters. The covariance analysis results show that the state estimate error contributions from measurement-related error sources, especially those due to the random noise and satellite-to-satellite ionospheric refraction correction errors, increase rapidly as the state process noise increases. These results prompted an in-depth investigation of the role of the filter tuning parameters in sequential OD covariance analysis. This paper analyzes how the spacecraft state estimate errors due to dynamic and measurement-related error sources are affected by the process noise level used. This information is then used to establish guidelines for determining optimal filter tuning parameters in a given sequential OD scenario for both covariance analysis and actual OD. Comparisons are also made with corresponding definitive OD results available from the TONS-EUVE analysis.

The qualitative assessment of pneumatic actuators operation in terms of vibration criteria

NASA Astrophysics Data System (ADS)

Hetmanczyk, M. P.; Michalski, P.

2015-11-01

The work quality of pneumatic actuators can be assessed in terms of multiple criteria. In the case of complex systems with pneumatic actuators retained at end positions (with occurrence of piston impact in cylinder covers) the vibration criteria constitute the most reliable indicators. The paper presents an impact assessment on the operating condition of the rodless pneumatic cylinder regarding to selected vibrational symptoms. On the basis of performed analysis the authors had shown meaningful premises allowing an evaluation of the performance and tuning of end position damping piston movement with usage the most common diagnostic tools (portable vibration analyzers). The presented method is useful in tuning of parameters in industrial conditions.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-11-01

Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

Intelligent tuning method of PID parameters based on iterative learning control for atomic force microscopy.

PubMed

Liu, Hui; Li, Yingzi; Zhang, Yingxu; Chen, Yifu; Song, Zihang; Wang, Zhenyu; Zhang, Suoxin; Qian, Jianqiang

2018-01-01

Proportional-integral-derivative (PID) parameters play a vital role in the imaging process of an atomic force microscope (AFM). Traditional parameter tuning methods require a lot of manpower and it is difficult to set PID parameters in unattended working environments. In this manuscript, an intelligent tuning method of PID parameters based on iterative learning control is proposed to self-adjust PID parameters of the AFM according to the sample topography. This method gets enough information about the output signals of PID controller and tracking error, which will be used to calculate the proper PID parameters, by repeated line scanning until convergence before normal scanning to learn the topography. Subsequently, the appropriate PID parameters are obtained by fitting method and then applied to the normal scanning process. The feasibility of the method is demonstrated by the convergence analysis. Simulations and experimental results indicate that the proposed method can intelligently tune PID parameters of the AFM for imaging different topographies and thus achieve good tracking performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method

NASA Astrophysics Data System (ADS)

Barducci, Alessandro; Bussi, Giovanni; Parrinello, Michele

2008-01-01

We present a method for determining the free-energy dependence on a selected number of collective variables using an adaptive bias. The formalism provides a unified description which has metadynamics and canonical sampling as limiting cases. Convergence and errors can be rigorously and easily controlled. The parameters of the simulation can be tuned so as to focus the computational effort only on the physically relevant regions of the order parameter space. The algorithm is tested on the reconstruction of an alanine dipeptide free-energy landscape.

Well-tempered metadynamics: a smoothly converging and tunable free-energy method.

PubMed

Barducci, Alessandro; Bussi, Giovanni; Parrinello, Michele

2008-01-18

We present a method for determining the free-energy dependence on a selected number of collective variables using an adaptive bias. The formalism provides a unified description which has metadynamics and canonical sampling as limiting cases. Convergence and errors can be rigorously and easily controlled. The parameters of the simulation can be tuned so as to focus the computational effort only on the physically relevant regions of the order parameter space. The algorithm is tested on the reconstruction of an alanine dipeptide free-energy landscape.

The influence of probe level on the tuning of stimulus frequency otoacoustic emissions and behavioral test in human.

PubMed

Wang, Yao; Gong, Qin; Zhang, Tao

2016-05-10

Frequency selectivity (FS) of the auditory system is established at the level of the cochlea and it is important for the perception of complex sounds. Although direct measurements of cochlear FS require surgical preparation, it can also be estimated with the measurements of otoacoustic emissions or behavioral tests, including stimulus frequency otoacoustic emission suppression tuning curves (SFOAE STCs) or psychophysical tuning curves (PTCs). These two methods result in similar estimates of FS at low probe levels. As the compressive nonlinearity of cochlea is strongly dependent on the stimulus intensity, the sharpness of tuning curves which is relevant to the cochlear nonlinearity will change as a function of probe level. The present study aims to investigate the influence of different probe levels on the relationship between SFOAE STCs and PTCs. The study included 15 young subjects with normal hearing. SFOAE STCs and PTCs were recorded at low and moderate probe levels for frequencies centred at 1, 2, and 4 kHz. The ratio or the difference of the characteristic parameters between the two methods was calculated at each probe level. The effect of probe level on the ratio or the difference between the parameters of SFOAE STCs and PTCs was then statistically analysed. The tuning of SFOAE STCs was significantly positively correlated with the tuning of the PTCs at both low and moderate probe levels; yet, at the moderate probe level, the SFOAE STCs were consistently broader than the PTCs. The mean ratio of sharpness of tuning at low probe levels was constantly around 1 while around 1.5 at moderate probe levels. Probe level had a significant effect on the sharpness of tuning between the two methods of estimating FS. SFOAE STC seems a good alternative measurement of PTC for FS assessment at low probe levels. At moderate probe levels, SFOAE STC and PTC were not equivalent measures of the FS in terms of their bandwidths. Because SFOAE STCs are not biased by higher levels auditory processing, they may represent cochlear FS better than PTCs.

Adaptive Self-Tuning Networks

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Lawry, B.; Chael, E. P.; Faust, A.; Peterson, M. G.

2015-12-01

The quality of automatic detections from seismic sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. Yet, achieving superior automatic detection of seismic events is closely related to these parameters. We present an automated sensor tuning (AST) system that learns near-optimal parameter settings for each event type using neuro-dynamic programming (reinforcement learning) trained with historic data. AST learns to test the raw signal against all event-settings and automatically self-tunes to an emerging event in real-time. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Reducing false alarms early in the seismic pipeline processing will have a significant impact on this goal. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections in seismic waveforms from a network of stations, we show that AST increases the probability of detection while decreasing false alarms.

Mobile, Virtual Enhancements for Rehabilitation (MOVER)

DTIC Science & Technology

2015-08-28

bottom of the figure. The patient uses COTS input devices, such as the Microsoft Kinect and the Wii Balance Board , to perform therapeutic exercises...specific, commonly used balance exercises into the system and enabling the therapists to select and customize pre-identified parameters for these exercises... balance disorder patients. We made these games highly customizable to enable therapists to tune each game to the capabilities of individual

Robust check loss-based variable selection of high-dimensional single-index varying-coefficient model

NASA Astrophysics Data System (ADS)

Song, Yunquan; Lin, Lu; Jian, Ling

2016-07-01

Single-index varying-coefficient model is an important mathematical modeling method to model nonlinear phenomena in science and engineering. In this paper, we develop a variable selection method for high-dimensional single-index varying-coefficient models using a shrinkage idea. The proposed procedure can simultaneously select significant nonparametric components and parametric components. Under defined regularity conditions, with appropriate selection of tuning parameters, the consistency of the variable selection procedure and the oracle property of the estimators are established. Moreover, due to the robustness of the check loss function to outliers in the finite samples, our proposed variable selection method is more robust than the ones based on the least squares criterion. Finally, the method is illustrated with numerical simulations.

Longitudinal control of aircraft dynamics based on optimization of PID parameters

NASA Astrophysics Data System (ADS)

Deepa, S. N.; Sudha, G.

2016-03-01

Recent years many flight control systems and industries are employing PID controllers to improve the dynamic behavior of the characteristics. In this paper, PID controller is developed to improve the stability and performance of general aviation aircraft system. Designing the optimum PID controller parameters for a pitch control aircraft is important in expanding the flight safety envelope. Mathematical model is developed to describe the longitudinal pitch control of an aircraft. The PID controller is designed based on the dynamic modeling of an aircraft system. Different tuning methods namely Zeigler-Nichols method (ZN), Modified Zeigler-Nichols method, Tyreus-Luyben tuning, Astrom-Hagglund tuning methods are employed. The time domain specifications of different tuning methods are compared to obtain the optimum parameters value. The results prove that PID controller tuned by Zeigler-Nichols for aircraft pitch control dynamics is better in stability and performance in all conditions. Future research work of obtaining optimum PID controller parameters using artificial intelligence techniques should be carried out.

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and computer vision literatures. This demonstrates benefits for all the functional enhancements of the HDSN, the class tuning inherent to discriminant saliency, and saliency layers based on templates of increasing target selectivity and invariance. Altogether, these experiments suggest that there are non-trivial benefits in integrating attention and recognition.

The Art and Science of Climate Model Tuning

DOE PAGES

Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew; ...

2017-03-31

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

The Art and Science of Climate Model Tuning

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

Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew

The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less

Auto-tuning for NMR probe using LabVIEW

NASA Astrophysics Data System (ADS)

Quen, Carmen; Pham, Stephanie; Bernal, Oscar

2014-03-01

Typical manual NMR-tuning method is not suitable for broadband spectra spanning several megahertz linewidths. Among the main problems encountered during manual tuning are pulse-power reproducibility, baselines, and transmission line reflections, to name a few. We present a design of an auto-tuning system using graphic programming language, LabVIEW, to minimize these problems. The program uses a simplified model of the NMR probe conditions near perfect tuning to mimic the tuning process and predict the position of the capacitor shafts needed to achieve the desirable impedance. The tuning capacitors of the probe are controlled by stepper motors through a LabVIEW/computer interface. Our program calculates the effective capacitance needed to tune the probe and provides controlling parameters to advance the motors in the right direction. The impedance reading of a network analyzer can be used to correct the model parameters in real time for feedback control.

Meta-Learning Approach for Automatic Parameter Tuning: A Case Study with Educational Datasets

ERIC Educational Resources Information Center

Molina, M. M.; Luna, J. M.; Romero, C.; Ventura, S.

2012-01-01

This paper proposes to the use of a meta-learning approach for automatic parameter tuning of a well-known decision tree algorithm by using past information about algorithm executions. Fourteen educational datasets were analysed using various combinations of parameter values to examine the effects of the parameter values on accuracy classification.…

TU-AB-BRC-05: Creation of a Monte Carlo TrueBeam Model by Reproducing Varian Phase Space Data

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

O’Grady, K; Davis, S; Seuntjens, J

Purpose: To create a Varian TrueBeam 6 MV FFF Monte Carlo model using BEAMnrc/EGSnrc that accurately reproduces the Varian representative dataset, followed by tuning the model’s source parameters to accurately reproduce in-house measurements. Methods: A BEAMnrc TrueBeam model for 6 MV FFF has been created by modifying a validated 6 MV Varian CL21EX model. Geometric dimensions and materials were adjusted in a trial and error approach to match the fluence and spectra of TrueBeam phase spaces output by the Varian VirtuaLinac. Once the model’s phase space matched Varian’s counterpart using the default source parameters, it was validated to match 10more » × 10 cm{sup 2} Varian representative data obtained with the IBA CC13. The source parameters were then tuned to match in-house 5 × 5 cm{sup 2} PTW microDiamond measurements. All dose to water simulations included detector models to include the effects of volume averaging and the non-water equivalence of the chamber materials, allowing for more accurate source parameter selection. Results: The Varian phase space spectra and fluence were matched with excellent agreement. The in-house model’s PDD agreement with CC13 TrueBeam representative data was within 0.9% local percent difference beyond the first 3 mm. Profile agreement at 10 cm depth was within 0.9% local percent difference and 1.3 mm distance-to-agreement in the central axis and penumbra regions, respectively. Once the source parameters were tuned, PDD agreement with microDiamond measurements was within 0.9% local percent difference beyond 2 mm. The microDiamond profile agreement at 10 cm depth was within 0.6% local percent difference and 0.4 mm distance-to-agreement in the central axis and penumbra regions, respectively. Conclusion: An accurate in-house Monte Carlo model of the Varian TrueBeam was achieved independently of the Varian phase space solution and was tuned to in-house measurements. KO acknowledges partial support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290).« less

Tuning a climate model using nudging to reanalysis.

NASA Astrophysics Data System (ADS)

Cheedela, S. K.; Mapes, B. E.

2014-12-01

Tuning a atmospheric general circulation model involves a daunting task of adjusting non-observable parameters to adjust the mean climate. These parameters arise from necessity to describe unresolved flow through parametrizations. Tuning a climate model is often done with certain set of priorities, such as global mean temperature, net top of the atmosphere radiation. These priorities are hard enough to reach let alone reducing systematic biases in the models. The goal of currently study is to explore alternate ways to tune a climate model to reduce some systematic biases that can be used in synergy with existing efforts. Nudging a climate model to a known state is a poor man's inverse of tuning process described above. Our approach involves nudging the atmospheric model to state of art reanalysis fields thereby providing a balanced state with respect to the global mean temperature and winds. The tendencies derived from nudging are negative of errors from physical parametrizations as the errors from dynamical core would be small. Patterns of nudging are compared to the patterns of different physical parametrizations to decipher the cause for certain biases in relation to tuning parameters. This approach might also help in understanding certain compensating errors that arise from tuning process. ECHAM6 is a comprehensive general model, also used in recent Coupled Model Intercomparision Project(CMIP5). The approach used to tune it and effect of certain parameters that effect its mean climate are reported clearly, hence it serves as a benchmark for our approach. Our planned experiments include nudging ECHAM6 atmospheric model to European Center Reanalysis (ERA-Interim) and reanalysis from National Center for Environmental Prediction (NCEP) and decipher choice of certain parameters that lead to systematic biases in its simulations. Of particular interest are reducing long standing biases related to simulation of Asian summer monsoon.

Bias in error estimation when using cross-validation for model selection.

PubMed

Varma, Sudhir; Simon, Richard

2006-02-23

Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data. We used CV to optimize the classification parameters for two kinds of classifiers; Shrunken Centroids and Support Vector Machines (SVM). Random training datasets were created, with no difference in the distribution of the features between the two classes. Using these "null" datasets, we selected classifier parameter values that minimized the CV error estimate. 10-fold CV was used for Shrunken Centroids while Leave-One-Out-CV (LOOCV) was used for the SVM. Independent test data was created to estimate the true error. With "null" and "non null" (with differential expression between the classes) data, we also tested a nested CV procedure, where an inner CV loop is used to perform the tuning of the parameters while an outer CV is used to compute an estimate of the error. The CV error estimate for the classifier with the optimal parameters was found to be a substantially biased estimate of the true error that the classifier would incur on independent data. Even though there is no real difference between the two classes for the "null" datasets, the CV error estimate for the Shrunken Centroid with the optimal parameters was less than 30% on 18.5% of simulated training data-sets. For SVM with optimal parameters the estimated error rate was less than 30% on 38% of "null" data-sets. Performance of the optimized classifiers on the independent test set was no better than chance. The nested CV procedure reduces the bias considerably and gives an estimate of the error that is very close to that obtained on the independent testing set for both Shrunken Centroids and SVM classifiers for "null" and "non-null" data distributions. We show that using CV to compute an error estimate for a classifier that has itself been tuned using CV gives a significantly biased estimate of the true error. Proper use of CV for estimating true error of a classifier developed using a well defined algorithm requires that all steps of the algorithm, including classifier parameter tuning, be repeated in each CV loop. A nested CV procedure provides an almost unbiased estimate of the true error.

Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells.

PubMed

Masoli, Stefano; Rizza, Martina F; Sgritta, Martina; Van Geit, Werner; Schürmann, Felix; D'Angelo, Egidio

2017-01-01

In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (G i-max ) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of G i-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of G i-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental G i-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.

Selective enhancement of orientation tuning before saccades.

PubMed

Ohl, Sven; Kuper, Clara; Rolfs, Martin

2017-11-01

Saccadic eye movements cause a rapid sweep of the visual image across the retina and bring the saccade's target into high-acuity foveal vision. Even before saccade onset, visual processing is selectively prioritized at the saccade target. To determine how this presaccadic attention shift exerts its influence on visual selection, we compare the dynamics of perceptual tuning curves before movement onset at the saccade target and in the opposite hemifield. Participants monitored a 30-Hz sequence of randomly oriented gratings for a target orientation. Combining a reverse correlation technique previously used to study orientation tuning in neurons and general additive mixed modeling, we found that perceptual reports were tuned to the target orientation. The gain of orientation tuning increased markedly within the last 100 ms before saccade onset. In addition, we observed finer orientation tuning right before saccade onset. This increase in gain and tuning occurred at the saccade target location and was not observed at the incongruent location in the opposite hemifield. The present findings suggest, therefore, that presaccadic attention exerts its influence on vision in a spatially and feature-selective manner, enhancing performance and sharpening feature tuning at the future gaze location before the eyes start moving.

A simple attitude control of quadrotor helicopter based on Ziegler-Nichols rules for tuning PD parameters.

PubMed

He, ZeFang; Zhao, Long

2014-01-01

An attitude control strategy based on Ziegler-Nichols rules for tuning PD (proportional-derivative) parameters of quadrotor helicopters is presented to solve the problem that quadrotor tends to be instable. This problem is caused by the narrow definition domain of attitude angles of quadrotor helicopters. The proposed controller is nonlinear and consists of a linear part and a nonlinear part. The linear part is a PD controller with PD parameters tuned by Ziegler-Nichols rules and acts on the quadrotor decoupled linear system after feedback linearization; the nonlinear part is a feedback linearization item which converts a nonlinear system into a linear system. It can be seen from the simulation results that the attitude controller proposed in this paper is highly robust, and its control effect is better than the other two nonlinear controllers. The nonlinear parts of the other two nonlinear controllers are the same as the attitude controller proposed in this paper. The linear part involves a PID (proportional-integral-derivative) controller with the PID controller parameters tuned by Ziegler-Nichols rules and a PD controller with the PD controller parameters tuned by GA (genetic algorithms). Moreover, this attitude controller is simple and easy to implement.

Self-tuning regulator for an interacting CSTR process

NASA Astrophysics Data System (ADS)

Rajendra Mungale, Niraj; Upadhyay, Akshay; Jaganatha Pandian, B.

2017-11-01

In the paper we have laid emphasis on STR that is Self Tuning Regulator and its application for an interacting process. CSTR has a great importance in Chemical Process when we deal with controlling different parameters of a process using CSTR. Basically CSTR is used to maintain a constant liquid temperature in the process. The proposed method called self-tuning regulator, is a different scheme where process parameters are updated and the controller parameters are obtained from the solution of a design problem. The paper deals with STR and methods associated with it.

Strategy for Developing Expert-System-Based Internet Protocols (TCP/IP)

NASA Technical Reports Server (NTRS)

Ivancic, William D.

1997-01-01

The Satellite Networks and Architectures Branch of NASA's Lewis Research is addressing the issue of seamless interoperability of satellite networks with terrestrial networks. One of the major issues is improving reliable transmission protocols such as TCP over long latency and error-prone links. Many tuning parameters are available to enhance the performance of TCP including segment size, timers and window sizes. There are also numerous congestion avoidance algorithms such as slow start, selective retransmission and selective acknowledgment that are utilized to improve performance. This paper provides a strategy to characterize the performance of TCP relative to various parameter settings in a variety of network environments (i.e. LAN, WAN, wireless, satellite, and IP over ATM). This information can then be utilized to develop expert-system-based Internet protocols.

Natural implementation of neutralino dark matter

NASA Astrophysics Data System (ADS)

King, Steve F.; Roberts, Jonathan P.

2006-09-01

The prediction of neutralino dark matter is generally regarded as one of the successes of the Minimal Supersymmetric Standard Model (MSSM). However the successful regions of parameter space allowed by WMAP and collider constraints are quite restricted. We discuss fine-tuning with respect to both dark matter and Electroweak Symmetry Breaking (EWSB) and explore regions of MSSM parameter space with non-universal gaugino and third family scalar masses in which neutralino dark matter may be implemented naturally. In particular allowing non-universal gauginos opens up the bulk region that allows Bino annihilation via t-channel slepton exchange, leading to ``supernatural dark matter'' corresponding to no fine-tuning at all with respect to dark matter. By contrast we find that the recently proposed ``well tempered neutralino'' regions involve substantial fine-tuning of MSSM parameters in order to satisfy the dark matter constraints, although the fine tuning may be ameliorated if several annihilation channels act simultaneously. Although we have identified regions of ``supernatural dark matter'' in which there is no fine tuning to achieve successful dark matter, the usual MSSM fine tuning to achieve EWSB always remains.

Automatic weight determination in nonlinear model predictive control of wind turbines using swarm optimization technique

NASA Astrophysics Data System (ADS)

Tofighi, Elham; Mahdizadeh, Amin

2016-09-01

This paper addresses the problem of automatic tuning of weighting coefficients for the nonlinear model predictive control (NMPC) of wind turbines. The choice of weighting coefficients in NMPC is critical due to their explicit impact on efficiency of the wind turbine control. Classically, these weights are selected based on intuitive understanding of the system dynamics and control objectives. The empirical methods, however, may not yield optimal solutions especially when the number of parameters to be tuned and the nonlinearity of the system increase. In this paper, the problem of determining weighting coefficients for the cost function of the NMPC controller is formulated as a two-level optimization process in which the upper- level PSO-based optimization computes the weighting coefficients for the lower-level NMPC controller which generates control signals for the wind turbine. The proposed method is implemented to tune the weighting coefficients of a NMPC controller which drives the NREL 5-MW wind turbine. The results are compared with similar simulations for a manually tuned NMPC controller. Comparison verify the improved performance of the controller for weights computed with the PSO-based technique.

PID Tuning Using Extremum Seeking

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

Killingsworth, N; Krstic, M

2005-11-15

Although proportional-integral-derivative (PID) controllers are widely used in the process industry, their effectiveness is often limited due to poor tuning. Manual tuning of PID controllers, which requires optimization of three parameters, is a time-consuming task. To remedy this difficulty, much effort has been invested in developing systematic tuning methods. Many of these methods rely on knowledge of the plant model or require special experiments to identify a suitable plant model. Reviews of these methods are given in [1] and the survey paper [2]. However, in many situations a plant model is not known, and it is not desirable to openmore » the process loop for system identification. Thus a method for tuning PID parameters within a closed-loop setting is advantageous. In relay feedback tuning [3]-[5], the feedback controller is temporarily replaced by a relay. Relay feedback causes most systems to oscillate, thus determining one point on the Nyquist diagram. Based on the location of this point, PID parameters can be chosen to give the closed-loop system a desired phase and gain margin. An alternative tuning method, which does not require either a modification of the system or a system model, is unfalsified control [6], [7]. This method uses input-output data to determine whether a set of PID parameters meets performance specifications. An adaptive algorithm is used to update the PID controller based on whether or not the controller falsifies a given criterion. The method requires a finite set of candidate PID controllers that must be initially specified [6]. Unfalsified control for an infinite set of PID controllers has been developed in [7]; this approach requires a carefully chosen input signal [8]. Yet another model-free PID tuning method that does not require opening of the loop is iterative feedback tuning (IFT). IFT iteratively optimizes the controller parameters with respect to a cost function derived from the output signal of the closed-loop system, see [9]. This method is based on the performance of the closed-loop system during a step response experiment [10], [11]. In this article we present a method for optimizing the step response of a closed-loop system consisting of a PID controller and an unknown plant with a discrete version of extremum seeking (ES). Specifically, ES is used to minimize a cost function similar to that used in [10], [11], which quantifies the performance of the PID controller. ES, a non-model-based method, iteratively modifies the arguments (in this application the PID parameters) of a cost function so that the output of the cost function reaches a local minimum or local maximum. In the next section we apply ES to PID controller tuning. We illustrate this technique through simulations comparing the effectiveness of ES to other PID tuning methods. Next, we address the importance of the choice of cost function and consider the effect of controller saturation. Furthermore, we discuss the choice of ES tuning parameters. Finally, we offer some conclusions.« less

The Magnetically-Tuned Transition-Edge Sensor

NASA Technical Reports Server (NTRS)

Sadleir, John E.; Lee, Sang-Jun; Smith, Stephen J.; Busch, Sarah E.; Bandler, Simon R.; Adams, Joseph S.; Eckart, Megan E.; Chevenak, James A.; Kelley, Richard L.; Kilbourne, Caroline A.;

Objective calibration of regional climate models

NASA Astrophysics Data System (ADS)

Bellprat, O.; Kotlarski, S.; Lüthi, D.; SchäR, C.

2012-12-01

Climate models are subject to high parametric uncertainty induced by poorly confined model parameters of parameterized physical processes. Uncertain model parameters are typically calibrated in order to increase the agreement of the model with available observations. The common practice is to adjust uncertain model parameters manually, often referred to as expert tuning, which lacks objectivity and transparency in the use of observations. These shortcomings often haze model inter-comparisons and hinder the implementation of new model parameterizations. Methods which would allow to systematically calibrate model parameters are unfortunately often not applicable to state-of-the-art climate models, due to computational constraints facing the high dimensionality and non-linearity of the problem. Here we present an approach to objectively calibrate a regional climate model, using reanalysis driven simulations and building upon a quadratic metamodel presented by Neelin et al. (2010) that serves as a computationally cheap surrogate of the model. Five model parameters originating from different parameterizations are selected for the optimization according to their influence on the model performance. The metamodel accurately estimates spatial averages of 2 m temperature, precipitation and total cloud cover, with an uncertainty of similar magnitude as the internal variability of the regional climate model. The non-linearities of the parameter perturbations are well captured, such that only a limited number of 20-50 simulations are needed to estimate optimal parameter settings. Parameter interactions are small, which allows to further reduce the number of simulations. In comparison to an ensemble of the same model which has undergone expert tuning, the calibration yields similar optimal model configurations, but leading to an additional reduction of the model error. The performance range captured is much wider than sampled with the expert-tuned ensemble and the presented methodology is effective and objective. It is argued that objective calibration is an attractive tool and could become standard procedure after introducing new model implementations, or after a spatial transfer of a regional climate model. Objective calibration of parameterizations with regional models could also serve as a strategy toward improving parameterization packages of global climate models.

Optimizing Input/Output Using Adaptive File System Policies

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

Post-LHC7 fine-tuning in the minimal supergravity/CMSSM model with a 125 GeV Higgs boson

NASA Astrophysics Data System (ADS)

Baer, Howard; Barger, Vernon; Huang, Peisi; Mickelson, Dan; Mustafayev, Azar; Tata, Xerxes

2013-02-01

The recent discovery of a 125 GeV Higgs-like resonance at LHC, coupled with the lack of evidence for weak scale supersymmetry (SUSY), has severely constrained SUSY models such as minimal supergravity (mSUGRA)/CMSSM. As LHC probes deeper into SUSY model parameter space, the little hierarchy problem—how to reconcile the Z and Higgs boson mass scale with the scale of SUSY breaking—will become increasingly exacerbated unless a sparticle signal is found. We evaluate two different measures of fine-tuning in the mSUGRA/CMSSM model. The more stringent of these, ΔHS, includes effects that arise from the high-scale origin of the mSUGRA parameters while the second measure, ΔEW, is determined only by weak scale parameters: hence, it is universal to any model with the same particle spectrum and couplings. Our results incorporate the latest constraints from LHC7 sparticle searches, LHCb limits from Bs→μ+μ- and also require a light Higgs scalar with mh˜123-127GeV. We present fine-tuning contours in the m0 vs m1/2 plane for several sets of A0 and tan⁡β values. We also present results for ΔHS and ΔEW from a scan over the entire viable model parameter space. We find a ΔHS≳103, or at best 0.1%, fine-tuning. For the less stringent electroweak fine-tuning, we find ΔEW≳102, or at best 1%, fine-tuning. Two benchmark points are presented that have the lowest values of ΔHS and ΔEW. Our results provide a quantitative measure for ascertaining whether or not the remaining mSUGRA/CMSSM model parameter space is excessively fine-tuned and so could provide impetus for considering alternative SUSY models.

An implicit iterative algorithm with a tuning parameter for Itô Lyapunov matrix equations

NASA Astrophysics Data System (ADS)

Zhang, Ying; Wu, Ai-Guo; Sun, Hui-Jie

2018-01-01

In this paper, an implicit iterative algorithm is proposed for solving a class of Lyapunov matrix equations arising in Itô stochastic linear systems. A tuning parameter is introduced in this algorithm, and thus the convergence rate of the algorithm can be changed. Some conditions are presented such that the developed algorithm is convergent. In addition, an explicit expression is also derived for the optimal tuning parameter, which guarantees that the obtained algorithm achieves its fastest convergence rate. Finally, numerical examples are employed to illustrate the effectiveness of the given algorithm.

A Simple Attitude Control of Quadrotor Helicopter Based on Ziegler-Nichols Rules for Tuning PD Parameters

PubMed Central

He, ZeFang

2014-01-01

An attitude control strategy based on Ziegler-Nichols rules for tuning PD (proportional-derivative) parameters of quadrotor helicopters is presented to solve the problem that quadrotor tends to be instable. This problem is caused by the narrow definition domain of attitude angles of quadrotor helicopters. The proposed controller is nonlinear and consists of a linear part and a nonlinear part. The linear part is a PD controller with PD parameters tuned by Ziegler-Nichols rules and acts on the quadrotor decoupled linear system after feedback linearization; the nonlinear part is a feedback linearization item which converts a nonlinear system into a linear system. It can be seen from the simulation results that the attitude controller proposed in this paper is highly robust, and its control effect is better than the other two nonlinear controllers. The nonlinear parts of the other two nonlinear controllers are the same as the attitude controller proposed in this paper. The linear part involves a PID (proportional-integral-derivative) controller with the PID controller parameters tuned by Ziegler-Nichols rules and a PD controller with the PD controller parameters tuned by GA (genetic algorithms). Moreover, this attitude controller is simple and easy to implement. PMID:25614879

Optimization of enzyme parameters for fermentative production of biorenewable fuels and chemicals

PubMed Central

Jarboe, Laura R.; Liu, Ping; Kautharapu, Kumar Babu; Ingram, Lonnie O.

2012-01-01

Microbial biocatalysts such as Escherichia coli and Saccharomyces cerevisiae have been extensively subjected to Metabolic Engineering for the fermentative production of biorenewable fuels and chemicals. This often entails the introduction of new enzymes, deletion of unwanted enzymes and efforts to fine-tune enzyme abundance in order to attain the desired strain performance. Enzyme performance can be quantitatively described in terms of the Michaelis-Menten type parameters Km, turnover number kcat and Ki, which roughly describe the affinity of an enzyme for its substrate, the speed of a reaction and the enzyme sensitivity to inhibition by regulatory molecules. Here we describe examples of where knowledge of these parameters have been used to select, evolve or engineer enzymes for the desired performance and enabled increased production of biorenewable fuels and chemicals. Examples include production of ethanol, isobutanol, 1-butanol and tyrosine and furfural tolerance. The Michaelis-Menten parameters can also be used to judge the cofactor dependence of enzymes and quantify their preference for NADH or NADPH. Similarly, enzymes can be selected, evolved or engineered for the preferred cofactor preference. Examples of exporter engineering and selection are also discussed in the context of production of malate, valine and limonene. PMID:24688665

Foldover effect and energy output from a nonlinear pseudo-maglev harvester

NASA Astrophysics Data System (ADS)

Kecik, Krzysztof; Mitura, Andrzej; Warminski, Jerzy; Lenci, Stefano

2018-01-01

Dynamics analysis and energy harvesting of a nonlinear magnetic pseudo-levitation (pseudo-maglev) harvester under harmonic excitation is presented in this paper. The system, for selected parameters, has two stable possible solutions with different corresponding energy outputs. The main goal is to analyse the influence of resistance load on the multi-stability zones and energy recovery which can help to tune the system to improve the energy harvesting efficiency.

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

PubMed Central

Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.

2017-01-01

Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines.

PubMed

Teodoro, George; Kurç, Tahsin M; Taveira, Luís F R; Melo, Alba C M A; Gao, Yi; Kong, Jun; Saltz, Joel H

2017-04-01

Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Source code: https://github.com/SBU-BMI/region-templates/ . teodoro@unb.br. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

A parametric model and estimation techniques for the inharmonicity and tuning of the piano.

PubMed

Rigaud, François; David, Bertrand; Daudet, Laurent

2013-05-01

Inharmonicity of piano tones is an essential property of their timbre that strongly influences the tuning, leading to the so-called octave stretching. It is proposed in this paper to jointly model the inharmonicity and tuning of pianos on the whole compass. While using a small number of parameters, these models are able to reflect both the specificities of instrument design and tuner's practice. An estimation algorithm is derived that can run either on a set of isolated note recordings, but also on chord recordings, assuming that the played notes are known. It is applied to extract parameters highlighting some tuner's choices on different piano types and to propose tuning curves for out-of-tune pianos or piano synthesizers.

Software Would Largely Automate Design of Kalman Filter

NASA Technical Reports Server (NTRS)

Chuang, Jason C. H.; Negast, William J.

2005-01-01

Embedded Navigation Filter Automatic Designer (ENFAD) is a computer program being developed to automate the most difficult tasks in designing embedded software to implement a Kalman filter in a navigation system. The most difficult tasks are selection of error states of the filter and tuning of filter parameters, which are timeconsuming trial-and-error tasks that require expertise and rarely yield optimum results. An optimum selection of error states and filter parameters depends on navigation-sensor and vehicle characteristics, and on filter processing time. ENFAD would include a simulation module that would incorporate all possible error states with respect to a given set of vehicle and sensor characteristics. The first of two iterative optimization loops would vary the selection of error states until the best filter performance was achieved in Monte Carlo simulations. For a fixed selection of error states, the second loop would vary the filter parameter values until an optimal performance value was obtained. Design constraints would be satisfied in the optimization loops. Users would supply vehicle and sensor test data that would be used to refine digital models in ENFAD. Filter processing time and filter accuracy would be computed by ENFAD.

A novel auto-tuning PID control mechanism for nonlinear systems.

PubMed

Cetin, Meric; Iplikci, Serdar

2015-09-01

In this paper, a novel Runge-Kutta (RK) discretization-based model-predictive auto-tuning proportional-integral-derivative controller (RK-PID) is introduced for the control of continuous-time nonlinear systems. The parameters of the PID controller are tuned using RK model of the system through prediction error-square minimization where the predicted information of tracking error provides an enhanced tuning of the parameters. Based on the model-predictive control (MPC) approach, the proposed mechanism provides necessary PID parameter adaptations while generating additive correction terms to assist the initially inadequate PID controller. Efficiency of the proposed mechanism has been tested on two experimental real-time systems: an unstable single-input single-output (SISO) nonlinear magnetic-levitation system and a nonlinear multi-input multi-output (MIMO) liquid-level system. RK-PID has been compared to standard PID, standard nonlinear MPC (NMPC), RK-MPC and conventional sliding-mode control (SMC) methods in terms of control performance, robustness, computational complexity and design issue. The proposed mechanism exhibits acceptable tuning and control performance with very small steady-state tracking errors, and provides very short settling time for parameter convergence. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Design of an iterative auto-tuning algorithm for a fuzzy PID controller

NASA Astrophysics Data System (ADS)

Saeed, Bakhtiar I.; Mehrdadi, B.

2012-05-01

Since the first application of fuzzy logic in the field of control engineering, it has been extensively employed in controlling a wide range of applications. The human knowledge on controlling complex and non-linear processes can be incorporated into a controller in the form of linguistic terms. However, with the lack of analytical design study it is becoming more difficult to auto-tune controller parameters. Fuzzy logic controller has several parameters that can be adjusted, such as: membership functions, rule-base and scaling gains. Furthermore, it is not always easy to find the relation between the type of membership functions or rule-base and the controller performance. This study proposes a new systematic auto-tuning algorithm to fine tune fuzzy logic controller gains. A fuzzy PID controller is proposed and applied to several second order systems. The relationship between the closed-loop response and the controller parameters is analysed to devise an auto-tuning method. The results show that the proposed method is highly effective and produces zero overshoot with enhanced transient response. In addition, the robustness of the controller is investigated in the case of parameter changes and the results show a satisfactory performance.

New bandwidth selection criterion for Kernel PCA: approach to dimensionality reduction and classification problems.

PubMed

Thomas, Minta; De Brabanter, Kris; De Moor, Bart

2014-05-10

DNA microarrays are potentially powerful technology for improving diagnostic classification, treatment selection, and prognostic assessment. The use of this technology to predict cancer outcome has a history of almost a decade. Disease class predictors can be designed for known disease cases and provide diagnostic confirmation or clarify abnormal cases. The main input to this class predictors are high dimensional data with many variables and few observations. Dimensionality reduction of these features set significantly speeds up the prediction task. Feature selection and feature transformation methods are well known preprocessing steps in the field of bioinformatics. Several prediction tools are available based on these techniques. Studies show that a well tuned Kernel PCA (KPCA) is an efficient preprocessing step for dimensionality reduction, but the available bandwidth selection method for KPCA was computationally expensive. In this paper, we propose a new data-driven bandwidth selection criterion for KPCA, which is related to least squares cross-validation for kernel density estimation. We propose a new prediction model with a well tuned KPCA and Least Squares Support Vector Machine (LS-SVM). We estimate the accuracy of the newly proposed model based on 9 case studies. Then, we compare its performances (in terms of test set Area Under the ROC Curve (AUC) and computational time) with other well known techniques such as whole data set + LS-SVM, PCA + LS-SVM, t-test + LS-SVM, Prediction Analysis of Microarrays (PAM) and Least Absolute Shrinkage and Selection Operator (Lasso). Finally, we assess the performance of the proposed strategy with an existing KPCA parameter tuning algorithm by means of two additional case studies. We propose, evaluate, and compare several mathematical/statistical techniques, which apply feature transformation/selection for subsequent classification, and consider its application in medical diagnostics. Both feature selection and feature transformation perform well on classification tasks. Due to the dynamic selection property of feature selection, it is hard to define significant features for the classifier, which predicts classes of future samples. Moreover, the proposed strategy enjoys a distinctive advantage with its relatively lesser time complexity.

Auditory steady-state evoked potentials vs. compound action potentials for the measurement of suppression tuning curves in the sedated dog puppy.

PubMed

Markessis, Emily; Poncelet, Luc; Colin, Cécile; Hoonhorst, Ingrid; Collet, Grégory; Deltenre, Paul; Moore, Brian C J

2010-06-01

Auditory steady-state evoked potential (ASSEP) tuning curves were compared to compound action potential (CAP) tuning curves, both measured at 2 Hz, using sedated beagle puppies. The effect of two types of masker (narrowband noise and sinusoidal) on the tuning curve parameters was assessed. Whatever the masker type, CAP tuning curve parameters were qualitatively and quantitatively similar to the ASSEP ones, with a similar inter-subject variability, but with a greater incidence of upward tip displacement. Whatever the procedure, sinusoidal maskers produced sharper tuning curves than narrow-band maskers. Although these differences are not likely to have significant implications for clinical work, from a fundamental point of view, their origin requires further investigations. The same amount of time was needed to record a CAP and an ASSEP 13-point tuning curve. The data further validate the ASSEP technique, which has the advantages of having a smaller tendency to produce upward tip shifts than the CAP technique. Moreover, being non invasive, ASSEP tuning curves can be easily repeated over time in the same subject for clinical and research purposes.

Beam energy tracking system on Optima XEx high energy ion implanter

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

David, Jonathan; Satoh, Shu; Wu Xiangyang

2012-11-06

The Axcelis Optima XEx high energy implanter is an RF linac-based implanter with 12 RF resonators for beam acceleration. Even though each acceleration field is an alternating, sinusoidal RF field, the well known phase-focusing principle produces a beam with a sharp quasi-monoenergetic energy spectrum. A magnetic energy filter after the linac further attenuates the low energy continuum in the energy spectrum often associated with RF acceleration. The final beam energy is a function of the phase and amplitude of the 12 resonators in the linac. When tuning a beam, the magnetic energy filter is set to the desired energy, andmore » each linac parameter is tuned to maximize the transmission through the filter. Once a beam is set up, all the parameters are stored in a recipe, which can be easily tuned and has proven to be quite repeatable. The magnetic field setting of the energy filter selects the beam energy from the RF Linac accelerator, and in-situ verification of beam energy in addition to the magnetic energy filter setting has long been desired. An independent energy tracking system was developed for this purpose, using the existing electrostatic beam scanner as a deflector to construct an in-situ electrostatic energy analyzer. This paper will describe the system and performance of the beam energy tracking system.« less

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

PubMed Central

Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package “DensParcorr” can be downloaded from CRAN for implementing the proposed statistical methods. PMID:27242395

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

PubMed

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package "DensParcorr" can be downloaded from CRAN for implementing the proposed statistical methods.

Kernel learning at the first level of inference.

PubMed

Cawley, Gavin C; Talbot, Nicola L C

2014-05-01

Kernel learning methods, whether Bayesian or frequentist, typically involve multiple levels of inference, with the coefficients of the kernel expansion being determined at the first level and the kernel and regularisation parameters carefully tuned at the second level, a process known as model selection. Model selection for kernel machines is commonly performed via optimisation of a suitable model selection criterion, often based on cross-validation or theoretical performance bounds. However, if there are a large number of kernel parameters, as for instance in the case of automatic relevance determination (ARD), there is a substantial risk of over-fitting the model selection criterion, resulting in poor generalisation performance. In this paper we investigate the possibility of learning the kernel, for the Least-Squares Support Vector Machine (LS-SVM) classifier, at the first level of inference, i.e. parameter optimisation. The kernel parameters and the coefficients of the kernel expansion are jointly optimised at the first level of inference, minimising a training criterion with an additional regularisation term acting on the kernel parameters. The key advantage of this approach is that the values of only two regularisation parameters need be determined in model selection, substantially alleviating the problem of over-fitting the model selection criterion. The benefits of this approach are demonstrated using a suite of synthetic and real-world binary classification benchmark problems, where kernel learning at the first level of inference is shown to be statistically superior to the conventional approach, improves on our previous work (Cawley and Talbot, 2007) and is competitive with Multiple Kernel Learning approaches, but with reduced computational expense. Copyright © 2014 Elsevier Ltd. All rights reserved.

Genomic data assimilation for estimating hybrid functional Petri net from time-course gene expression data.

PubMed

Nagasaki, Masao; Yamaguchi, Rui; Yoshida, Ryo; Imoto, Seiya; Doi, Atsushi; Tamada, Yoshinori; Matsuno, Hiroshi; Miyano, Satoru; Higuchi, Tomoyuki

2006-01-01

We propose an automatic construction method of the hybrid functional Petri net as a simulation model of biological pathways. The problems we consider are how we choose the values of parameters and how we set the network structure. Usually, we tune these unknown factors empirically so that the simulation results are consistent with biological knowledge. Obviously, this approach has the limitation in the size of network of interest. To extend the capability of the simulation model, we propose the use of data assimilation approach that was originally established in the field of geophysical simulation science. We provide genomic data assimilation framework that establishes a link between our simulation model and observed data like microarray gene expression data by using a nonlinear state space model. A key idea of our genomic data assimilation is that the unknown parameters in simulation model are converted as the parameter of the state space model and the estimates are obtained as the maximum a posteriori estimators. In the parameter estimation process, the simulation model is used to generate the system model in the state space model. Such a formulation enables us to handle both the model construction and the parameter tuning within a framework of the Bayesian statistical inferences. In particular, the Bayesian approach provides us a way of controlling overfitting during the parameter estimations that is essential for constructing a reliable biological pathway. We demonstrate the effectiveness of our approach using synthetic data. As a result, parameter estimation using genomic data assimilation works very well and the network structure is suitably selected.

Parallel optimization of signal detection in active magnetospheric signal injection experiments

NASA Astrophysics Data System (ADS)

Gowanlock, Michael; Li, Justin D.; Rude, Cody M.; Pankratius, Victor

2018-05-01

Signal detection and extraction requires substantial manual parameter tuning at different stages in the processing pipeline. Time-series data depends on domain-specific signal properties, necessitating unique parameter selection for a given problem. The large potential search space makes this parameter selection process time-consuming and subject to variability. We introduce a technique to search and prune such parameter search spaces in parallel and select parameters for time series filters using breadth- and depth-first search strategies to increase the likelihood of detecting signals of interest in the field of magnetospheric physics. We focus on studying geomagnetic activity in the extremely and very low frequency ranges (ELF/VLF) using ELF/VLF transmissions from Siple Station, Antarctica, received at Québec, Canada. Our technique successfully detects amplified transmissions and achieves substantial speedup performance gains as compared to an exhaustive parameter search. We present examples where our algorithmic approach reduces the search from hundreds of seconds down to less than 1 s, with a ranked signal detection in the top 99th percentile, thus making it valuable for real-time monitoring. We also present empirical performance models quantifying the trade-off between the quality of signal recovered and the algorithm response time required for signal extraction. In the future, improved signal extraction in scenarios like the Siple experiment will enable better real-time diagnostics of conditions of the Earth's magnetosphere for monitoring space weather activity.

Microwave Characterization of the GaAs MESFET and Development of a Low Noise Microwave Amplifier.

DTIC Science & Technology

1979-12-01

investigation. Comparison of measured scattering parameters with those predicted by this model pro - vide a useful check for the validity of the model. B. Device...tuning co-nditions can be changed and their effects measured without changing the setup con - figuration. Gain or noise figure measurements are selected by...lines. The coaxial sections then transition to precision, sexless 7 mm (type APC-7) con - nectors, which provide highly repeatable connections, and a

Dream controller

DOEpatents

Cheng, George Shu-Xing; Mulkey, Steven L; Wang, Qiang; Chow, Andrew J

2013-11-26

A method and apparatus for intelligently controlling continuous process variables. A Dream Controller comprises an Intelligent Engine mechanism and a number of Model-Free Adaptive (MFA) controllers, each of which is suitable to control a process with specific behaviors. The Intelligent Engine can automatically select the appropriate MFA controller and its parameters so that the Dream Controller can be easily used by people with limited control experience and those who do not have the time to commission, tune, and maintain automatic controllers.

Otoacoustic Estimates of Cochlear Tuning: Testing Predictions in Macaque

NASA Astrophysics Data System (ADS)

Shera, Christopher A.; Bergevin, Christopher; Kalluri, Radha; Mc Laughlin, Myles; Michelet, Pascal; van der Heijden, Marcel; Joris, Philip X.

2011-11-01

Otoacoustic estimates of cochlear frequency selectivity suggest substantially sharper tuning in humans. However, the logic and methodology underlying these estimates remain untested by direct measurements in primates. We report measurements of frequency tuning in macaque monkeys, Old-World primates phylogenetically closer to humans than the small laboratory animals often taken as models of human hearing (e.g., cats, guinea pigs, and chinchillas). We find that measurements of tuning obtained directly from individual nerve fibers and indirectly using otoacoustic emissions both indicate that peripheral frequency selectivity in macaques is significantly sharper than in small laboratory animals, matching that inferred for humans at high frequencies. Our results validate the use of otoacoustic emissions for noninvasive measurement of cochlear tuning and corroborate the finding of sharper tuning in humans.

Decoding the non-stationary neuron spike trains by dual Monte Carlo point process estimation in motor Brain Machine Interfaces.

PubMed

Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang

2014-01-01

Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.

Taming parallel I/O complexity with auto-tuning

DOE PAGES

Behzad, Babak; Luu, Huong Vu Thanh; Huchette, Joseph; ...

2013-11-17

We present an auto-tuning system for optimizing I/O performance of HDF5 applications and demonstrate its value across platforms, applications, and at scale. The system uses a genetic algorithm to search a large space of tunable parameters and to identify effective settings at all layers of the parallel I/O stack. The parameter settings are applied transparently by the auto-tuning system via dynamically intercepted HDF5 calls. To validate our auto-tuning system, we applied it to three I/O benchmarks (VPIC, VORPAL, and GCRM) that replicate the I/O activity of their respective applications. We tested the system with different weak-scaling configurations (128, 2048, andmore » 4096 CPU cores) that generate 30 GB to 1 TB of data, and executed these configurations on diverse HPC platforms (Cray XE6, IBM BG/P, and Dell Cluster). In all cases, the auto-tuning framework identified tunable parameters that substantially improved write performance over default system settings. In conclusion, we consistently demonstrate I/O write speedups between 2x and 100x for test configurations.« less

An algorithm for the design and tuning of RF accelerating structures with variable cell lengths

NASA Astrophysics Data System (ADS)

Lal, Shankar; Pant, K. K.

2018-05-01

An algorithm is proposed for the design of a π mode standing wave buncher structure with variable cell lengths. It employs a two-parameter, multi-step approach for the design of the structure with desired resonant frequency and field flatness. The algorithm, along with analytical scaling laws for the design of the RF power coupling slot, makes it possible to accurately design the structure employing a freely available electromagnetic code like SUPERFISH. To compensate for machining errors, a tuning method has been devised to achieve desired RF parameters for the structure, which has been qualified by the successful tuning of a 7-cell buncher to π mode frequency of 2856 MHz with field flatness <3% and RF coupling coefficient close to unity. The proposed design algorithm and tuning method have demonstrated the feasibility of developing an S-band accelerating structure for desired RF parameters with a relatively relaxed machining tolerance of ∼ 25 μm. This paper discusses the algorithm for the design and tuning of an RF accelerating structure with variable cell lengths.

Flying and swimming animals cruise at a Strouhal number tuned for high power efficiency.

PubMed

Taylor, Graham K; Nudds, Robert L; Thomas, Adrian L R

2003-10-16

Dimensionless numbers are important in biomechanics because their constancy can imply dynamic similarity between systems, despite possible differences in medium or scale. A dimensionless parameter that describes the tail or wing kinematics of swimming and flying animals is the Strouhal number, St = fA/U, which divides stroke frequency (f) and amplitude (A) by forward speed (U). St is known to govern a well-defined series of vortex growth and shedding regimes for airfoils undergoing pitching and heaving motions. Propulsive efficiency is high over a narrow range of St and usually peaks within the interval 0.2 < St < 0.4 (refs 3-8). Because natural selection is likely to tune animals for high propulsive efficiency, we expect it to constrain the range of St that animals use. This seems to be true for dolphins, sharks and bony fish, which swim at 0.2 < St < 0.4. Here we show that birds, bats and insects also converge on the same narrow range of St, but only when cruising. Tuning cruise kinematics to optimize St therefore seems to be a general principle of oscillatory lift-based propulsion.

Continuous Firefly Algorithm for Optimal Tuning of Pid Controller in Avr System

NASA Astrophysics Data System (ADS)

Bendjeghaba, Omar

2014-01-01

This paper presents a tuning approach based on Continuous firefly algorithm (CFA) to obtain the proportional-integral- derivative (PID) controller parameters in Automatic Voltage Regulator system (AVR). In the tuning processes the CFA is iterated to reach the optimal or the near optimal of PID controller parameters when the main goal is to improve the AVR step response characteristics. Conducted simulations show the effectiveness and the efficiency of the proposed approach. Furthermore the proposed approach can improve the dynamic of the AVR system. Compared with particle swarm optimization (PSO), the new CFA tuning method has better control system performance in terms of time domain specifications and set-point tracking.

Online automatic tuning and control for fed-batch cultivation

PubMed Central

van Straten, Gerrit; van der Pol, Leo A.; van Boxtel, Anton J. B.

2007-01-01

Performance of controllers applied in biotechnological production is often below expectation. Online automatic tuning has the capability to improve control performance by adjusting control parameters. This work presents automatic tuning approaches for model reference specific growth rate control during fed-batch cultivation. The approaches are direct methods that use the error between observed specific growth rate and its set point; systematic perturbations of the cultivation are not necessary. Two automatic tuning methods proved to be efficient, in which the adaptation rate is based on a combination of the error, squared error and integral error. These methods are relatively simple and robust against disturbances, parameter uncertainties, and initialization errors. Application of the specific growth rate controller yields a stable system. The controller and automatic tuning methods are qualified by simulations and laboratory experiments with Bordetella pertussis. PMID:18157554

Tuning to optimize SVM approach for assisting ovarian cancer diagnosis with photoacoustic imaging.

PubMed

Wang, Rui; Li, Rui; Lei, Yanyan; Zhu, Quing

2015-01-01

Support vector machine (SVM) is one of the most effective classification methods for cancer detection. The efficiency and quality of a SVM classifier depends strongly on several important features and a set of proper parameters. Here, a series of classification analyses, with one set of photoacoustic data from ovarian tissues ex vivo and a widely used breast cancer dataset- the Wisconsin Diagnostic Breast Cancer (WDBC), revealed the different accuracy of a SVM classification in terms of the number of features used and the parameters selected. A pattern recognition system is proposed by means of SVM-Recursive Feature Elimination (RFE) with the Radial Basis Function (RBF) kernel. To improve the effectiveness and robustness of the system, an optimized tuning ensemble algorithm called as SVM-RFE(C) with correlation filter was implemented to quantify feature and parameter information based on cross validation. The proposed algorithm is first demonstrated outperforming SVM-RFE on WDBC. Then the best accuracy of 94.643% and sensitivity of 94.595% were achieved when using SVM-RFE(C) to test 57 new PAT data from 19 patients. The experiment results show that the classifier constructed with SVM-RFE(C) algorithm is able to learn additional information from new data and has significant potential in ovarian cancer diagnosis.

Mode selection and frequency tuning by injection in pulsed TEA-CO2 lasers

NASA Technical Reports Server (NTRS)

Flamant, P. H.; Menzies, R. T.

1983-01-01

An analytical model characterizing pulsed-TEA-CO2-laser injection locking by tunable CW-laser radiation is presented and used to explore the requirements for SLM pulse generation. Photon-density-rate equations describing the laser mechanism are analyzed in terms of the mode competition between photon densities emitted at two frequencies. The expression derived for pulsed dye lasers is extended to homogeneously broadened CO2 lasers, and locking time is defined as a function of laser parameters. The extent to which injected radiation can be detuned from the CO2 line center and continue to produce SLM pulses is investigated experimentally in terms of the analytical framework. The dependence of locking time on the detuning/pressure-broadened-halfwidth ratio is seen as important for spectroscopic applications requiring tuning within the TEA-laser line-gain bandwidth.

Tuning without over-tuning: parametric uncertainty quantification for the NEMO ocean model

NASA Astrophysics Data System (ADS)

Williamson, Daniel B.; Blaker, Adam T.; Sinha, Bablu

2017-04-01

In this paper we discuss climate model tuning and present an iterative automatic tuning method from the statistical science literature. The method, which we refer to here as iterative refocussing (though also known as history matching), avoids many of the common pitfalls of automatic tuning procedures that are based on optimisation of a cost function, principally the over-tuning of a climate model due to using only partial observations. This avoidance comes by seeking to rule out parameter choices that we are confident could not reproduce the observations, rather than seeking the model that is closest to them (a procedure that risks over-tuning). We comment on the state of climate model tuning and illustrate our approach through three waves of iterative refocussing of the NEMO (Nucleus for European Modelling of the Ocean) ORCA2 global ocean model run at 2° resolution. We show how at certain depths the anomalies of global mean temperature and salinity in a standard configuration of the model exceeds 10 standard deviations away from observations and show the extent to which this can be alleviated by iterative refocussing without compromising model performance spatially. We show how model improvements can be achieved by simultaneously perturbing multiple parameters, and illustrate the potential of using low-resolution ensembles to tune NEMO ORCA configurations at higher resolutions.

Analysis of tuning methods in semiconductor frequency-selective surfaces

NASA Astrophysics Data System (ADS)

Shemelya, Corey; Palm, Dominic; Fip, Tassilo; Rahm, Marco

2017-02-01

Advanced technology, such as sensing and communication equipment, has recently begun to combine optically sensitive nano-scale structures with customizable semiconductor material systems. Included within this broad field of study is the aptly named frequency-selective surface; which is unique in that it can be artificially designed to produce a specific electromagnetic or optical response. With the inherent utility of a frequency-selective surface, there has been an increased interest in the area of dynamic frequency-selective surfaces, which can be altered through optical or electrical tuning. This area has had exciting break throughs as tuning methods have evolved; however, these methods are typically energy intensive (optical tuning) or have met with limited success (electrical tuning). As such, this work investigates multiple structures and processes which implement semiconductor electrical biasing and/or optical tuning. Within this study are surfaces ranging from transmission meta-structures to metamaterial surface-waves and the associated coupling schemes. This work shows the utility of each design, while highlighting potential methods for optimizing dynamic meta-surfaces. As an added constraint, the structures were also designed to operate in unison with a state-of-the-art Ti:Sapphire Spitfire Ace and Spitfire Ace PA dual system (12 Watt) with pulse front matching THz generation and an EOS detection system. Additionally, the Ti:Sapphire laser system would provide the means for optical tunablity, while electrical tuning can be obtained through external power supplies.

Self-tuning bistable parametric feedback oscillator: Near-optimal amplitude maximization without model information

NASA Astrophysics Data System (ADS)

Braun, David J.; Sutas, Andrius; Vijayakumar, Sethu

2017-01-01

Theory predicts that parametrically excited oscillators, tuned to operate under resonant condition, are capable of large-amplitude oscillation useful in diverse applications, such as signal amplification, communication, and analog computation. However, due to amplitude saturation caused by nonlinearity, lack of robustness to model uncertainty, and limited sensitivity to parameter modulation, these oscillators require fine-tuning and strong modulation to generate robust large-amplitude oscillation. Here we present a principle of self-tuning parametric feedback excitation that alleviates the above-mentioned limitations. This is achieved using a minimalistic control implementation that performs (i) self-tuning (slow parameter adaptation) and (ii) feedback pumping (fast parameter modulation), without sophisticated signal processing past observations. The proposed approach provides near-optimal amplitude maximization without requiring model-based control computation, previously perceived inevitable to implement optimal control principles in practical application. Experimental implementation of the theory shows that the oscillator self-tunes itself near to the onset of dynamic bifurcation to achieve extreme sensitivity to small resonant parametric perturbations. As a result, it achieves large-amplitude oscillations by capitalizing on the effect of nonlinearity, despite substantial model uncertainties and strong unforeseen external perturbations. We envision the present finding to provide an effective and robust approach to parametric excitation when it comes to real-world application.

Stay tuned: active amplification tunes tree cricket ears to track temperature-dependent song frequency.

PubMed

Mhatre, Natasha; Pollack, Gerald; Mason, Andrew

2016-04-01

Tree cricket males produce tonal songs, used for mate attraction and male-male interactions. Active mechanics tunes hearing to conspecific song frequency. However, tree cricket song frequency increases with temperature, presenting a problem for tuned listeners. We show that the actively amplified frequency increases with temperature, thus shifting mechanical and neuronal auditory tuning to maintain a match with conspecific song frequency. Active auditory processes are known from several taxa, but their adaptive function has rarely been demonstrated. We show that tree crickets harness active processes to ensure that auditory tuning remains matched to conspecific song frequency, despite changing environmental conditions and signal characteristics. Adaptive tuning allows tree crickets to selectively detect potential mates or rivals over large distances and is likely to bestow a strong selective advantage by reducing mate-finding effort and facilitating intermale interactions. © 2016 The Author(s).

Evaluation and benchmarking of an EC-QCL-based mid-infrared spectrometer for monitoring metabolic blood parameters in critical care units

NASA Astrophysics Data System (ADS)

Grafen, M.; Delbeck, S.; Busch, H.; Heise, H. M.; Ostendorf, A.

2018-02-01

Mid-infrared spectroscopy hyphenated with micro-dialysis is an excellent method for monitoring metabolic blood parameters as it enables the concurrent, reagent-free and precise measurement of multiple clinically relevant substances such as glucose, lactate and urea in micro-dialysates of blood or interstitial fluid. For a marketable implementation, quantum cascade lasers (QCL) seem to represent a favourable technology due to their high degree of miniaturization and potentially low production costs. In this work, an external cavity (EC) - QCL-based spectrometer and two Fourier-transform infrared (FTIR) spectrometers were benchmarked with regard to the precision, accuracy and long-term stability needed for the monitoring of critically ill patients. For the tests, ternary aqueous solutions of glucose, lactate and mannitol (the latter for dialysis recovery determination) were measured in custom-made flow-through transmission cells of different pathlengths and analyzed by Partial Least Squares calibration models. It was revealed, that the wavenumber tuning speed of the QCL had a severe impact on the EC-mirror trajectory due to matching the digital-analog-converter step frequency with the mechanical resonance frequency of the mirror actuation. By selecting an appropriate tuning speed, the mirror oscillations acted as a hardware smoothing filter for the significant intensity variations caused by mode hopping. Besides the tuning speed, the effects of averaging over multiple spectra and software smoothing parameters (Savitzky-Golay-filters and FT-smoothing) were investigated. The final settings led to a performance of the QCL-system, which was comparable with a research FTIR-spectrometer and even surpassed the performance of a small FTIR-mini-spectrometer.

Advanced membrane electrode assemblies for fuel cells

DOEpatents

Kim, Yu Seung; Pivovar, Bryan S.

2012-07-24

A method of preparing advanced membrane electrode assemblies (MEA) for use in fuel cells. A base polymer is selected for a base membrane. An electrode composition is selected to optimize properties exhibited by the membrane electrode assembly based on the selection of the base polymer. A property-tuning coating layer composition is selected based on compatibility with the base polymer and the electrode composition. A solvent is selected based on the interaction of the solvent with the base polymer and the property-tuning coating layer composition. The MEA is assembled by preparing the base membrane and then applying the property-tuning coating layer to form a composite membrane. Finally, a catalyst is applied to the composite membrane.

Advanced membrane electrode assemblies for fuel cells

DOEpatents

Kim, Yu Seung; Pivovar, Bryan S

2014-02-25

A method of preparing advanced membrane electrode assemblies (MEA) for use in fuel cells. A base polymer is selected for a base membrane. An electrode composition is selected to optimize properties exhibited by the membrane electrode assembly based on the selection of the base polymer. A property-tuning coating layer composition is selected based on compatibility with the base polymer and the electrode composition. A solvent is selected based on the interaction of the solvent with the base polymer and the property-tuning coating layer composition. The MEA is assembled by preparing the base membrane and then applying the property-tuning coating layer to form a composite membrane. Finally, a catalyst is applied to the composite membrane.

Attention selectively modifies the representation of individual faces in the human brain

PubMed Central

Gratton, Caterina; Sreenivasan, Kartik K.; Silver, Michael A.; D’Esposito, Mark

2013-01-01

Attention modifies neural tuning for low-level features, but it is unclear how attention influences tuning for complex stimuli. We investigated this question in humans using fMRI and face stimuli. Participants were shown six faces (F1-F6) along a morph continuum, and selectivity was quantified by constructing tuning curves for individual voxels. Face-selective voxels exhibited greater responses to their preferred face than to non-preferred faces, particularly in posterior face areas. Anterior face areas instead displayed tuning for face categories: voxels in these areas preferred either the first (F1-F3) or second (F4-F6) half of the morph continuum. Next, we examined the effects of attention on voxel tuning by having subjects direct attention to one of the superimposed images of F1 and F6. We found that attention selectively enhanced responses in voxels preferring the attended face. Taken together, our results demonstrate that single voxels carry information about individual faces and that the nature of this information varies across cortical face areas. Additionally, we found that attention selectively enhances these representations. Our findings suggest that attention may act via a unitary principle of selective enhancement of responses to both simple and complex stimuli across multiple stages of the visual hierarchy. PMID:23595755

Robust fixed-time synchronization of delayed Cohen-Grossberg neural networks.

PubMed

Wan, Ying; Cao, Jinde; Wen, Guanghui; Yu, Wenwu

2016-01-01

The fixed-time master-slave synchronization of Cohen-Grossberg neural networks with parameter uncertainties and time-varying delays is investigated. Compared with finite-time synchronization where the convergence time relies on the initial synchronization errors, the settling time of fixed-time synchronization can be adjusted to desired values regardless of initial conditions. Novel synchronization control strategy for the slave neural network is proposed. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, some sufficient schemes are provided for selecting the control parameters to ensure synchronization with required convergence time and in the presence of parameter uncertainties. Corresponding criteria for tuning control inputs are also derived for the finite-time synchronization. Finally, two numerical examples are given to illustrate the validity of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

On the effect of response transformations in sequential parameter optimization.

PubMed

Wagner, Tobias; Wessing, Simon

2012-01-01

Parameter tuning of evolutionary algorithms (EAs) is attracting more and more interest. In particular, the sequential parameter optimization (SPO) framework for the model-assisted tuning of stochastic optimizers has resulted in established parameter tuning algorithms. In this paper, we enhance the SPO framework by introducing transformation steps before the response aggregation and before the actual modeling. Based on design-of-experiments techniques, we empirically analyze the effect of integrating different transformations. We show that in particular, a rank transformation of the responses provides significant improvements. A deeper analysis of the resulting models and additional experiments with adaptive procedures indicates that the rank and the Box-Cox transformation are able to improve the properties of the resultant distributions with respect to symmetry and normality of the residuals. Moreover, model-based effect plots document a higher discriminatory power obtained by the rank transformation.

Synaptic Basis for Differential Orientation Selectivity between Complex and Simple Cells in Mouse Visual Cortex

PubMed Central

Li, Ya-tang; Liu, Bao-hua; Chou, Xiao-lin; Zhang, Li I.

2015-01-01

In the primary visual cortex (V1), orientation-selective neurons can be categorized into simple and complex cells primarily based on their receptive field (RF) structures. In mouse V1, although previous studies have examined the excitatory/inhibitory interplay underlying orientation selectivity (OS) of simple cells, the synaptic bases for that of complex cells have remained obscure. Here, by combining in vivo loose-patch and whole-cell recordings, we found that complex cells, identified by their overlapping on/off subfields, had significantly weaker OS than simple cells at both spiking and subthreshold membrane potential response levels. Voltage-clamp recordings further revealed that although excitatory inputs to complex and simple cells exhibited a similar degree of OS, inhibition in complex cells was more narrowly tuned than excitation, whereas in simple cells inhibition was more broadly tuned than excitation. The differential inhibitory tuning can primarily account for the difference in OS between complex and simple cells. Interestingly, the differential synaptic tuning correlated well with the spatial organization of synaptic input: the inhibitory visual RF in complex cells was more elongated in shape than its excitatory counterpart and also was more elongated than that in simple cells. Together, our results demonstrate that OS of complex and simple cells is differentially shaped by cortical inhibition based on its orientation tuning profile relative to excitation, which is contributed at least partially by the spatial organization of RFs of presynaptic inhibitory neurons. SIGNIFICANCE STATEMENT Simple and complex cells, two classes of principal neurons in the primary visual cortex (V1), are generally thought to be equally selective for orientation. In mouse V1, we report that complex cells, identified by their overlapping on/off subfields, has significantly weaker orientation selectivity (OS) than simple cells. This can be primarily attributed to the differential tuning selectivity of inhibitory synaptic input: inhibition in complex cells is more narrowly tuned than excitation, whereas in simple cells inhibition is more broadly tuned than excitation. In addition, there is a good correlation between inhibitory tuning selectivity and the spatial organization of inhibitory inputs. These complex and simple cells with differential degree of OS may provide functionally distinct signals to different downstream targets. PMID:26245969

Synaptic Basis for Differential Orientation Selectivity between Complex and Simple Cells in Mouse Visual Cortex.

PubMed

Li, Ya-tang; Liu, Bao-hua; Chou, Xiao-lin; Zhang, Li I; Tao, Huizhong W

2015-08-05

In the primary visual cortex (V1), orientation-selective neurons can be categorized into simple and complex cells primarily based on their receptive field (RF) structures. In mouse V1, although previous studies have examined the excitatory/inhibitory interplay underlying orientation selectivity (OS) of simple cells, the synaptic bases for that of complex cells have remained obscure. Here, by combining in vivo loose-patch and whole-cell recordings, we found that complex cells, identified by their overlapping on/off subfields, had significantly weaker OS than simple cells at both spiking and subthreshold membrane potential response levels. Voltage-clamp recordings further revealed that although excitatory inputs to complex and simple cells exhibited a similar degree of OS, inhibition in complex cells was more narrowly tuned than excitation, whereas in simple cells inhibition was more broadly tuned than excitation. The differential inhibitory tuning can primarily account for the difference in OS between complex and simple cells. Interestingly, the differential synaptic tuning correlated well with the spatial organization of synaptic input: the inhibitory visual RF in complex cells was more elongated in shape than its excitatory counterpart and also was more elongated than that in simple cells. Together, our results demonstrate that OS of complex and simple cells is differentially shaped by cortical inhibition based on its orientation tuning profile relative to excitation, which is contributed at least partially by the spatial organization of RFs of presynaptic inhibitory neurons. Simple and complex cells, two classes of principal neurons in the primary visual cortex (V1), are generally thought to be equally selective for orientation. In mouse V1, we report that complex cells, identified by their overlapping on/off subfields, has significantly weaker orientation selectivity (OS) than simple cells. This can be primarily attributed to the differential tuning selectivity of inhibitory synaptic input: inhibition in complex cells is more narrowly tuned than excitation, whereas in simple cells inhibition is more broadly tuned than excitation. In addition, there is a good correlation between inhibitory tuning selectivity and the spatial organization of inhibitory inputs. These complex and simple cells with differential degree of OS may provide functionally distinct signals to different downstream targets. Copyright © 2015 the authors 0270-6474/15/3511081-13$15.00/0.

Tuning In to Sound: Frequency-Selective Attentional Filter in Human Primary Auditory Cortex

PubMed Central

Da Costa, Sandra; van der Zwaag, Wietske; Miller, Lee M.; Clarke, Stephanie

2013-01-01

Cocktail parties, busy streets, and other noisy environments pose a difficult challenge to the auditory system: how to focus attention on selected sounds while ignoring others? Neurons of primary auditory cortex, many of which are sharply tuned to sound frequency, could help solve this problem by filtering selected sound information based on frequency-content. To investigate whether this occurs, we used high-resolution fMRI at 7 tesla to map the fine-scale frequency-tuning (1.5 mm isotropic resolution) of primary auditory areas A1 and R in six human participants. Then, in a selective attention experiment, participants heard low (250 Hz)- and high (4000 Hz)-frequency streams of tones presented at the same time (dual-stream) and were instructed to focus attention onto one stream versus the other, switching back and forth every 30 s. Attention to low-frequency tones enhanced neural responses within low-frequency-tuned voxels relative to high, and when attention switched the pattern quickly reversed. Thus, like a radio, human primary auditory cortex is able to tune into attended frequency channels and can switch channels on demand. PMID:23365225

Fuzzy logic controllers for electrotechnical devices - On-site tuning approach

NASA Astrophysics Data System (ADS)

Hissel, D.; Maussion, P.; Faucher, J.

2001-12-01

Fuzzy logic offers nowadays an interesting alternative to the designers of non linear control laws for electrical or electromechanical systems. However, due to the huge number of tuning parameters, this kind of control is only used in a few industrial applications. This paper proposes a new, very simple, on-site tuning strategy for a PID-like fuzzy logic controller. Thanks to the experimental designs methodology, we will propose sets of optimized pre-established settings for this kind of fuzzy controllers. The proposed parameters are only depending on one on-site open-loop identification test. In this way, this on-site tuning methodology has to be compared to the Ziegler-Nichols one's for conventional controllers. Experimental results (on a permanent magnets synchronous motor and on a DC/DC converter) will underline all the efficiency of this tuning methodology. Finally, the field of validity of the proposed pre-established settings will be given.

PID controller tuning using metaheuristic optimization algorithms for benchmark problems

NASA Astrophysics Data System (ADS)

Gholap, Vishal; Naik Dessai, Chaitali; Bagyaveereswaran, V.

2017-11-01

This paper contributes to find the optimal PID controller parameters using particle swarm optimization (PSO), Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm. The algorithms were developed through simulation of chemical process and electrical system and the PID controller is tuned. Here, two different fitness functions such as Integral Time Absolute Error and Time domain Specifications were chosen and applied on PSO, GA and SA while tuning the controller. The proposed Algorithms are implemented on two benchmark problems of coupled tank system and DC motor. Finally, comparative study has been done with different algorithms based on best cost, number of iterations and different objective functions. The closed loop process response for each set of tuned parameters is plotted for each system with each fitness function.

Refinement of Earth's gravity field with Topex GPS measurements

NASA Technical Reports Server (NTRS)

Wu, Sien-Chong; Wu, Jiun-Tsong

1989-01-01

The NASA Ocean Topography Experiment satellite TOPEX will carry a microwave altimeter accurate to a few centimeters for the measurement of ocean height. The capability can be fully exploited only if TOPEX altitude can be independently determined to 15 cm or better. This in turn requires an accurate gravity model. The gravity will be tuned with selected nine 10-day arcs of laser ranging, which will be the baseline tracking data type, collected in the first six months of TOPEX flight. TOPEX will also carry onboard an experimental Global Positioning System (GPS) flight receiver capable of simultaneously observing six GPS satellites above its horizon to demonstrate the capability of GPS carrier phase and P-code pseudorange for precise determination of the TOPEX orbit. It was found that subdecimeter orbit accuracy can be achieved with a mere two-hour arc of GPS tracking data, provided that simultaneous measurements are also made at six of more ground tracking sites. The precision GPS data from TOPEX are also valuable for refining the gravity model. An efficient technique is presented for gravity tuning using GPS measurements. Unlike conventional global gravity tuning, this technique solves for far fewer gravity parameters in each filter run. These gravity parameters yield local gravity anomalies which can later be combined with the solutions over other parts of the earth to generate a global gravity map. No supercomputing power will be needed for such combining. The approaches used in this study are described and preliminary results of a covariance analysis presented.

Adjoint-Based Climate Model Tuning: Application to the Planet Simulator

NASA Astrophysics Data System (ADS)

Lyu, Guokun; Köhl, Armin; Matei, Ion; Stammer, Detlef

2018-01-01

The adjoint method is used to calibrate the medium complexity climate model "Planet Simulator" through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.

Numerical weather prediction model tuning via ensemble prediction system

NASA Astrophysics Data System (ADS)

Jarvinen, H.; Laine, M.; Ollinaho, P.; Solonen, A.; Haario, H.

2011-12-01

This paper discusses a novel approach to tune predictive skill of numerical weather prediction (NWP) models. NWP models contain tunable parameters which appear in parameterizations schemes of sub-grid scale physical processes. Currently, numerical values of these parameters are specified manually. In a recent dual manuscript (QJRMS, revised) we developed a new concept and method for on-line estimation of the NWP model parameters. The EPPES ("Ensemble prediction and parameter estimation system") method requires only minimal changes to the existing operational ensemble prediction infra-structure and it seems very cost-effective because practically no new computations are introduced. The approach provides an algorithmic decision making tool for model parameter optimization in operational NWP. In EPPES, statistical inference about the NWP model tunable parameters is made by (i) generating each member of the ensemble of predictions using different model parameter values, drawn from a proposal distribution, and (ii) feeding-back the relative merits of the parameter values to the proposal distribution, based on evaluation of a suitable likelihood function against verifying observations. In the presentation, the method is first illustrated in low-order numerical tests using a stochastic version of the Lorenz-95 model which effectively emulates the principal features of ensemble prediction systems. The EPPES method correctly detects the unknown and wrongly specified parameters values, and leads to an improved forecast skill. Second, results with an atmospheric general circulation model based ensemble prediction system show that the NWP model tuning capacity of EPPES scales up to realistic models and ensemble prediction systems. Finally, a global top-end NWP model tuning exercise with preliminary results is published.

A regularized variable selection procedure in additive hazards model with stratified case-cohort design.

PubMed

Ni, Ai; Cai, Jianwen

2018-07-01

Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.

Tuning transport selectivity of ionic species by phosphoric acid gradient in positively charged nanochannel membranes.

PubMed

Yang, Meng; Yang, Xiaohai; Wang, Kemin; Wang, Qing; Fan, Xin; Liu, Wei; Liu, Xizhen; Liu, Jianbo; Huang, Jin

2015-02-03

The transport of ionic species through a nanochannel plays important roles in fundamental research and practical applications of the nanofluidic device. Here, we demonstrated that ionic transport selectivity of a positively charged nanochannel membrane can be tuned under a phosphoric acid gradient. When phosphoric acid solution and analyte solution were connected by the positively charged nanochannel membrane, the faster-moving analyte through the positively charged nanochannel membrane was the positively charged dye (methylviologen, MV(2+)) instead of the negatively charged dye (1,5-naphthalene disulfonate, NDS(2-)). In other words, a reversed ion selectivity of the nanochannel membranes can be found. It can be explained as a result of the combination of diffusion, induced electroosmosis, and induced electrophoresis. In addition, the influencing factors of transport selectivity, including concentration of phosphoric acid, penetration time, and volume of feed solution, were also investigated. The results showed that the transport selectivity can further be tuned by adjusting these factors. As a method of tuning ionic transport selectivity by establishing phosphoric acid gradient, it will be conducive to improving the separation of ionic species.

Genetic algorithm parameters tuning for resource-constrained project scheduling problem

NASA Astrophysics Data System (ADS)

Tian, Xingke; Yuan, Shengrui

2018-04-01

Project Scheduling Problem (RCPSP) is a kind of important scheduling problem. To achieve a certain optimal goal such as the shortest duration, the smallest cost, the resource balance and so on, it is required to arrange the start and finish of all tasks under the condition of satisfying project timing constraints and resource constraints. In theory, the problem belongs to the NP-hard problem, and the model is abundant. Many combinatorial optimization problems are special cases of RCPSP, such as job shop scheduling, flow shop scheduling and so on. At present, the genetic algorithm (GA) has been used to deal with the classical RCPSP problem and achieved remarkable results. Vast scholars have also studied the improved genetic algorithm for the RCPSP problem, which makes it to solve the RCPSP problem more efficiently and accurately. However, for the selection of the main parameters of the genetic algorithm, there is no parameter optimization in these studies. Generally, we used the empirical method, but it cannot ensure to meet the optimal parameters. In this paper, the problem was carried out, which is the blind selection of parameters in the process of solving the RCPSP problem. We made sampling analysis, the establishment of proxy model and ultimately solved the optimal parameters.

Antenna Linear-Quadratic-Gaussian (LQG) Ccontrollers: Properties, Limits of Performance, and Tuning

NASA Technical Reports Server (NTRS)

Gawronski, Wodek K.

2004-01-01

The LQG controllers significantly improve antenna tracking precision, but their tuning is a trial-and-error process. A control engineer has two tools to tune an LQG controller: the choice of coordinate system of the controller, and the selection of weights of the LQG performance index. The paper selects the coordinates of the open-loop model that simplify the shaping of the closed-loop performance. and analyzes the impact of thc weights on the antenna closed-loop bandwidth, disturbance rejection properties, and antenna acceleration. Finally, it presents the LQG controller tuning procedure that rationally shapes the closed-loop performance.

Valence electronic structure of cobalt phthalocyanine from an optimally tuned range-separated hybrid functional.

PubMed

Brumboiu, Iulia Emilia; Prokopiou, Georgia; Kronik, Leeor; Brena, Barbara

2017-07-28

We analyse the valence electronic structure of cobalt phthalocyanine (CoPc) by means of optimally tuning a range-separated hybrid functional. The tuning is performed by modifying both the amount of short-range exact exchange (α) included in the hybrid functional and the range-separation parameter (γ), with two strategies employed for finding the optimal γ for each α. The influence of these two parameters on the structural, electronic, and magnetic properties of CoPc is thoroughly investigated. The electronic structure is found to be very sensitive to the amount and range in which the exact exchange is included. The electronic structure obtained using the optimal parameters is compared to gas-phase photo-electron data and GW calculations, with the unoccupied states additionally compared with inverse photo-electron spectroscopy measurements. The calculated spectrum with tuned γ, determined for the optimal value of α = 0.1, yields a very good agreement with both experimental results and with GW calculations that well-reproduce the experimental data.

Parametrization of Combined Quantum Mechanical and Molecular Mechanical Methods: Bond-Tuned Link Atoms.

PubMed

Wu, Xin-Ping; Gagliardi, Laura; Truhlar, Donald G

2018-05-30

Combined quantum mechanical and molecular mechanical (QM/MM) methods are the most powerful available methods for high-level treatments of subsystems of very large systems. The treatment of the QM-MM boundary strongly affects the accuracy of QM/MM calculations. For QM/MM calculations having covalent bonds cut by the QM-MM boundary, it has been proposed previously to use a scheme with system-specific tuned fluorine link atoms. Here, we propose a broadly parametrized scheme where the parameters of the tuned F link atoms depend only on the type of bond being cut. In the proposed new scheme, the F link atom is tuned for systems with a certain type of cut bond at the QM-MM boundary instead of for a specific target system, and the resulting link atoms are call bond-tuned link atoms. In principle, the bond-tuned link atoms can be as convenient as the popular H link atoms, and they are especially well adapted for high-throughput and accurate QM/MM calculations. Here, we present the parameters for several kinds of cut bonds along with a set of validation calculations that confirm that the proposed bond-tuned link-atom scheme can be as accurate as the system-specific tuned F link-atom scheme.

Experiments on Adaptive Self-Tuning of Seismic Signal Detector Parameters

NASA Astrophysics Data System (ADS)

Knox, H. A.; Draelos, T.; Young, C. J.; Chael, E. P.; Peterson, M. G.; Lawry, B.; Phillips-Alonge, K. E.; Balch, R. S.; Ziegler, A.

2016-12-01

Scientific applications, including underground nuclear test monitoring and microseismic monitoring can benefit enormously from data-driven dynamic algorithms for tuning seismic and infrasound signal detection parameters since continuous streams are producing waveform archives on the order of 1TB per month. Tuning is a challenge because there are a large number of data processing parameters that interact in complex ways, and because the underlying populating of true signal detections is generally unknown. The largely manual process of identifying effective parameters, often performed only over a subset of stations over a short time period, is painstaking and does not guarantee that the resulting controls are the optimal configuration settings. We present improvements to an Adaptive Self-Tuning algorithm for continuously adjusting detection parameters based on consistency with neighboring sensors. Results are shown for 1) data from a very dense network ( 120 stations, 10 km radius) deployed during 2008 on Erebus Volcano, Antarctica, and 2) data from a continuous downhole seismic array in the Farnsworth Field, an oil field in Northern Texas that hosts an ongoing carbon capture, utilization, and storage project. Performance is assessed in terms of missed detections and false detections relative to human analyst detections, simulated waveforms where ground-truth detections exist and visual inspection.

Inverse optimal self-tuning PID control design for an autonomous underwater vehicle

NASA Astrophysics Data System (ADS)

Rout, Raja; Subudhi, Bidyadhar

2017-01-01

This paper presents a new approach to path following control design for an autonomous underwater vehicle (AUV). A NARMAX model of the AUV is derived first and then its parameters are adapted online using the recursive extended least square algorithm. An adaptive Propotional-Integral-Derivative (PID) controller is developed using the derived parameters to accomplish the path following task of an AUV. The gain parameters of the PID controller are tuned using an inverse optimal control technique, which alleviates the problem of solving Hamilton-Jacobian equation and also satisfies an error cost function. Simulation studies were pursued to verify the efficacy of the proposed control algorithm. From the obtained results, it is envisaged that the proposed NARMAX model-based self-tuning adaptive PID control provides good path following performance even in the presence of uncertainty arising due to ocean current or hydrodynamic parameter.

Optimum Parameters of a Tuned Liquid Column Damper in a Wind Turbine Subject to Stochastic Load

NASA Astrophysics Data System (ADS)

Alkmim, M. H.; de Morais, M. V. G.; Fabro, A. T.

2017-12-01

Parameter optimization for tuned liquid column dampers (TLCD), a class of passive structural control, have been previously proposed in the literature for reducing vibration in wind turbines, and several other applications. However, most of the available work consider the wind excitation as either a deterministic harmonic load or random load with white noise spectra. In this paper, a global direct search optimization algorithm to reduce vibration of a tuned liquid column damper (TLCD), a class of passive structural control device, is presented. The objective is to find optimized parameters for the TLCD under stochastic load from different wind power spectral density. A verification is made considering the analytical solution of undamped primary system under white noise excitation by comparing with result from the literature. Finally, it is shown that different wind profiles can significantly affect the optimum TLCD parameters.

Air-mass flux measurement system using Doppler-shifted filtered Rayleigh scattering

NASA Technical Reports Server (NTRS)

Shirley, John A.; Winter, Michael

1993-01-01

An optical system has been investigated to measure mass flux distributions in the inlet of a high speed air-breathing propulsion system. Rayleigh scattered light from air is proportional to the number density of molecules and hence can be used to ascertain the gas density in a calibrated system. Velocity field measurements are achieved by spectrally filtering the elastically-scattered Doppler-shifted light with an absorbing molecular filter. A novel anamorphic optical collection system is used which allows optical rays from different scattering angles, that have different Doppler shifts, to be recorded separately. This is shown to obviate the need to tune the laser through the absorption to determine velocities, while retaining the ability to make spatially-resolved measurements along a line. By properly selecting the laser tuning and filter parameters, simultaneous density measurements can be made. These properties are discussed in the paper and experiments demonstrating the velocimetry capability are described.

Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

PubMed

Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

2017-02-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

High-volume image quality assessment systems: tuning performance with an interactive data visualization tool

NASA Astrophysics Data System (ADS)

Bresnahan, Patricia A.; Pukinskis, Madeleine; Wiggins, Michael

1999-03-01

Image quality assessment systems differ greatly with respect to the number and types of mags they need to evaluate, and their overall architectures. Managers of these systems, however, all need to be able to tune and evaluate system performance, requirements often overlooked or under-designed during project planning. Performance tuning tools allow users to define acceptable quality standards for image features and attributes by adjusting parameter settings. Performance analysis tools allow users to evaluate and/or predict how well a system performs in a given parameter state. While image assessment algorithms are becoming quite sophisticated, duplicating or surpassing the human decision making process in their speed and reliability, they often require a greater investment in 'training' or fine tuning of parameters in order to achieve optimum performance. This process may involve the analysis of hundreds or thousands of images, generating a large database of files and statistics that can be difficult to sort through and interpret. Compounding the difficulty is the fact that personnel charged with tuning and maintaining the production system may not have the statistical or analytical background required for the task. Meanwhile, hardware innovations have greatly increased the volume of images that can be handled in a given time frame, magnifying the consequences of running a production site with an inadequately tuned system. In this paper, some general requirements for a performance evaluation and tuning data visualization system are discussed. A custom engineered solution to the tuning and evaluation problem is then presented, developed within the context of a high volume image quality assessment, data entry, OCR, and image archival system. A key factor influencing the design of the system was the context-dependent definition of image quality, as perceived by a human interpreter. This led to the development of a five-level, hierarchical approach to image quality evaluation. Lower-level pass-fail conditions and decision rules were coded into the system. Higher-level image quality states were defined by allowing the users to interactively adjust the system's sensitivity to various image attributes by manipulating graphical controls. Results were presented in easily interpreted bar graphs. These graphs were mouse- sensitive, allowing the user to more fully explore the subsets of data indicated by various color blocks. In order to simplify the performance evaluation and tuning process, users could choose to view the results of (1) the existing system parameter state, (2) the results of any arbitrary parameter values they chose, or (3) the results of a quasi-optimum parameter state, derived by applying a decision rule to a large set of possible parameter states. Giving managers easy- to-use tools for defining the more subjective aspects of quality resulted in a system that responded to contextual cues that are difficult to hard-code. It had the additional advantage of allowing the definition of quality to evolve over time, as users became more knowledgeable as to the strengths and limitations of an automated quality inspection system.

Parameterization of an interfacial force field for accurate representation of peptide adsorption free energy on high-density polyethylene

PubMed Central

Abramyan, Tigran M.; Snyder, James A.; Yancey, Jeremy A.; Thyparambil, Aby A.; Wei, Yang; Stuart, Steven J.; Latour, Robert A.

2015-01-01

Interfacial force field (IFF) parameters for use with the CHARMM force field have been developed for interactions between peptides and high-density polyethylene (HDPE). Parameterization of the IFF was performed to achieve agreement between experimental and calculated adsorption free energies of small TGTG–X–GTGT host–guest peptides (T = threonine, G = glycine, and X = variable amino-acid residue) on HDPE, with ±0.5 kcal/mol agreement. This IFF parameter set consists of tuned nonbonded parameters (i.e., partial charges and Lennard–Jones parameters) for use with an in-house-modified CHARMM molecular dynamic program that enables the use of an independent set of force field parameters to control molecular behavior at a solid–liquid interface. The R correlation coefficient between the simulated and experimental peptide adsorption free energies increased from 0.00 for the standard CHARMM force field parameters to 0.88 for the tuned IFF parameters. Subsequent studies are planned to apply the tuned IFF parameter set for the simulation of protein adsorption behavior on an HDPE surface for comparison with experimental values of adsorbed protein orientation and conformation. PMID:25818122

Mode selection and tuning of single-frequency short-cavity VECSELs

DOE PAGES

Serkland, Darwin K.; So, Haley M.; Peake, Gregory M.; ...

2018-03-05

Here, we report on mode selection and tuning properties of vertical-external-cavity surface-emitting lasers (VECSELs) containing coupled semiconductor and external cavities of total length less than 1 mm. Our goal is to create narrowlinewidth (<1MHz) single-frequency VECSELs that operate near 850 nm on a single longitudinal cavity resonance and tune versus temperature without mode hops. We have designed, fabricated, and measured VECSELs with external-cavity lengths ranging from 25 to 800 μm. Lastly, we compare simulated and measured coupled-cavity mode frequencies and discuss criteria for single mode selection.

The use of Argo for validation and tuning of mixed layer models

NASA Astrophysics Data System (ADS)

Acreman, D. M.; Jeffery, C. D.

We present results from validation and tuning of 1-D ocean mixed layer models using data from Argo floats and data from Ocean Weather Station Papa (145°W, 50°N). Model tests at Ocean Weather Station Papa showed that a bulk model could perform well provided it was tuned correctly. The Large et al. [Large, W.G., McWilliams, J.C., Doney, S.C., 1994. Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterisation. Rev. Geophys. 32 (Novermber), 363-403] K-profile parameterisation (KPP) model also gave a good representation of mixed layer depth provided the vertical resolution was sufficiently high. Model tests using data from a single Argo float indicated a tendency for the KPP model to deepen insufficiently over an annual cycle, whereas the tuned bulk model and general ocean turbulence model (GOTM) gave a better representation of mixed layer depth. The bulk model was then tuned using data from a sample of Argo floats and a set of optimum parameters was found; these optimum parameters were consistent with the tuning at OWS Papa.

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

NASA Astrophysics Data System (ADS)

Marzbanrad, Javad; Tahbaz-zadeh Moghaddam, Iman

2016-09-01

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.

Parameter meta-optimization of metaheuristics of solving specific NP-hard facility location problem

NASA Astrophysics Data System (ADS)

Skakov, E. S.; Malysh, V. N.

2018-03-01

The aim of the work is to create an evolutionary method for optimizing the values of the control parameters of metaheuristics of solving the NP-hard facility location problem. A system analysis of the tuning process of optimization algorithms parameters is carried out. The problem of finding the parameters of a metaheuristic algorithm is formulated as a meta-optimization problem. Evolutionary metaheuristic has been chosen to perform the task of meta-optimization. Thus, the approach proposed in this work can be called “meta-metaheuristic”. Computational experiment proving the effectiveness of the procedure of tuning the control parameters of metaheuristics has been performed.

Semi-automated segmentation of neuroblastoma nuclei using the gradient energy tensor: a user driven approach

NASA Astrophysics Data System (ADS)

Kromp, Florian; Taschner-Mandl, Sabine; Schwarz, Magdalena; Blaha, Johanna; Weiss, Tamara; Ambros, Peter F.; Reiter, Michael

2015-02-01

We propose a user-driven method for the segmentation of neuroblastoma nuclei in microscopic fluorescence images involving the gradient energy tensor. Multispectral fluorescence images contain intensity and spatial information about antigene expression, fluorescence in situ hybridization (FISH) signals and nucleus morphology. The latter serves as basis for the detection of single cells and the calculation of shape features, which are used to validate the segmentation and to reject false detections. Accurate segmentation is difficult due to varying staining intensities and aggregated cells. It requires several (meta-) parameters, which have a strong influence on the segmentation results and have to be selected carefully for each sample (or group of similar samples) by user interactions. Because our method is designed for clinicians and biologists, who may have only limited image processing background, an interactive parameter selection step allows the implicit tuning of parameter values. With this simple but intuitive method, segmentation results with high precision for a large number of cells can be achieved by minimal user interaction. The strategy was validated on handsegmented datasets of three neuroblastoma cell lines.

Binocular disparity tuning and visual-vestibular congruency of multisensory neurons in macaque parietal cortex

PubMed Central

Yang, Yun; Liu, Sheng; Chowdhury, Syed A.; DeAngelis, Gregory C.; Angelaki, Dora E.

2012-01-01

Many neurons in the dorsal medial superior temporal (MSTd) and ventral intraparietal (VIP) areas of the macaque brain are multisensory, responding to both optic flow and vestibular cues to self-motion. The heading tuning of visual and vestibular responses can be either congruent or opposite, but only congruent cells have been implicated in cue integration for heading perception. Because of the geometric properties of motion parallax, however, both congruent and opposite cells could be involved in coding self-motion when observers fixate a world-fixed target during translation, if congruent cells prefer near disparities and opposite cells prefer far disparities. We characterized the binocular disparity selectivity and heading tuning of MSTd and VIP cells using random-dot stimuli. Most (70%) MSTd neurons were disparity-selective with monotonic tuning, and there was no consistent relationship between depth preference and congruency of visual and vestibular heading tuning. One-third of disparity-selective MSTd cells reversed their depth preference for opposite directions of motion (direction-dependent disparity tuning, DDD), but most of these cells were unisensory with no tuning for vestibular stimuli. Inconsistent with previous reports, the direction preferences of most DDD neurons do not reverse with disparity. By comparison to MSTd, VIP contains fewer disparity-selective neurons (41%) and very few DDD cells. On average, VIP neurons also preferred higher speeds and nearer disparities than MSTd cells. Our findings are inconsistent with the hypothesis that visual/vestibular congruency is linked to depth preference, and also suggest that DDD cells are not involved in multisensory integration for heading perception. PMID:22159105

Thermal tuning of infrared resonant absorbers based on hybrid gold-VO{sub 2} nanostructures

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

Kocer, Hasan; Department of Electrical Engineering, Turkish Military Academy, 06654 Ankara; Butun, Serkan

2015-04-20

Resonant absorbers based on plasmonic materials, metamaterials, and thin films enable spectrally selective absorption filters, where absorption is maximized at the resonance wavelength. By controlling the geometrical parameters of nano/microstructures and materials' refractive indices, resonant absorbers are designed to operate at wide range of wavelengths for applications including absorption filters, thermal emitters, thermophotovoltaic devices, and sensors. However, once resonant absorbers are fabricated, it is rather challenging to control and tune the spectral absorption response. Here, we propose and demonstrate thermally tunable infrared resonant absorbers using hybrid gold-vanadium dioxide (VO{sub 2}) nanostructure arrays. Absorption intensity is tuned from 90% to 20%more » and 96% to 32% using hybrid gold-VO{sub 2} nanowire and nanodisc arrays, respectively, by heating up the absorbers above the phase transition temperature of VO{sub 2} (68 °C). Phase change materials such as VO{sub 2} deliver useful means of altering optical properties as a function of temperature. Absorbers with tunable spectral response can find applications in sensor and detector applications, in which external stimulus such as heat, electrical signal, or light results in a change in the absorption spectrum and intensity.« less

Orientation selectivity and the functional clustering of synaptic inputs in primary visual cortex

PubMed Central

Wilson, Daniel E.; Whitney, David E.; Scholl, Benjamin; Fitzpatrick, David

2016-01-01

The majority of neurons in primary visual cortex are tuned for stimulus orientation, but the factors that account for the range of orientation selectivities exhibited by cortical neurons remain unclear. To address this issue, we used in vivo 2-photon calcium imaging to characterize the orientation tuning and spatial arrangement of synaptic inputs to the dendritic spines of individual pyramidal neurons in layer 2/3 of ferret visual cortex. The summed synaptic input to individual neurons reliably predicted the neuron’s orientation preference, but did not account for differences in orientation selectivity among neurons. These differences reflected a robust input-output nonlinearity that could not be explained by spike threshold alone, and was strongly correlated with the spatial clustering of co-tuned synaptic inputs within the dendritic field. Dendritic branches with more co-tuned synaptic clusters exhibited greater rates of local dendritic calcium events supporting a prominent role for functional clustering of synaptic inputs in dendritic nonlinearities that shape orientation selectivity. PMID:27294510

Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

PubMed Central

Hu, Haigen; Xu, Lihong; Wei, Ruihua; Zhu, Bingkun

2011-01-01

This paper investigates the issue of tuning the Proportional Integral and Derivative (PID) controller parameters for a greenhouse climate control system using an Evolutionary Algorithm (EA) based on multiple performance measures such as good static-dynamic performance specifications and the smooth process of control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a simulation experiment. The results show that by tuning the gain parameters the controllers can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Besides, it can be applied to tuning the system with different properties, such as strong interactions among variables, nonlinearities and conflicting performance criteria. The results implicate that it is a quite effective and promising tuning method using multi-objective optimization algorithms in the complex greenhouse production. PMID:22163927

Parameter tuning method for dither compensation of a pneumatic proportional valve with friction

NASA Astrophysics Data System (ADS)

Wang, Tao; Song, Yang; Huang, Leisheng; Fan, Wei

2016-05-01

In the practical application of pneumatic control devices, the nonlinearity of a pneumatic control valve become the main factor affecting the control effect, which comes mainly from the dynamic friction force. The dynamic friction inside the valve may cause hysteresis and a dead zone. In this paper, a dither compensation mechanism is proposed to reduce negative effects on the basis of analyzing the mechanism of friction force. The specific dither signal (using a sinusoidal signal) was superimposed on the control signal of the valve. Based on the relationship between the parameters of the dither signal and the inherent characteristics of the proportional servo valve, a parameter tuning method was proposed, which uses a displacement sensor to measure the maximum static friction inside the valve. According to the experimental results, the proper amplitude ranges are determined for different pressures. In order to get the optimal parameters of the dither signal, some dither compensation experiments have been carried out on different signal amplitude and gas pressure conditions. Optimal parameters are determined under two kinds of pressure conditions. Using tuning parameters the valve spool displacement experiment has been taken. From the experiment results, hysteresis of the proportional servo valve is significantly reduced. And through simulation and experiments, the cut-off frequency of the proportional valve has also been widened. Therefore after adding the dither signal, the static and dynamic characteristics of the proportional valve are both improved to a certain degree. This research proposes a parameter tuning method of dither signal, and the validity of the method is verified experimentally.

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

NASA Technical Reports Server (NTRS)

Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.

2017-01-01

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

[Spectral Study on the Effects of Angle-Tuned Filter Wedge Angle Parameter to Reflecting Characteristics].

PubMed

Yu, Kan; Huang, De-xiu; Yin, Juan-juan; Bao, Jia-qi

2015-08-01

Three-port tunable optical filter is a key device in the all-optic intelligent switching network and dense wavelength division multiplexing system. The characteristics of the reflecting spectrum, especially the reflectivity and the isolation degree are very important to the three-port filter. Angle-tuned thin film filter is widely used as a three-port tunable filter for its high rectangular degree and good temperature stability. The characteristics of the reflecting spectrum are greatly influenced not only by the incident angle, but also by the wedge angle parameter of the non-paralleled wedge thin film filter. In the present paper, the influences of the wedge angle parameter to the reflectivity and the half bandwidth are analyzed, and the reflecting spectrum characterstics are simulationed in different wedge angle parameter and polarity. The wedge angle-tuned thin film filter with 0.8° wedge angle parameter is fabricated. The experimental results show that keeping the wedge angle the same orientation to the incident angle will worsen the reflectivity and the rectangular degree of the reflecting spectrum. However, keeping the wedge angle orientation reverse to the incident angle will enhance the reflectivity and decrease the bandwidth, which will give higher reflectivity and isolation degree to the three-port filter than that of high parallel degree angle-tuned thin film filter.

Image quality enhancement for skin cancer optical diagnostics

NASA Astrophysics Data System (ADS)

Bliznuks, Dmitrijs; Kuzmina, Ilona; Bolocko, Katrina; Lihachev, Alexey

2017-12-01

The research presents image quality analysis and enhancement proposals in biophotonic area. The sources of image problems are reviewed and analyzed. The problems with most impact in biophotonic area are analyzed in terms of specific biophotonic task - skin cancer diagnostics. The results point out that main problem for skin cancer analysis is the skin illumination problems. Since it is often not possible to prevent illumination problems, the paper proposes image post processing algorithm - low frequency filtering. Practical results show diagnostic results improvement after using proposed filter. Along that, filter do not reduces diagnostic results' quality for images without illumination defects. Current filtering algorithm requires empirical tuning of filter parameters. Further work needed to test the algorithm in other biophotonic applications and propose automatic filter parameter selection.

Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar.

PubMed

Lomp, Oliver; Richter, Mathis; Zibner, Stephan K U; Schöner, Gregor

2016-01-01

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded. The scaling and autonomy problems are solved, in part, by dynamic field theory (DFT), a theoretical framework for the neural grounding of sensorimotor and cognitive processes. In this paper, we address how to efficiently build DFT architectures that control embodied agents and how to tune their parameters so that the desired cognitive functions emerge while such agents are situated in real environments. In DFT architectures, dynamic neural fields or nodes are assigned dynamic regimes, that is, attractor states and their instabilities, from which cognitive function emerges. Tuning thus amounts to determining values of the dynamic parameters for which the components of a DFT architecture are in the specified dynamic regime under the appropriate environmental conditions. The process of tuning is facilitated by the software framework cedar , which provides a graphical interface to build and execute DFT architectures. It enables to change dynamic parameters online and visualize the activation states of any component while the agent is receiving sensory inputs in real time. Using a simple example, we take the reader through the workflow of conceiving of DFT architectures, implementing them on embodied agents, tuning their parameters, and assessing performance while the system is coupled to real sensory inputs.

Developing Dynamic Field Theory Architectures for Embodied Cognitive Systems with cedar

PubMed Central

Lomp, Oliver; Richter, Mathis; Zibner, Stephan K. U.; Schöner, Gregor

2016-01-01

Embodied artificial cognitive systems, such as autonomous robots or intelligent observers, connect cognitive processes to sensory and effector systems in real time. Prime candidates for such embodied intelligence are neurally inspired architectures. While components such as forward neural networks are well established, designing pervasively autonomous neural architectures remains a challenge. This includes the problem of tuning the parameters of such architectures so that they deliver specified functionality under variable environmental conditions and retain these functions as the architectures are expanded. The scaling and autonomy problems are solved, in part, by dynamic field theory (DFT), a theoretical framework for the neural grounding of sensorimotor and cognitive processes. In this paper, we address how to efficiently build DFT architectures that control embodied agents and how to tune their parameters so that the desired cognitive functions emerge while such agents are situated in real environments. In DFT architectures, dynamic neural fields or nodes are assigned dynamic regimes, that is, attractor states and their instabilities, from which cognitive function emerges. Tuning thus amounts to determining values of the dynamic parameters for which the components of a DFT architecture are in the specified dynamic regime under the appropriate environmental conditions. The process of tuning is facilitated by the software framework cedar, which provides a graphical interface to build and execute DFT architectures. It enables to change dynamic parameters online and visualize the activation states of any component while the agent is receiving sensory inputs in real time. Using a simple example, we take the reader through the workflow of conceiving of DFT architectures, implementing them on embodied agents, tuning their parameters, and assessing performance while the system is coupled to real sensory inputs. PMID:27853431

Thermodynamic behavior of a phase transition in a model for sympatric speciation

NASA Astrophysics Data System (ADS)

Luz-Burgoa, K.; Moss de Oliveira, S.; Schwämmle, Veit; Sá Martins, J. S.

2006-08-01

We investigate the macroscopic effects of the ingredients that drive the origin of species through sympatric speciation. In our model, sympatric speciation is obtained as we tune up the strength of competition between individuals with different phenotypes. As a function of this control parameter, we can characterize, through the behavior of a macroscopic order parameter, a phase transition from a nonspeciation to a speciation state of the system. The behavior of the first derivative of the order parameter with respect to the control parameter is consistent with a phase transition and exhibits a sharp peak at the transition point. For different resources distribution, the transition point is shifted, an effect similar to pressure in a PVT system. The inverse of the parameter related to a sexual selection strength behaves like an external field in the system and, as thus, is also a control parameter. The macroscopic effects of the biological parameters used in our model are a reminiscent of the behavior of thermodynamic quantities in a phase transition of an equilibrium physical system.

A new model to compute the desired steering torque for steer-by-wire vehicles and driving simulators

NASA Astrophysics Data System (ADS)

Fankem, Steve; Müller, Steffen

2014-05-01

This paper deals with the control of the hand wheel actuator in steer-by-wire (SbW) vehicles and driving simulators (DSs). A novel model for the computation of the desired steering torque is presented. The introduced steering torque computation does not only aim to generate a realistic steering feel, which means that the driver should not miss the basic steering functionality of a modern conventional steering system such as an electric power steering (EPS) or hydraulic power steering (HPS), and this in every driving situation. In addition, the modular structure of the steering torque computation combined with suitably selected tuning parameters has the objective to offer a high degree of customisability of the steering feel and thus to provide each driver with his preferred steering feel in a very intuitive manner. The task and the tuning of each module are firstly described. Then, the steering torque computation is parameterised such that the steering feel of a series EPS system is reproduced. For this purpose, experiments are conducted in a hardware-in-the-loop environment where a test EPS is mounted on a steering test bench coupled with a vehicle simulator and parameter identification techniques are applied. Subsequently, how appropriate the steering torque computation mimics the test EPS system is objectively evaluated with respect to criteria concerning the steering torque level and gradient, the feedback behaviour and the steering return ability. Finally, the intuitive tuning of the modular steering torque computation is demonstrated for deriving a sportier steering feel configuration.

An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

NASA Technical Reports Server (NTRS)

imon, Donald L.; Armstrong, Jeffrey B.

2012-01-01

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

Application of genetic algorithms to tuning fuzzy control systems

NASA Technical Reports Server (NTRS)

Espy, Todd; Vombrack, Endre; Aldridge, Jack

1993-01-01

Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.

Survey of Current Practice in the Fitting and Fine-Tuning of Common Signal-Processing Features in Hearing Aids for Adults.

PubMed

Anderson, Melinda C; Arehart, Kathryn H; Souza, Pamela E

2018-02-01

Current guidelines for adult hearing aid fittings recommend the use of a prescriptive fitting rationale with real-ear verification that considers the audiogram for the determination of frequency-specific gain and ratios for wide dynamic range compression. However, the guidelines lack recommendations for how other common signal-processing features (e.g., noise reduction, frequency lowering, directional microphones) should be considered during the provision of hearing aid fittings and fine-tunings for adult patients. The purpose of this survey was to identify how audiologists make clinical decisions regarding common signal-processing features for hearing aid provision in adults. An online survey was sent to audiologists across the United States. The 22 survey questions addressed four primary topics including demographics of the responding audiologists, factors affecting selection of hearing aid devices, the approaches used in the fitting of signal-processing features, and the strategies used in the fine-tuning of these features. A total of 251 audiologists who provide hearing aid fittings to adults completed the electronically distributed survey. The respondents worked in a variety of settings including private practice, physician offices, university clinics, and hospitals/medical centers. Data analysis was based on a qualitative analysis of the question responses. The survey results for each of the four topic areas (demographics, device selection, hearing aid fitting, and hearing aid fine-tuning) are summarized descriptively. Survey responses indicate that audiologists vary in the procedures they use in fitting and fine-tuning based on the specific feature, such that the approaches used for the fitting of frequency-specific gain differ from other types of features (i.e., compression time constants, frequency lowering parameters, noise reduction strength, directional microphones, feedback management). Audiologists commonly rely on prescriptive fitting formulas and probe microphone measures for the fitting of frequency-specific gain and rely on manufacturers' default settings and recommendations for both the initial fitting and the fine-tuning of signal-processing features other than frequency-specific gain. The survey results are consistent with a lack of published protocols and guidelines for fitting and adjusting signal-processing features beyond frequency-specific gain. To streamline current practice, a transparent evidence-based tool that enables clinicians to prescribe the setting of other features from individual patient characteristics would be desirable. American Academy of Audiology

Image processing for IMRT QA dosimetry.

PubMed

Zaini, Mehran R; Forest, Gary J; Loshek, David D

2005-01-01

We have automated the determination of the placement location of the dosimetry ion chamber within intensity-modulated radiotherapy (IMRT) fields, as part of streamlining the entire IMRT quality assurance process. This paper describes the mathematical image-processing techniques to arrive at the appropriate measurement locations within the planar dose maps of the IMRT fields. A specific spot within the found region is identified based on its flatness, radiation magnitude, location, area, and the avoidance of the interleaf spaces. The techniques used include applying a Laplacian, dilation, erosion, region identification, and measurement point selection based on three parameters: the size of the erosion operator, the gradient, and the importance of the area of a region versus its magnitude. These three parameters are adjustable by the user. However, the first one requires tweaking in extremely rare occasions, the gradient requires rare adjustments, and the last parameter needs occasional fine-tuning. This algorithm has been tested in over 50 cases. In about 5% of cases, the algorithm does not find a measurement point due to the extremely steep and narrow regions within the fluence maps. In such cases, manual selection of a point is allowed by our code, which is also difficult to ascertain, since the fluence map does not yield itself to an appropriate measurement point selection.

Kernel parameter variation-based selective ensemble support vector data description for oil spill detection on the ocean via hyperspectral imaging

NASA Astrophysics Data System (ADS)

Uslu, Faruk Sukru

2017-07-01

Oil spills on the ocean surface cause serious environmental, political, and economic problems. Therefore, these catastrophic threats to marine ecosystems require detection and monitoring. Hyperspectral sensors are powerful optical sensors used for oil spill detection with the help of detailed spectral information of materials. However, huge amounts of data in hyperspectral imaging (HSI) require fast and accurate computation methods for detection problems. Support vector data description (SVDD) is one of the most suitable methods for detection, especially for large data sets. Nevertheless, the selection of kernel parameters is one of the main problems in SVDD. This paper presents a method, inspired by ensemble learning, for improving performance of SVDD without tuning its kernel parameters. Additionally, a classifier selection technique is proposed to get more gain. The proposed approach also aims to solve the small sample size problem, which is very important for processing high-dimensional data in HSI. The algorithm is applied to two HSI data sets for detection problems. In the first HSI data set, various targets are detected; in the second HSI data set, oil spill detection in situ is realized. The experimental results demonstrate the feasibility and performance improvement of the proposed algorithm for oil spill detection problems.

A case study of tuning MapReduce for efficient Bioinformatics in the cloud

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

Shi, Lizhen; Wang, Zhong; Yu, Weikuan

The combination of the Hadoop MapReduce programming model and cloud computing allows biological scientists to analyze next-generation sequencing (NGS) data in a timely and cost-effective manner. Cloud computing platforms remove the burden of IT facility procurement and management from end users and provide ease of access to Hadoop clusters. However, biological scientists are still expected to choose appropriate Hadoop parameters for running their jobs. More importantly, the available Hadoop tuning guidelines are either obsolete or too general to capture the particular characteristics of bioinformatics applications. In this paper, we aim to minimize the cloud computing cost spent on bioinformatics datamore » analysis by optimizing the extracted significant Hadoop parameters. When using MapReduce-based bioinformatics tools in the cloud, the default settings often lead to resource underutilization and wasteful expenses. We choose k-mer counting, a representative application used in a large number of NGS data analysis tools, as our study case. Experimental results show that, with the fine-tuned parameters, we achieve a total of 4× speedup compared with the original performance (using the default settings). Finally, this paper presents an exemplary case for tuning MapReduce-based bioinformatics applications in the cloud, and documents the key parameters that could lead to significant performance benefits.« less

SPECIAL ISSUE DEVOTED TO THE 80TH BIRTHDAY OF S.A. AKHMANOV: Selective generation of a higher harmonic in plasma

NASA Astrophysics Data System (ADS)

Kulagin, I. A.; Usmanov, T.

2009-07-01

It is shown for the first time that the use of autoionisation states for phase matching leads to the efficient selection of a single harmonic generated in a plateau region in plasma. The selected harmonic frequency can be tuned by changing the relative concentration of plasma components and tuning the fundamental radiation frequency. It is shown that the contrast of the selected harmonic can exceed 104.

Strings on a Violin: Location Dependence of Frequency Tuning in Active Dendrites.

PubMed

Das, Anindita; Rathour, Rahul K; Narayanan, Rishikesh

2017-01-01

Strings on a violin are tuned to generate distinct sound frequencies in a manner that is firmly dependent on finger location along the fingerboard. Sound frequencies emerging from different violins could be very different based on their architecture, the nature of strings and their tuning. Analogously, active neuronal dendrites, dendrites endowed with active channel conductances, are tuned to distinct input frequencies in a manner that is dependent on the dendritic location of the synaptic inputs. Further, disparate channel expression profiles and differences in morphological characteristics could result in dendrites on different neurons of the same subtype tuned to distinct frequency ranges. Alternately, similar location-dependence along dendritic structures could be achieved through disparate combinations of channel profiles and morphological characteristics, leading to degeneracy in active dendritic spectral tuning. Akin to strings on a violin being tuned to different frequencies than those on a viola or a cello, different neuronal subtypes exhibit distinct channel profiles and disparate morphological characteristics endowing each neuronal subtype with unique location-dependent frequency selectivity. Finally, similar to the tunability of musical instruments to elicit distinct location-dependent sounds, neuronal frequency selectivity and its location-dependence are tunable through activity-dependent plasticity of ion channels and morphology. In this morceau, we explore the origins of neuronal frequency selectivity, and survey the literature on the mechanisms behind the emergence of location-dependence in distinct forms of frequency tuning. As a coda to this composition, we present some future directions for this exciting convergence of biophysical mechanisms that endow a neuron with frequency multiplexing capabilities.

Level-tolerant duration selectivity in the auditory cortex of the velvety free-tailed bat Molossus molossus.

PubMed

Macías, Silvio; Hernández-Abad, Annette; Hechavarría, Julio C; Kössl, Manfred; Mora, Emanuel C

2015-05-01

It has been reported previously that in the inferior colliculus of the bat Molossus molossus, neuronal duration tuning is ambiguous because the tuning type of the neurons dramatically changes with the sound level. In the present study, duration tuning was examined in the auditory cortex of M. molossus to describe if it is as ambiguous as the collicular tuning. From a population of 174 cortical 104 (60 %) neurons did not show duration selectivity (all-pass). Around 5 % (9 units) responded preferentially to stimuli having longer durations showing long-pass duration response functions, 35 (20 %) responded to a narrow range of stimulus durations showing band-pass duration response functions, 24 (14 %) responded most strongly to short stimulus durations showing short-pass duration response functions and two neurons (1 %) responded best to two different stimulus durations showing a two-peaked duration-response function. The majority of neurons showing short- (16 out of 24) and band-pass (24 out 35) selectivity displayed "O-shaped" duration response areas. In contrast to the inferior colliculus, duration tuning in the auditory cortex of M. molossus appears level tolerant. That is, the type of duration selectivity and the stimulus duration eliciting the maximum response were unaffected by changing sound level.

Widely Tunable Mode-Hop-Free External-Cavity Quantum Cascade Laser

NASA Technical Reports Server (NTRS)

Wysocki, Gerard; Curl, Robert F.; Tittel, Frank K.

2010-01-01

The external-cavity quantum cascade laser (EC-QCL) system is based on an optical configuration of the Littrow type. It is a room-temperature, continuous wave, widely tunable, mode-hop-free, mid-infrared, EC-QCL spectroscopic source. It has a single-mode tuning range of 155 cm(exp -1) (approximately equal to 8% of the center wavelength) with a maximum power of 11.1 mW and 182 cm(exp -1) (approximately equal to 15% of the center wavelength), and a maximum power of 50 mW as demonstrated for 5.3 micron and 8.4 micron EC-QCLs, respectively. This technology is particularly suitable for high-resolution spectroscopic applications, multi-species tracegas detection, and spectroscopic measurements of broadband absorbers. Wavelength tuning of EC-QCL spectroscopic source can be implemented by varying three independent parameters of the laser: (1) the optical length of the gain medium (which, in this case, is equivalent to QCL injection current modulation), (2) the length of the EC (which can be independently varied in the Rice EC-QCL setup), and (3) the angle of beam incidence at the diffraction grating (frequency tuning related directly to angular dispersion of the grating). All three mechanisms of frequency tuning have been demonstrated and are required to obtain a true mode-hop-free laser frequency tuning. The precise frequency tuning characteristics of the EC-QCL output have been characterized using a variety of diagnostic tools available at Rice University (e.g., a monochromator, FTIR spectrometer, and a Fabry-Perot spectrometer). Spectroscopic results were compared with available databases (such as HITRAN, PNNL, EPA, and NIST). These enable precision verification of complete spectral parameters of the EC-QCL, such as wavelength, tuning range, tuning characteristics, and line width. The output power of the EC-QCL is determined by the performance of the QC laser chip, its operating conditions, and parameters of the QC laser cavity such as mirror reflectivity or intracavity losses. In order to maximize the output power, an analysis and optimization of the EC laser parameters has been performed. The parameters of the beam emitted from the gain medium, such as divergence angle, beam profile, and astigmatism, have been investigated. The gain medium has been fully characterized before and after each stage of modification. The main modification steps are coating one facet of the gain chip with a high reflectivity mirror and the other facet with an anti-reflection layer. Then the chip is mounted in the EC-QCL. The optomechanical design has been reviewed and improved to provide for precise collimation of the strongly divergent beam of the QCL and the tuning diffraction grating.

Integrative Analysis of “-Omics” Data Using Penalty Functions

PubMed Central

Zhao, Qing; Shi, Xingjie; Huang, Jian; Liu, Jin; Li, Yang; Ma, Shuangge

2014-01-01

In the analysis of omics data, integrative analysis provides an effective way of pooling information across multiple datasets or multiple correlated responses, and can be more effective than single-dataset (response) analysis. Multiple families of integrative analysis methods have been proposed in the literature. The current review focuses on the penalization methods. Special attention is paid to sparse meta-analysis methods that pool summary statistics across datasets, and integrative analysis methods that pool raw data across datasets. We discuss their formulation and rationale. Beyond “standard” penalized selection, we also review contrasted penalization and Laplacian penalization which accommodate finer data structures. The computational aspects, including computational algorithms and tuning parameter selection, are examined. This review concludes with possible limitations and extensions. PMID:25691921

Tuning Features of Chinese Folk Song Singing: A Case Study of Hua'er Music.

PubMed

Yang, Yang; Welch, Graham; Sundberg, Johan; Himonides, Evangelos

2015-07-01

The learning and teaching of different singing styles, such as operatic and Chinese folk singing, was often found to be very challenging in professional music education because of the complexity of varied musical properties and vocalizations. By studying the acoustical and musical parameters of the singing voice, this study identified distinctive tuning characteristics of a particular folk music in China-Hua'er music-to inform the ineffective folk singing practices, which were hampered by the neglect of inherent tuning issues in music. Thirteen unaccompanied folk song examples from four folk singers were digitally audio recorded in a sound studio. Using an analyzing toolkit consisting of Praat, PeakFit, and MS Excel, the fundamental frequencies (F0) of these song examples were extracted into sets of "anchor pitches" mostly used, which were further divided into 253 F0 clusters. The interval structures of anchor pitches within each song were analyzed and then compared across 13 examples providing parameters that indicate the tuning preference of this particular singing style. The data analyses demonstrated that all singers used a tuning pattern consisting of five major anchor pitches suggesting a nonequal-tempered bias in singing. This partly verified the pentatonic scale proposed in previous empirical research but also argued a potential misunderstanding of the studied folk music scale that failed to take intrinsic tuning issues into consideration. This study suggests that, in professional music training, any tuning strategy should be considered in terms of the reference pitch and likely tuning systems. Any accompanying instruments would need to be tuned to match the underlying tuning bias. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Tuning Higher Education

NASA Astrophysics Data System (ADS)

Carroll, Bradley

2011-03-01

In April 2009, the Lumina Foundation launched its Tuning USA project. Faculty teams in selected disciplines from Indiana, Minnesota, and Utah started pilot Tuning programs at their home institutions. Using Europe's Bologna Process as a guide, Utah physicists worked to reach a consensus about the knowledge and skills that should characterize the 2-year, batchelor's, and master's degree levels. I will share my experience as a member of Utah's physics Tuning team, and describe our progress, frustrations, and evolving understanding of the Tuning project's history, methods, and goals.

Reducing variable frequency vibrations in a powertrain system with an adaptive tuned vibration absorber group

NASA Astrophysics Data System (ADS)

Gao, Pu; Xiang, Changle; Liu, Hui; Zhou, Han

2018-07-01

Based on a multiple degrees of freedom dynamic model of a vehicle powertrain system, natural vibration analyses and sensitivity analyses of the eigenvalues are performed to determine the key inertia for each natural vibration of a powertrain system. Then, the results are used to optimize the installation position of each adaptive tuned vibration absorber. According to the relationship between the variable frequency torque excitation and the natural vibration of a powertrain system, the entire vibration frequency band is divided into segments, and the auxiliary vibration absorber and dominant vibration absorber are determined for each sensitive frequency band. The optimum parameters of the auxiliary vibration absorber are calculated based on the optimal frequency ratio and the optimal damping ratio of the passive vibration absorber. The instantaneous change state of the natural vibrations of a powertrain system with adaptive tuned vibration absorbers is studied, and the optimized start and stop tuning frequencies of the adaptive tuned vibration absorber are obtained. These frequencies can be translated into the optimum parameters of the dominant vibration absorber. Finally, the optimal tuning scheme for the adaptive tuned vibration absorber group, which can be used to reduce the variable frequency vibrations of a powertrain system, is proposed, and corresponding numerical simulations are performed. The simulation time history signals are transformed into three-dimensional information related to time, frequency and vibration energy via the Hilbert-Huang transform (HHT). A comprehensive time-frequency analysis is then conducted to verify that the optimal tuning scheme for the adaptive tuned vibration absorber group can significantly reduce the variable frequency vibrations of a powertrain system.

A PET reconstruction formulation that enforces non-negativity in projection space for bias reduction in Y-90 imaging

NASA Astrophysics Data System (ADS)

Lim, Hongki; Dewaraja, Yuni K.; Fessler, Jeffrey A.

2018-02-01

Most existing PET image reconstruction methods impose a nonnegativity constraint in the image domain that is natural physically, but can lead to biased reconstructions. This bias is particularly problematic for Y-90 PET because of the low probability positron production and high random coincidence fraction. This paper investigates a new PET reconstruction formulation that enforces nonnegativity of the projections instead of the voxel values. This formulation allows some negative voxel values, thereby potentially reducing bias. Unlike the previously reported NEG-ML approach that modifies the Poisson log-likelihood to allow negative values, the new formulation retains the classical Poisson statistical model. To relax the non-negativity constraint embedded in the standard methods for PET reconstruction, we used an alternating direction method of multipliers (ADMM). Because choice of ADMM parameters can greatly influence convergence rate, we applied an automatic parameter selection method to improve the convergence speed. We investigated the methods using lung to liver slices of XCAT phantom. We simulated low true coincidence count-rates with high random fractions corresponding to the typical values from patient imaging in Y-90 microsphere radioembolization. We compared our new methods with standard reconstruction algorithms and NEG-ML and a regularized version thereof. Both our new method and NEG-ML allow more accurate quantification in all volumes of interest while yielding lower noise than the standard method. The performance of NEG-ML can degrade when its user-defined parameter is tuned poorly, while the proposed algorithm is robust to any count level without requiring parameter tuning.

Objective calibration of numerical weather prediction models

NASA Astrophysics Data System (ADS)

Voudouri, A.; Khain, P.; Carmona, I.; Bellprat, O.; Grazzini, F.; Avgoustoglou, E.; Bettems, J. M.; Kaufmann, P.

2017-07-01

Numerical weather prediction (NWP) and climate models use parameterization schemes for physical processes, which often include free or poorly confined parameters. Model developers normally calibrate the values of these parameters subjectively to improve the agreement of forecasts with available observations, a procedure referred as expert tuning. A practicable objective multi-variate calibration method build on a quadratic meta-model (MM), that has been applied for a regional climate model (RCM) has shown to be at least as good as expert tuning. Based on these results, an approach to implement the methodology to an NWP model is presented in this study. Challenges in transferring the methodology from RCM to NWP are not only restricted to the use of higher resolution and different time scales. The sensitivity of the NWP model quality with respect to the model parameter space has to be clarified, as well as optimize the overall procedure, in terms of required amount of computing resources for the calibration of an NWP model. Three free model parameters affecting mainly turbulence parameterization schemes were originally selected with respect to their influence on the variables associated to daily forecasts such as daily minimum and maximum 2 m temperature as well as 24 h accumulated precipitation. Preliminary results indicate that it is both affordable in terms of computer resources and meaningful in terms of improved forecast quality. In addition, the proposed methodology has the advantage of being a replicable procedure that can be applied when an updated model version is launched and/or customize the same model implementation over different climatological areas.

Attention to Color Sharpens Neural Population Tuning via Feedback Processing in the Human Visual Cortex Hierarchy.

PubMed

Bartsch, Mandy V; Loewe, Kristian; Merkel, Christian; Heinze, Hans-Jochen; Schoenfeld, Mircea A; Tsotsos, John K; Hopf, Jens-Max

2017-10-25

Attention can facilitate the selection of elementary object features such as color, orientation, or motion. This is referred to as feature-based attention and it is commonly attributed to a modulation of the gain and tuning of feature-selective units in visual cortex. Although gain mechanisms are well characterized, little is known about the cortical processes underlying the sharpening of feature selectivity. Here, we show with high-resolution magnetoencephalography in human observers (men and women) that sharpened selectivity for a particular color arises from feedback processing in the human visual cortex hierarchy. To assess color selectivity, we analyze the response to a color probe that varies in color distance from an attended color target. We find that attention causes an initial gain enhancement in anterior ventral extrastriate cortex that is coarsely selective for the target color and transitions within ∼100 ms into a sharper tuned profile in more posterior ventral occipital cortex. We conclude that attention sharpens selectivity over time by attenuating the response at lower levels of the cortical hierarchy to color values neighboring the target in color space. These observations support computational models proposing that attention tunes feature selectivity in visual cortex through backward-propagating attenuation of units less tuned to the target. SIGNIFICANCE STATEMENT Whether searching for your car, a particular item of clothing, or just obeying traffic lights, in everyday life, we must select items based on color. But how does attention allow us to select a specific color? Here, we use high spatiotemporal resolution neuromagnetic recordings to examine how color selectivity emerges in the human brain. We find that color selectivity evolves as a coarse to fine process from higher to lower levels within the visual cortex hierarchy. Our observations support computational models proposing that feature selectivity increases over time by attenuating the responses of less-selective cells in lower-level brain areas. These data emphasize that color perception involves multiple areas across a hierarchy of regions, interacting with each other in a complex, recursive manner. Copyright © 2017 the authors 0270-6474/17/3710346-12$15.00/0.

The impact of orientation filtering on face-selective neurons in monkey inferior temporal cortex.

PubMed

Taubert, Jessica; Goffaux, Valerie; Van Belle, Goedele; Vanduffel, Wim; Vogels, Rufin

2016-02-16

Faces convey complex social signals to primates. These signals are tolerant of some image transformations (e.g. changes in size) but not others (e.g. picture-plane rotation). By filtering face stimuli for orientation content, studies of human behavior and brain responses have shown that face processing is tuned to selective orientation ranges. In the present study, for the first time, we recorded the responses of face-selective neurons in monkey inferior temporal (IT) cortex to intact and scrambled faces that were filtered to selectively preserve horizontal or vertical information. Guided by functional maps, we recorded neurons in the lateral middle patch (ML), the lateral anterior patch (AL), and an additional region located outside of the functionally defined face-patches (CONTROL). We found that neurons in ML preferred horizontal-passed faces over their vertical-passed counterparts. Neurons in AL, however, had a preference for vertical-passed faces, while neurons in CONTROL had no systematic preference. Importantly, orientation filtering did not modulate the firing rate of neurons to phase-scrambled face stimuli in any recording region. Together these results suggest that face-selective neurons found in the face-selective patches are differentially tuned to orientation content, with horizontal tuning in area ML and vertical tuning in area AL.

Natural extension of fast-slow decomposition for dynamical systems

NASA Astrophysics Data System (ADS)

Rubin, J. E.; Krauskopf, B.; Osinga, H. M.

2018-01-01

Modeling and parameter estimation to capture the dynamics of physical systems are often challenging because many parameters can range over orders of magnitude and are difficult to measure experimentally. Moreover, selecting a suitable model complexity requires a sufficient understanding of the model's potential use, such as highlighting essential mechanisms underlying qualitative behavior or precisely quantifying realistic dynamics. We present an approach that can guide model development and tuning to achieve desired qualitative and quantitative solution properties. It relies on the presence of disparate time scales and employs techniques of separating the dynamics of fast and slow variables, which are well known in the analysis of qualitative solution features. We build on these methods to show how it is also possible to obtain quantitative solution features by imposing designed dynamics for the slow variables in the form of specified two-dimensional paths in a bifurcation-parameter landscape.

Self-tuning wireless power transmission scheme based on on-line scattering parameters measurement and two-side power matching.

PubMed

Luo, Yanting; Yang, Yongmin; Chen, Zhongsheng

2014-04-10

Sub-resonances often happen in wireless power transmission (WPT) systems using coupled magnetic resonances (CMR) due to environmental changes, coil movements or component degradations, which is a serious challenge for high efficiency power transmission. Thus self-tuning is very significant to keep WPT systems following strongly magnetic resonant conditions in practice. Traditional coupled-mode ways is difficult to solve this problem. In this paper a two-port power wave model is presented, where power matching and the overall systemic power transmission efficiency are firstly defined by scattering (S) parameters. Then we propose a novel self-tuning scheme based on on-line S parameters measurements and two-side power matching. Experimental results testify the feasibility of the proposed method. These findings suggest that the proposed method is much potential to develop strongly self-adaptive WPT systems with CMR.

Tuning magnetofluidic spreading in microchannels

NASA Astrophysics Data System (ADS)

Wang, Zhaomeng; Varma, V. B.; Wang, Z. P.; Ramanujan, R. V.

2015-12-01

Magnetofluidic spreading (MFS) is a phenomenon in which a uniform magnetic field is used to induce spreading of a ferrofluid core cladded by diamagnetic fluidic streams in a three-stream channel. Applications of MFS include micromixing, cell sorting and novel microfluidic lab-on-a-chip design. However, the relative importance of the parameters which govern MFS is still unclear, leading to non-optimal control of MFS. Hence, in this work, the effect of various key parameters on MFS was experimentally and numerically studied. Our multi-physics model, which combines magnetic and fluidic analysis, showed excellent agreement between theory and experiment. It was found that spreading was mainly due to cross-sectional convection induced by magnetic forces, and can be enhanced by tuning various parameters. Smaller flow rate ratio, higher magnetic field, higher core stream or lower cladding stream dynamic viscosity, and larger magnetic particle size can increase MFS. These results can be used to tune magnetofluidic spreading in microchannels.

A Numerical Optimization Approach for Tuning Fuzzy Logic Controllers

NASA Technical Reports Server (NTRS)

Woodard, Stanley E.; Garg, Devendra P.

1998-01-01

This paper develops a method to tune fuzzy controllers using numerical optimization. The main attribute of this approach is that it allows fuzzy logic controllers to be tuned to achieve global performance requirements. Furthermore, this approach allows design constraints to be implemented during the tuning process. The method tunes the controller by parameterizing the membership functions for error, change-in-error and control output. The resulting parameters form a design vector which is iteratively changed to minimize an objective function. The minimal objective function results in an optimal performance of the system. A spacecraft mounted science instrument line-of-sight pointing control is used to demonstrate results.

Role of inhibition in the specification of orientation selectivity of cells in the cat striate cortex.

PubMed

Bonds, A B

1989-01-01

Mechanisms supporting orientation selectivity of cat striate cortical cells were studied by stimulation with two superimposed sine-wave gratings of different orientations. One grating (base) generated a discharge of known amplitude which could be modified by the second grating (mask). Masks presented at nonoptimal orientations usually reduced the base-generated response, but the degree of reduction varied widely between cells. Cells with narrow orientation tuning tended to be more susceptible to mask presence than broadly tuned cells; similarly, simple cells generally showed more response reduction than did complex cells. The base and mask stimuli were drifted at different temporal frequencies which, in simple cells, permitted the identification of individual response components from each stimulus. This revealed that the reduction of the base response by the mask usually did not vary regularly with mask orientation, although response facilitation from the mask was orientation selective. In some sharply tuned simple cells, response reduction had clear local maxima near the limits of the cell's orientation-tuning function. Response reduction resulted from a nearly pure rightward shift of the response versus log contrast function. The lowest mask contrast yielding reduction was within 0.1-0.3 log unit of the lowest contrast effective for excitation. The temporal-frequency bandpass of the response-reduction mechanism resembled that of most cortical cells. The spatial-frequency bandpass was much broader than is typical for single cortical cells, spanning essentially the entire visual range of the cat. These findings are compatible with a model in which weak intrinsic orientation-selective excitation is enhanced in two stages: (1) control of threshold by nonorientation-selective inhibition that is continuously dependent on stimulus contrast; and (2) in the more narrowly tuned cells, orientation-selective inhibition that has local maxima serving to increase the slope of the orientation-tuning function.

Short-Term Depression, Temporal Summation, and Onset Inhibition Shape Interval Tuning in Midbrain Neurons

PubMed Central

Baker, Christa A.

2014-01-01

A variety of synaptic mechanisms can contribute to single-neuron selectivity for temporal intervals in sensory stimuli. However, it remains unknown how these mechanisms interact to establish single-neuron sensitivity to temporal patterns of sensory stimulation in vivo. Here we address this question in a circuit that allows us to control the precise temporal patterns of synaptic input to interval-tuned neurons in behaviorally relevant ways. We obtained in vivo intracellular recordings under multiple levels of current clamp from midbrain neurons in the mormyrid weakly electric fish Brienomyrus brachyistius during stimulation with electrosensory pulse trains. To reveal the excitatory and inhibitory inputs onto interval-tuned neurons, we then estimated the synaptic conductances underlying responses. We found short-term depression in excitatory and inhibitory pathways onto all interval-tuned neurons. Short-interval selectivity was associated with excitation that depressed less than inhibition at short intervals, as well as temporally summating excitation. Long-interval selectivity was associated with long-lasting onset inhibition. We investigated tuning after separately nullifying the contributions of temporal summation and depression, and found the greatest diversity of interval selectivity among neurons when both mechanisms were at play. Furthermore, eliminating the effects of depression decreased sensitivity to directional changes in interval. These findings demonstrate that variation in depression and summation of excitation and inhibition helps to establish tuning to behaviorally relevant intervals in communication signals, and that depression contributes to neural coding of interval sequences. This work reveals for the first time how the interplay between short-term plasticity and temporal summation mediates the decoding of temporal sequences in awake, behaving animals. PMID:25339741

Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression.

PubMed

Agrawal, Deepak K; Tang, Xun; Westbrook, Alexandra; Marshall, Ryan; Maxwell, Colin S; Lucks, Julius; Noireaux, Vincent; Beisel, Chase L; Dunlop, Mary J; Franco, Elisa

2018-05-08

Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.

Filter parameter tuning analysis for operational orbit determination support

NASA Technical Reports Server (NTRS)

Dunham, J.; Cox, C.; Niklewski, D.; Mistretta, G.; Hart, R.

1994-01-01

The use of an extended Kalman filter (EKF) for operational orbit determination support is being considered by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD). To support that investigation, analysis was performed to determine how an EKF can be tuned for operational support of a set of earth-orbiting spacecraft. The objectives of this analysis were to design and test a general purpose scheme for filter tuning, evaluate the solution accuracies, and develop practical methods to test the consistency of the EKF solutions in an operational environment. The filter was found to be easily tuned to produce estimates that were consistent, agreed with results from batch estimation, and compared well among the common parameters estimated for several spacecraft. The analysis indicates that there is not a sharply defined 'best' tunable parameter set, especially when considering only the position estimates over the data arc. The comparison of the EKF estimates for the user spacecraft showed that the filter is capable of high-accuracy results and can easily meet the current accuracy requirements for the spacecraft included in the investigation. The conclusion is that the EKF is a viable option for FDD operational support.

High pressure research using muons at the Paul Scherrer Institute

NASA Astrophysics Data System (ADS)

Khasanov, R.; Guguchia, Z.; Maisuradze, A.; Andreica, D.; Elender, M.; Raselli, A.; Shermadini, Z.; Goko, T.; Knecht, F.; Morenzoni, E.; Amato, A.

2016-04-01

Pressure, together with temperature and magnetic field, is an important thermodynamical parameter in physics. Investigating the response of a compound or of a material to pressure allows to elucidate ground states, investigate their interplay and interactions and determine microscopic parameters. Pressure tuning is used to establish phase diagrams, study phase transitions and identify critical points. Muon spin rotation/relaxation (μSR) is now a standard technique making increasing significant contribution in condensed matter physics, material science research and other fields. In this review, we will discuss specific requirements and challenges to perform μSR experiments under pressure, introduce the high pressure muon facility at the Paul Scherrer Institute (PSI, Switzerland) and present selected results obtained by combining the sensitivity of the μSR technique with pressure.

Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting

PubMed Central

Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.

2016-01-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048

Gas Sensors Based on Semiconducting Nanowire Field-Effect Transistors

PubMed Central

Feng, Ping; Shao, Feng; Shi, Yi; Wan, Qing

2014-01-01

One-dimensional semiconductor nanostructures are unique sensing materials for the fabrication of gas sensors. In this article, gas sensors based on semiconducting nanowire field-effect transistors (FETs) are comprehensively reviewed. Individual nanowires or nanowire network films are usually used as the active detecting channels. In these sensors, a third electrode, which serves as the gate, is used to tune the carrier concentration of the nanowires to realize better sensing performance, including sensitivity, selectivity and response time, etc. The FET parameters can be modulated by the presence of the target gases and their change relate closely to the type and concentration of the gas molecules. In addition, extra controls such as metal decoration, local heating and light irradiation can be combined with the gate electrode to tune the nanowire channel and realize more effective gas sensing. With the help of micro-fabrication techniques, these sensors can be integrated into smart systems. Finally, some challenges for the future investigation and application of nanowire field-effect gas sensors are discussed. PMID:25232915

Design and Theoretical Analysis of a Resonant Sensor for Liquid Density Measurement

PubMed Central

Zheng, Dezhi; Shi, Jiying; Fan, Shangchun

2012-01-01

In order to increase the accuracy of on-line liquid density measurements, a sensor equipped with a tuning fork as the resonant sensitive component is designed in this paper. It is a quasi-digital sensor with simple structure and high precision. The sensor is based on resonance theory and composed of a sensitive unit and a closed-loop control unit, where the sensitive unit consists of the actuator, the resonant tuning fork and the detector and the closed-loop control unit comprises precondition circuit, digital signal processing and control unit, analog-to-digital converter and digital-to-analog converter. An approximate parameters model of the tuning fork is established and the impact of liquid density, position of the tuning fork, temperature and structural parameters on the natural frequency of the tuning fork are also analyzed. On this basis, a tuning fork liquid density measurement sensor is developed. In addition, experimental testing on the sensor has been carried out on standard calibration facilities under constant 20 °C, and the sensor coefficients are calibrated. The experimental results show that the repeatability error is about 0.03% and the accuracy is about 0.4 kg/m3. The results also confirm that the method to increase the accuracy of liquid density measurement is feasible. PMID:22969378

Design and theoretical analysis of a resonant sensor for liquid density measurement.

PubMed

Zheng, Dezhi; Shi, Jiying; Fan, Shangchun

2012-01-01

In order to increase the accuracy of on-line liquid density measurements, a sensor equipped with a tuning fork as the resonant sensitive component is designed in this paper. It is a quasi-digital sensor with simple structure and high precision. The sensor is based on resonance theory and composed of a sensitive unit and a closed-loop control unit, where the sensitive unit consists of the actuator, the resonant tuning fork and the detector and the closed-loop control unit comprises precondition circuit, digital signal processing and control unit, analog-to-digital converter and digital-to-analog converter. An approximate parameters model of the tuning fork is established and the impact of liquid density, position of the tuning fork, temperature and structural parameters on the natural frequency of the tuning fork are also analyzed. On this basis, a tuning fork liquid density measurement sensor is developed. In addition, experimental testing on the sensor has been carried out on standard calibration facilities under constant 20 °C, and the sensor coefficients are calibrated. The experimental results show that the repeatability error is about 0.03% and the accuracy is about 0.4 kg/m(3). The results also confirm that the method to increase the accuracy of liquid density measurement is feasible.

Tuning maps for setpoint changes and load disturbance upsets in a three capacity process under multivariable control

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Smith, Ira C.

1991-01-01

Tuning maps are an aid in the controller tuning process because they provide a convenient way for the plant operator to determine the consequences of adjusting different controller parameters. In this application the maps provide a graphical representation of the effect of varying the gains in the state feedback matrix on startup and load disturbance transients for a three capacity process. Nominally, the three tank system, represented in diagonal form, has a Proportional-Integral control on each loop. Cross coupling is then introduced between the loops by using non-zero off-diagonal proportional parameters. Changes in transient behavior due to setpoint and load changes are examined by varying the gains of the cross coupling terms.

Electrically assisted bandedge mode selection of photonic crystal lasing in chiral nematic liquid crystals

NASA Astrophysics Data System (ADS)

Wang, Chun-Ta; Chen, Chun-Wei; Yang, Tzu-Hsuan; Nys, Inge; Li, Cheng-Chang; Lin, Tsung-Hsien; Neyts, Kristiaan; Beeckman, Jeroen

2018-01-01

Selection of the bandedge lasing mode of a photonic crystal laser has been realized in a fluorescent dye doped chiral nematic liquid crystal by exerting electrical control over the mode competition. The bandedge lasing can be reversibly switched from the short-wavelength edge mode to the long-wavelength edge mode by applying a voltage of only 20 V, without tuning the bandgap. The underlying mechanism is the field-induced change in the order parameter of the fluorescent dye in the liquid crystal. The orientation of the transition dipole moment determines the polarization state of the dye emission, thereby promoting lasing in the bandedge mode that favors the emission polarization. Moreover, the dynamic mode-selection capability is retained upon polymer-stabilizing the chiral nematic liquid crystal laser. In the polymer-stabilized system, greatly improved stability and lasing performance are observed.

Visual Tuning Properties of Genetically Identified Layer 2/3 Neuronal Types in the Primary Visual Cortex of Cre-Transgenic Mice

PubMed Central

Zariwala, Hatim A.; Madisen, Linda; Ahrens, Kurt F.; Bernard, Amy; Lein, Edward S.; Jones, Allan R.; Zeng, Hongkui

2011-01-01

The putative excitatory and inhibitory cell classes within the mouse primary visual cortex V1 have different functional properties as studied using recording microelectrode. Excitatory neurons show high selectivity for the orientation angle of moving gratings while the putative inhibitory neurons show poor selectivity. However, the study of selectivity of the genetically identified interneurons and their subtypes remain controversial. Here we use novel Cre-driver and reporter mice to identify genetic subpopulations in vivo for two-photon calcium dye imaging: Wfs1(+)/Gad1(−) mice that labels layer 2/3 excitatory cell population and Pvalb(+)/Gad1(+) mice that labels a genetic subpopulation of inhibitory neurons. The cells in both mice were identically labeled with a tdTomato protein, visible in vivo, using a Cre-reporter line. We found that the Wfs1(+) cells exhibited visual tuning properties comparable to the excitatory population, i.e., high selectivity and tuning to the angle, direction, and spatial frequency of oriented moving gratings. The functional tuning of Pvalb(+) neurons was consistent with previously reported narrow-spiking interneurons in microelectrode studies, exhibiting poorer selectivity than the excitatory neurons. This study demonstrates the utility of Cre-transgenic mouse technology in selective targeting of subpopulations of neurons and makes them amenable to structural, functional, and connectivity studies. PMID:21283555

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2011-12-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model

NASA Astrophysics Data System (ADS)

Qian, Y.; Yang, B.; Lin, G.; Leung, R.; Zhang, Y.

2012-04-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. The latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic important-sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e., the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Some issues in uncertainty quantification and parameter tuning: a case study of convective parameterization scheme in the WRF regional climate model

NASA Astrophysics Data System (ADS)

Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y.

2012-03-01

The current tuning process of parameters in global climate models is often performed subjectively or treated as an optimization procedure to minimize model biases based on observations. While the latter approach may provide more plausible values for a set of tunable parameters to approximate the observed climate, the system could be forced to an unrealistic physical state or improper balance of budgets through compensating errors over different regions of the globe. In this study, the Weather Research and Forecasting (WRF) model was used to provide a more flexible framework to investigate a number of issues related uncertainty quantification (UQ) and parameter tuning. The WRF model was constrained by reanalysis of data over the Southern Great Plains (SGP), where abundant observational data from various sources was available for calibration of the input parameters and validation of the model results. Focusing on five key input parameters in the new Kain-Fritsch (KF) convective parameterization scheme used in WRF as an example, the purpose of this study was to explore the utility of high-resolution observations for improving simulations of regional patterns and evaluate the transferability of UQ and parameter tuning across physical processes, spatial scales, and climatic regimes, which have important implications to UQ and parameter tuning in global and regional models. A stochastic importance sampling algorithm, Multiple Very Fast Simulated Annealing (MVFSA) was employed to efficiently sample the input parameters in the KF scheme based on a skill score so that the algorithm progressively moved toward regions of the parameter space that minimize model errors. The results based on the WRF simulations with 25-km grid spacing over the SGP showed that the precipitation bias in the model could be significantly reduced when five optimal parameters identified by the MVFSA algorithm were used. The model performance was found to be sensitive to downdraft- and entrainment-related parameters and consumption time of Convective Available Potential Energy (CAPE). Simulated convective precipitation decreased as the ratio of downdraft to updraft flux increased. Larger CAPE consumption time resulted in less convective but more stratiform precipitation. The simulation using optimal parameters obtained by constraining only precipitation generated positive impact on the other output variables, such as temperature and wind. By using the optimal parameters obtained at 25-km simulation, both the magnitude and spatial pattern of simulated precipitation were improved at 12-km spatial resolution. The optimal parameters identified from the SGP region also improved the simulation of precipitation when the model domain was moved to another region with a different climate regime (i.e. the North America monsoon region). These results suggest that benefits of optimal parameters determined through vigorous mathematical procedures such as the MVFSA process are transferable across processes, spatial scales, and climatic regimes to some extent. This motivates future studies to further assess the strategies for UQ and parameter optimization at both global and regional scales.

Grey Relational Analysis Coupled with Principal Component Analysis for Optimization of Stereolithography Process to Enhance Part Quality

NASA Astrophysics Data System (ADS)

Raju, B. S.; Sekhar, U. Chandra; Drakshayani, D. N.

2017-08-01

The paper investigates optimization of stereolithography process for SL5530 epoxy resin material to enhance part quality. The major characteristics indexed for performance selected to evaluate the processes are tensile strength, Flexural strength, Impact strength and Density analysis and corresponding process parameters are Layer thickness, Orientation and Hatch spacing. In this study, the process is intrinsically with multiple parameters tuning so that grey relational analysis which uses grey relational grade as performance index is specially adopted to determine the optimal combination of process parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively desired. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively acquire the optimal combination of process parameters. Hence, this confirm that the proposed approach in this study can be an useful tool to improve the process parameters in stereolithography process, which is very useful information for machine designers as well as RP machine users.

Controlling Reaction Selectivity through the Surface Termination of Perovskite Catalysts

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

Polo-Garzon, Felipe; Yang, Shi-Ze; Fung, Victor

2017-07-19

Although perovskites have been widely used in catalysis, tuning their surface terminations to control reaction selectivities has not been well established. In this work, we employ multiple surface sensitive techniques to characterize the surface termination (one aspect of surface reconstruction) of SrTiO 3 (STO) after thermal pretreatment (Sr-enrichment) and chemical etching (Ti-enrichment). We show, using the conversion of 2-propanol as a probe reaction, that the surface termination of STO can be controlled to greatly tune catalytic acid/base properties and consequently the reaction selectivities in a wide range, which are inaccessible using single metal oxides, either SrO or TiO 2. Densitymore » functional theory (DFT) calculations well explain the selectivity tuning and reaction mechanism on different surface terminations of STO. Similar catalytic tunability is also observed on BaZrO 3, highlighting the generality of the finding from this work.« less

Parameter optimization of an inerter-based isolator for passive vibration control of Michelangelo's Rondanini Pietà

NASA Astrophysics Data System (ADS)

Siami, A.; Karimi, H. R.; Cigada, A.; Zappa, E.; Sabbioni, E.

2018-01-01

Preserving cultural heritage against earthquake and ambient vibrations can be an attractive topic in the field of vibration control. This paper proposes a passive vibration isolator methodology based on inerters for improving the performance of the isolation system of the famous statue of Michelangelo Buonarroti Pietà Rondanini. More specifically, a five-degree-of-freedom (5DOF) model of the statue and the anti-seismic and anti-vibration base is presented and experimentally validated. The parameters of this model are tuned according to the experimental tests performed on the assembly of the isolator and the structure. Then, the developed model is used to investigate the impact of actuation devices such as tuned mass-damper (TMD) and tuned mass-damper-inerter (TMDI) in vibration reduction of the structure. The effect of implementation of TMDI on the 5DOF model is shown based on physical limitations of the system parameters. Simulation results are provided to illustrate effectiveness of the passive element of TMDI in reduction of the vibration transmitted to the statue in vertical direction. Moreover, the optimal design parameters of the passive system such as frequency and damping coefficient will be calculated using two different performance indexes. The obtained optimal parameters have been evaluated by using two different optimization algorithms: the sequential quadratic programming method and the Firefly algorithm. The results prove significant reduction in the transmitted vibration to the structure in the presence of the proposed tuned TMDI, without imposing a large amount of mass or modification to the structure of the isolator.

Hydrogen maser frequency standard computer model for automatic cavity tuning servo simulations

NASA Technical Reports Server (NTRS)

Potter, P. D.; Finnie, C.

1978-01-01

A computer model of the JPL hydrogen maser frequency standard was developed. This model allows frequency stability data to be generated, as a function of various maser parameters, many orders of magnitude faster than these data can be obtained by experimental test. In particular, the maser performance as a function of the various automatic tuning servo parameters may be readily determined. Areas of discussion include noise sources, first-order autotuner loop, second-order autotuner loop, and a comparison of the loops.

A Tuned Single Parameter for Representing Conjunction Risk

NASA Technical Reports Server (NTRS)

Plakaloic, D.; Hejduk, M. D.; Frigm, R. C.; Newman, L. K.

2011-01-01

Satellite conjunction assessment risk analysis is a subjective enterprise that can benefit from quantitative aids and, to this end, NASA/GSFC has developed a fuzzy logic construct - called the F-value - to attempt to provide a statement of conjunction risk that amalgamates multiple indices and yields a more stable intra-event assessment. This construct has now sustained an extended tuning procedure against heuristic analyst assessment of event risk. The tuning effort has resulted in modifications to the calculation procedure and the adjustment of tuning coefficients, producing a construct with both more predictive force and a better statement of its error.

Systematic characterization of a 1550 nm microelectromechanical (MEMS)-tunable vertical-cavity surface-emitting laser (VCSEL) with 7.92 THz tuning range for terahertz photomixing systems

NASA Astrophysics Data System (ADS)

Haidar, M. T.; Preu, S.; Cesar, J.; Paul, S.; Hajo, A. S.; Neumeyr, C.; Maune, H.; Küppers, F.

2018-01-01

Continuous-wave (CW) terahertz (THz) photomixing requires compact, widely tunable, mode-hop-free driving lasers. We present a single-mode microelectromechanical system (MEMS)-tunable vertical-cavity surface-emitting laser (VCSEL) featuring an electrothermal tuning range of 64 nm (7.92 THz) that exceeds the tuning range of commercially available distributed-feedback laser (DFB) diodes (˜4.8 nm) by a factor of about 13. We first review the underlying theory and perform a systematic characterization of the MEMS-VCSEL, with particular focus on the parameters relevant for THz photomixing. These parameters include mode-hop-free CW tuning with a side-mode-suppression-ratio >50 dB, a linewidth as narrow as 46.1 MHz, and wavelength and polarization stability. We conclude with a demonstration of a CW THz photomixing setup by subjecting the MEMS-VCSEL to optical beating with a DFB diode driving commercial photomixers. The achievable THz bandwidth is limited only by the employed photomixers. Once improved photomixers become available, electrothermally actuated MEMS-VCSELs should allow for a tuning range covering almost the whole THz domain with a single system.

Tuning the Selectivity of Single-Site Supported Metal Catalysts with Ionic Liquids

DOE PAGES

Babucci, Melike; Fang, Chia -Yu; Hoffman, Adam S.; ...

2017-09-11

1,3-Dialkylimidazolium ionic liquid coatings act as electron donors, increasing the selectivity for partial hydrogenation of 1,3-butadiene catalyzed by iridium complexes supported on high-surface-area γ-Al 2O 3. High-energy-resolution fluorescence detection X-ray absorption near-edge structure (HERFD XANES) measurements quantify the electron donation and are correlated with the catalytic activity and selectivity. Furthermore, the results demonstrate broad opportunities to tune electronic environments and catalytic properties of atomically dispersed supported metal catalysts.

Gas separation mechanism of CO 2 selective amidoxime-poly(1-trimethylsilyl-1-propyne) membranes

DOE PAGES

Feng, Hongbo; Hong, Tao; Mahurin, Shannon Mark; ...

2017-05-09

Polymeric membranes for CO 2 separation have drawn significant attention in academia and industry. We prepared amidoxime-functionalized poly(1-trimethylsilyl-1-propyne) (AO-PTMSP) membranes through hydrosilylation and post-polymerization modification. Compared to neat PTMSP membranes, the AO-PTMSP membranes showed significant enhancements in CO 2/N 2 gas separation performance (CO 2 permeability ~6000 Barrer; CO 2/N 2 selectivity 17). This systematic study provides clear guidelines on how to tune the CO 2-philicity within PTMSP matrices and the effects on gas selectivity. Key parameters for elucidating the gas transport mechanism were discussed based on CO 2 sorption measurements and fractional free volume estimates. The effect of themore » AO content on CO 2/N 2 selectivity was further examined by means of density functional theory calculations. Here, both experimental and theoretical data provide consistent results that conclusively show that CO 2/N 2 separation performance is enhanced by increased CO 2 polymer interactions.« less

Gas separation mechanism of CO 2 selective amidoxime-poly(1-trimethylsilyl-1-propyne) membranes

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

Feng, Hongbo; Hong, Tao; Mahurin, Shannon Mark

Polymeric membranes for CO 2 separation have drawn significant attention in academia and industry. We prepared amidoxime-functionalized poly(1-trimethylsilyl-1-propyne) (AO-PTMSP) membranes through hydrosilylation and post-polymerization modification. Compared to neat PTMSP membranes, the AO-PTMSP membranes showed significant enhancements in CO 2/N 2 gas separation performance (CO 2 permeability ~6000 Barrer; CO 2/N 2 selectivity 17). This systematic study provides clear guidelines on how to tune the CO 2-philicity within PTMSP matrices and the effects on gas selectivity. Key parameters for elucidating the gas transport mechanism were discussed based on CO 2 sorption measurements and fractional free volume estimates. The effect of themore » AO content on CO 2/N 2 selectivity was further examined by means of density functional theory calculations. Here, both experimental and theoretical data provide consistent results that conclusively show that CO 2/N 2 separation performance is enhanced by increased CO 2 polymer interactions.« less

Towards water compatible MIPs for sensing in aqueous media.

PubMed

Horemans, F; Weustenraed, A; Spivak, D; Cleij, T J

2012-06-01

When synthesizing molecularly imprinted polymers (MIPs), a few fundamental principles should be kept in mind. There is a strong correlation between porogen polarity, MIP microenvironment polarity and the imprinting effect itself. The combination of these parameters eventually determines the overall binding behavior of a MIP in a given solvent. In addition, it is shown that MIP binding is strongly influenced by the polarity of the rebinding solvent. Because the use of MIPs in biomedical environments is of considerable interest, it is important that these MIPs perform well in aqueous media. In this article, various approaches are explored towards a water compatible MIP for the target molecule l-nicotine. To this end, the imprinting effect together with the MIP matrix polarity is fine-tuned during MIP synthesis. The binding behavior of the resulting MIPs is evaluated by performing batch rebinding experiments that makes it possible to select the most suitable MIP/non-imprinted polymer couple for future application in aqueous environments. One method to achieve improved compatibility with water is referred to as porogen tuning, in which porogens of varying polarities are used. It is demonstrated that, especially when multiple porogens are mixed, this approach can lead to superior performance in aqueous environments. Another method involves the incorporation of polar or non-polar comonomers in the MIP matrix. It is shown that by carefully selecting these monomers, it is also possible to obtain MIPs, which can selectively bind their target in water. Copyright © 2012 John Wiley & Sons, Ltd.

Adding words to the brain's visual dictionary: novel word learning selectively sharpens orthographic representations in the VWFA.

PubMed

Glezer, Laurie S; Kim, Judy; Rule, Josh; Jiang, Xiong; Riesenhuber, Maximilian

2015-03-25

The nature of orthographic representations in the human brain is still subject of much debate. Recent reports have claimed that the visual word form area (VWFA) in left occipitotemporal cortex contains an orthographic lexicon based on neuronal representations highly selective for individual written real words (RWs). This theory predicts that learning novel words should selectively increase neural specificity for these words in the VWFA. We trained subjects to recognize novel pseudowords (PWs) and used fMRI rapid adaptation to compare neural selectivity with RWs, untrained PWs (UTPWs), and trained PWs (TPWs). Before training, PWs elicited broadly tuned responses, whereas responses to RWs indicated tight tuning. After training, TPW responses resembled those of RWs, whereas UTPWs continued to show broad tuning. This change in selectivity was specific to the VWFA. Therefore, word learning appears to selectively increase neuronal specificity for the new words in the VWFA, thereby adding these words to the brain's visual dictionary. Copyright © 2015 the authors 0270-6474/15/354965-08$15.00/0.

Event generator tunes obtained from underlying event and multiparton scattering measurements.

PubMed

Khachatryan, V; Sirunyan, A M; Tumasyan, A; Adam, W; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Friedl, M; Frühwirth, R; Ghete, V M; Hartl, C; Hörmann, N; Hrubec, J; Jeitler, M; Knünz, V; König, A; Krammer, M; Krätschmer, I; Liko, D; Matsushita, T; Mikulec, I; Rabady, D; Rahbaran, B; Rohringer, H; Schieck, J; Schöfbeck, R; Strauss, J; Treberer-Treberspurg, W; Waltenberger, W; Wulz, C-E; Mossolov, V; Shumeiko, N; Suarez Gonzalez, J; Alderweireldt, S; Cornelis, T; De Wolf, E A; Janssen, X; Knutsson, A; Lauwers, J; Luyckx, S; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Van Spilbeeck, A; Abu Zeid, S; Blekman, F; D'Hondt, J; Daci, N; De Bruyn, I; Deroover, K; Heracleous, N; Keaveney, J; Lowette, S; Moreels, L; Olbrechts, A; Python, Q; Strom, D; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Onsem, G P; Van Parijs, I; Barria, P; Brun, H; Caillol, C; Clerbaux, B; De Lentdecker, G; Fasanella, G; Favart, L; Grebenyuk, A; Karapostoli, G; Lenzi, T; Léonard, A; Maerschalk, T; Marinov, A; Perniè, L; Randle-Conde, A; Seva, T; Vander Velde, C; Yonamine, R; Vanlaer, P; Yonamine, R; Zenoni, F; Zhang, F; Adler, V; Beernaert, K; Benucci, L; Cimmino, A; Crucy, S; Dobur, D; Fagot, A; Garcia, G; Gul, M; Mccartin, J; Ocampo Rios, A A; Poyraz, D; Ryckbosch, D; Salva, S; Sigamani, M; Tytgat, M; Van Driessche, W; Yazgan, E; Zaganidis, N; Basegmez, S; Beluffi, C; Bondu, O; Brochet, S; Bruno, G; Caudron, A; Ceard, L; Da Silveira, G G; Delaere, C; Favart, D; Forthomme, L; Giammanco, A; Hollar, J; Jafari, A; Jez, P; Komm, M; Lemaitre, V; Mertens, A; Musich, M; Nuttens, C; Perrini, L; Pin, A; Piotrzkowski, K; Popov, A; Quertenmont, L; Selvaggi, M; Vidal Marono, M; Beliy, N; Hammad, G H; Júnior, W L Aldá; Alves, F L; Alves, G A; Brito, L; Correa Martins Junior, M; Hamer, M; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Huertas Guativa, L M; Malbouisson, H; Matos Figueiredo, D; Mora Herrera, C; Mundim, L; Nogima, H; Prado Da Silva, W L; Santoro, A; Sznajder, A; Tonelli Manganote, E J; Vilela Pereira, A; Ahuja, S; Bernardes, C A; De Souza Santos, A; Dogra, S; Fernandez Perez Tomei, T R; Gregores, E M; Mercadante, P G; Moon, C S; Novaes, S F; Padula, Sandra S; Romero Abad, D; Ruiz Vargas, J C; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Rodozov, M; Stoykova, S; Sultanov, G; Vutova, M; Dimitrov, A; Glushkov, I; Litov, L; Pavlov, B; Petkov, P; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Cheng, T; Du, R; Jiang, C H; Plestina, R; Romeo, F; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Zhang, H; Asawatangtrakuldee, C; Ban, Y; Li, Q; Liu, S; Mao, Y; Qian, S J; Wang, D; Xu, Z; Avila, C; Cabrera, A; Chaparro Sierra, L F; Florez, C; Gomez, J P; Gomez Moreno, B; Sanabria, J C; Godinovic, N; Lelas, D; Puljak, I; Ribeiro Cipriano, P M; Antunovic, Z; Kovac, M; Brigljevic, V; Kadija, K; 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Worm, S D; Baber, M; Bainbridge, R; Buchmuller, O; Bundock, A; Burton, D; Casasso, S; Citron, M; Colling, D; Corpe, L; Cripps, N; Dauncey, P; Davies, G; De Wit, A; Della Negra, M; Dunne, P; Elwood, A; Elwood, A; Ferguson, W; Futyan, D; Hall, G; Iles, G; Kenzie, M; Lane, R; Lucas, R; Lyons, L; Magnan, A-M; Malik, S; Nash, J; Nikitenko, A; Pela, J; Pesaresi, M; Petridis, K; Raymond, D M; Richards, A; Rose, A; Seez, C; Tapper, A; Uchida, K; Vazquez Acosta, M; Virdee, T; Zenz, S C; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Leggat, D; Leslie, D; Reid, I D; Symonds, P; Teodorescu, L; Turner, M; Borzou, A; Call, K; Dittmann, J; Hatakeyama, K; Liu, H; Pastika, N; Scarborough, T; Wu, Z; Charaf, O; Cooper, S I; Henderson, C; Rumerio, P; Arcaro, D; Avetisyan, A; Bose, T; Fantasia, C; Gastler, D; Lawson, P; Rankin, D; Richardson, C; Rohlf, J; St John, J; Sulak, L; Zou, D; Alimena, J; Berry, E; Bhattacharya, S; Cutts, D; Dhingra, N; Ferapontov, A; Garabedian, A; Hakala, J; Heintz, U; Laird, E; Landsberg, G; 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Campagnari, C; Dishaw, A; Dutta, V; Flowers, K; Franco Sevilla, M; Geffert, P; George, C; Golf, F; Gouskos, L; Gran, J; Incandela, J; Mccoll, N; Mullin, S D; Mullin, S D; Richman, J; Stuart, D; Suarez, I; West, C; Yoo, J; Anderson, D; Apresyan, A; Bornheim, A; Bunn, J; Chen, Y; Duarte, J; Mott, A; Newman, H B; Pena, C; Pierini, M; Spiropulu, M; Vlimant, J R; Xie, S; Zhu, R Y; Andrews, M B; Azzolini, V; Calamba, A; Carlson, B; Ferguson, T; Paulini, M; Russ, J; Sun, M; Vogel, H; Vorobiev, I; Cumalat, J P; Ford, W T; Gaz, A; Jensen, F; Johnson, A; Krohn, M; Mulholland, T; Nauenberg, U; Stenson, K; Wagner, S R; Alexander, J; Chatterjee, A; Chaves, J; Chu, J; Dittmer, S; Eggert, N; Mirman, N; Nicolas Kaufman, G; Patterson, J R; Rinkevicius, A; Ryd, A; Skinnari, L; Soffi, L; Sun, W; Tan, S M; Teo, W D; Thom, J; Thompson, J; Tucker, J; Weng, Y; Wittich, P; Abdullin, S; Albrow, M; Apollinari, G; Banerjee, S; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bolla, G; Burkett, K; Butler, J N; Cheung, H W K; Chlebana, F; Cihangir, S; Elvira, V D; Fisk, I; Freeman, J; Gottschalk, E; Gray, L; Green, D; Grünendahl, S; Gutsche, O; Hanlon, J; Hare, D; Harris, R M; Hasegawa, S; Hirschauer, J; Hu, Z; Jayatilaka, B; Jindariani, S; Johnson, M; Joshi, U; Jung, A W; Klima, B; Kreis, B; Lammel, S; Linacre, J; Lincoln, D; Lipton, R; Liu, T; Lopes De Sá, R; Lykken, J; Maeshima, K; Marraffino, J M; Martinez Outschoorn, V I; Maruyama, S; Mason, D; McBride, P; Merkel, P; Mishra, K; Mrenna, S; Nahn, S; Newman-Holmes, C; O'Dell, V; Pedro, K; Prokofyev, O; Rakness, G; Sexton-Kennedy, E; Soha, A; Spalding, W J; Spiegel, L; Strobbe, N; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vernieri, C; Verzocchi, M; Vidal, R; Weber, H A; Whitbeck, A; Acosta, D; Avery, P; Bortignon, P; Bourilkov, D; Carnes, A; Carver, M; Curry, D; Das, S; Field, R D; Furic, I K; Gleyzer, S V; Hugon, J; Konigsberg, J; Korytov, A; Kotov, K; Low, J F; Ma, P; Matchev, K; Mei, H; Milenovic, P; Mitselmakher, G; Rank, D; Rossin, R; Shchutska, L; Snowball, M; Sperka, D; Terentyev, N; Thomas, L; Wang, J; Wang, S; Yelton, J; Hewamanage, S; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Adams, J R; Ackert, A; Adams, T; Askew, A; Bein, S; Bochenek, J; Diamond, B; Haas, J; Hagopian, S; Hagopian, V; Johnson, K F; Khatiwada, A; Prosper, H; Weinberg, M; Baarmand, M M; Bhopatkar, V; Colafranceschi, S; Hohlmann, M; Kalakhety, H; Noonan, D; Roy, T; Yumiceva, F; Adams, M R; Apanasevich, L; Berry, D; Betts, R R; Bucinskaite, I; Cavanaugh, R; Evdokimov, O; Gauthier, L; Gerber, C E; Hofman, D J; Kurt, P; O'Brien, C; Sandoval Gonzalez, L D; Silkworth, C; Turner, P; Varelas, N; Wu, Z; Zakaria, M; Bilki, B; Clarida, W; Dilsiz, K; Durgut, S; Gandrajula, R P; Haytmyradov, M; Khristenko, V; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Ogul, H; Onel, Y; Ozok, F; Penzo, A; Snyder, C; Tiras, E; Wetzel, J; Yi, K; Anderson, I; Anderson, I; Barnett, B A; Blumenfeld, B; Eminizer, N; Fehling, D; Feng, L; Gritsan, A V; Maksimovic, P; Martin, C; Osherson, M; Roskes, J; Sady, A; Sarica, U; Swartz, M; Xiao, M; Xin, Y; You, C; Xiao, M; Baringer, P; Bean, A; Benelli, G; Bruner, C; Kenny, R P; Majumder, D; Majumder, D; Malek, M; Murray, M; Sanders, S; Stringer, R; Wang, Q; Ivanov, A; Kaadze, K; Khalil, S; Makouski, M; Maravin, Y; Mohammadi, A; Saini, L K; Skhirtladze, N; Toda, S; Lange, D; Rebassoo, F; Wright, D; Anelli, C; Baden, A; Baron, O; Belloni, A; Calvert, B; Eno, S C; Ferraioli, C; Gomez, J A; Hadley, N J; Jabeen, S; Jabeen, S; Kellogg, R G; Kolberg, T; Kunkle, J; Lu, Y; Mignerey, A C; Shin, Y H; Skuja, A; Tonjes, M B; Tonwar, S C; Apyan, A; Barbieri, R; Baty, A; Bierwagen, K; Brandt, S; Bierwagen, K; Busza, W; Cali, I A; Demiragli, Z; Di Matteo, L; Gomez Ceballos, G; Goncharov, M; Gulhan, D; Iiyama, Y; Innocenti, G M; Klute, M; Kovalskyi, D; Lai, Y S; Lee, Y-J; Levin, A; Luckey, P D; Marini, A C; Mcginn, C; Mironov, C; Narayanan, S; Niu, X; Paus, C; Ralph, D; Roland, C; Roland, G; Salfeld-Nebgen, J; Stephans, G S F; Sumorok, K; Varma, M; Velicanu, D; Veverka, J; Wang, J; Wang, T W; Wyslouch, B; Yang, M; Zhukova, V; Dahmes, B; Evans, A; Finkel, A; Gude, A; Hansen, P; Kalafut, S; Kao, S C; Klapoetke, K; Kubota, Y; Lesko, Z; Mans, J; Nourbakhsh, S; Ruckstuhl, N; Rusack, R; Tambe, N; Turkewitz, J; Acosta, J G; Oliveros, S; Avdeeva, E; Bloom, K; Bose, S; Claes, D R; Dominguez, A; Fangmeier, C; Gonzalez Suarez, R; Kamalieddin, R; Keller, J; Knowlton, D; Kravchenko, I; Meier, F; Monroy, J; Ratnikov, F; Siado, J E; Snow, G R; Alyari, M; Dolen, J; George, J; Godshalk, A; Harrington, C; Iashvili, I; Kaisen, J; Kharchilava, A; Kumar, A; Rappoccio, S; Roozbahani, B; Alverson, G; Barberis, E; Baumgartel, D; Chasco, M; Hortiangtham, A; Massironi, A; Morse, D M; Nash, D; Orimoto, T; Teixeira De Lima, R; Trocino, D; Wang, R-J; Wood, D; Zhang, J; Hahn, K A; Kubik, A; Mucia, N; Odell, N; Pollack, B; Pozdnyakov, A; Schmitt, M; Stoynev, S; Sung, K; Trovato, M; Velasco, M; Brinkerhoff, A; Dev, N; Hildreth, M; Jessop, C; Karmgard, D J; Kellams, N; Lannon, K; Marinelli, N; Meng, F; Mueller, C; Musienko, Y; Planer, M; Reinsvold, A; Ruchti, R; Smith, G; Taroni, S; Valls, N; Wayne, M; Wolf, M; Woodard, A; Antonelli, L; Brinson, J; Bylsma, B; Durkin, L S; Flowers, S; Hart, A; Hill, C; Hughes, R; Ji, W; Ling, T Y; Liu, B; Luo, W; Puigh, D; Rodenburg, M; Winer, B L; Wulsin, H W; Driga, O; Elmer, P; Hardenbrook, J; Hebda, P; Koay, S A; Lujan, P; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Palmer, C; Piroué, P; Saka, H; Stickland, D; Tully, C; Zuranski, A; Malik, S; Barnes, V E; Benedetti, D; Bortoletto, D; Gutay, L; Jha, M K; Jones, M; Jung, K; Miller, D H; Neumeister, N; Primavera, F; Radburn-Smith, B C; Shi, X; Shipsey, I; Silvers, D; Sun, J; Svyatkovskiy, A; Wang, F; Xie, W; Xu, L; Parashar, N; Stupak, J; Adair, A; Akgun, B; Chen, Z; Ecklund, K M; Geurts, F J M; Guilbaud, M; Li, W; Michlin, B; Northup, M; Padley, B P; Redjimi, R; Roberts, J; Rorie, J; Tu, Z; Zabel, J; Betchart, B; 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New sets of parameters ("tunes") for the underlying-event (UE) modelling of the pythia8, pythia6 and herwig++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton-proton ([Formula: see text]) data at [Formula: see text] and to UE proton-antiproton ([Formula: see text]) data from the CDF experiment at lower [Formula: see text], are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton-proton collisions at 13[Formula: see text]. In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons are presented of the UE tunes to "minimum bias" (MB) events, multijet, and Drell-Yan ([Formula: see text] lepton-antilepton+jets) observables at 7 and 8[Formula: see text], as well as predictions for MB and UE observables at 13[Formula: see text].

Analytical design of modified Smith predictor for unstable second-order processes with time delay

NASA Astrophysics Data System (ADS)

Ajmeri, Moina; Ali, Ahmad

2017-06-01

In this paper, a modified Smith predictor using three controllers, namely, stabilising (Gc), set-point tracking (Gc1), and load disturbance rejection (Gc2) controllers is proposed for second-order unstable processes with time delay. Controllers of the proposed structure are tuned using direct synthesis approach as this method enables the user to achieve a trade-off between the performance and robustness by adjusting a single design parameter. Furthermore, suitable values of the tuning parameters are recommended after studying their effect on the closed-loop performance and robustness. This is the main advantage of the proposed work over other recently published manuscripts, where authors provide only suitable ranges for the tuning parameters in spite of giving their suitable values. Simulation studies show that the proposed method results in satisfactory performance and improved robustness as compared to the recently reported control schemes. It is observed that the proposed scheme is able to work in the noisy environment also.

Molecular interfaces for plasmonic hot electron photovoltaics

NASA Astrophysics Data System (ADS)

Pelayo García de Arquer, F.; Mihi, Agustín; Konstantatos, Gerasimos

2015-01-01

The use of self-assembled monolayers (SAMs) to improve and tailor the photovoltaic performance of plasmonic hot-electron Schottky solar cells is presented. SAMs allow the simultaneous control of open-circuit voltage, hot-electron injection and short-circuit current. To that end, a plurality of molecule structural parameters can be adjusted: SAM molecule's length can be adjusted to control plasmonic hot electron injection. Modifying SAMs dipole moment allows for a precise tuning of the open-circuit voltage. The functionalization of the SAM can also be selected to modify short-circuit current. This allows the simultaneous achievement of high open-circuit voltages (0.56 V) and fill-factors (0.58), IPCE above 5% at the plasmon resonance and maximum power-conversion efficiencies of 0.11%, record for this class of devices.The use of self-assembled monolayers (SAMs) to improve and tailor the photovoltaic performance of plasmonic hot-electron Schottky solar cells is presented. SAMs allow the simultaneous control of open-circuit voltage, hot-electron injection and short-circuit current. To that end, a plurality of molecule structural parameters can be adjusted: SAM molecule's length can be adjusted to control plasmonic hot electron injection. Modifying SAMs dipole moment allows for a precise tuning of the open-circuit voltage. The functionalization of the SAM can also be selected to modify short-circuit current. This allows the simultaneous achievement of high open-circuit voltages (0.56 V) and fill-factors (0.58), IPCE above 5% at the plasmon resonance and maximum power-conversion efficiencies of 0.11%, record for this class of devices. Electronic supplementary information (ESI) available: Contact-potential differentiometry measurements, FTIR characterization, performance statistics and gold devices. See DOI: 10.1039/c4nr06356b

Long adaptation reveals mostly attractive shifts of orientation tuning in cat primary visual cortex.

PubMed

Ghisovan, N; Nemri, A; Shumikhina, S; Molotchnikoff, S

2009-12-15

In the adult brain, sensory cortical neurons undergo transient changes of their response properties following prolonged exposure to an appropriate stimulus (adaptation). In cat V1, orientation-selective cells shift their preferred orientation after being adapted to a non-preferred orientation. There are conflicting reports as to the direction of those shifts, towards (attractive) or away (repulsive) from the adapter. Moreover, the mechanisms underlying attractive shifts remain unexplained. In the present investigation we show that attractive shifts are the most frequent outcome of a 12 min adaptation. Overall, cells displaying selectivity for oblique orientations exhibit significantly larger shifts than cells tuned to cardinal orientations. In addition, cells selective to cardinal orientations had larger shift amplitudes when the absolute difference between the original preferred orientation and the adapting orientation increased. Conversely, cells tuned to oblique orientations exhibited larger shift amplitudes when this absolute orientation difference was narrower. Hence, neurons tuned to oblique contours appear to show more plasticity in response to small perturbations. Two different mechanisms appear to produce attractive and repulsive orientation shifts. Attractive shifts result from concurrent response depression on the non-adapted flank and selective response facilitation on the adapted flank of the orientation tuning curve. In contrast, repulsive shifts are caused solely by response depression on the adapted flank. We suggest that an early mechanism leads to repulsive shifts while attractive shifts engage a subsequent late facilitation. A potential role for attractive shifts may be improved stimulus discrimination around the adapting orientation.

An adaptive control scheme for a flexible manipulator

NASA Technical Reports Server (NTRS)

Yang, T. C.; Yang, J. C. S.; Kudva, P.

1987-01-01

The problem of controlling a single link flexible manipulator is considered. A self-tuning adaptive control scheme is proposed which consists of a least squares on-line parameter identification of an equivalent linear model followed by a tuning of the gains of a pole placement controller using the parameter estimates. Since the initial parameter values for this model are assumed unknown, the use of arbitrarily chosen initial parameter estimates in the adaptive controller would result in undesirable transient effects. Hence, the initial stage control is carried out with a PID controller. Once the identified parameters have converged, control is transferred to the adaptive controller. Naturally, the relevant issues in this scheme are tests for parameter convergence and minimization of overshoots during control switch-over. To demonstrate the effectiveness of the proposed scheme, simulation results are presented with an analytical nonlinear dynamic model of a single link flexible manipulator.

The opponent channel population code of sound location is an efficient representation of natural binaural sounds.

PubMed

Młynarski, Wiktor

2015-05-01

In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a "panoramic" code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding.

Rational Design and Tuning of Functional RNA Switch to Control an Allosteric Intermolecular Interaction.

PubMed

Endoh, Tamaki; Sugimoto, Naoki

2015-08-04

Conformational transitions of biomolecules in response to specific stimuli control many biological processes. In natural functional RNA switches, often called riboswitches, a particular RNA structure that has a suppressive or facilitative effect on gene expression transitions to an alternative structure with the opposite effect upon binding of a specific metabolite to the aptamer region. Stability of RNA secondary structure (-ΔG°) can be predicted based on thermodynamic parameters and is easily tuned by changes in nucleobases. We envisioned that tuning of a functional RNA switch that causes an allosteric interaction between an RNA and a peptide would be possible based on a predicted switching energy (ΔΔG°) that corresponds to the energy difference between the RNA secondary structure before (-ΔG°before) and after (-ΔG°after) the RNA conformational transition. We first selected functional RNA switches responsive to neomycin with predicted ΔΔG° values ranging from 5.6 to 12.2 kcal mol(-1). We then demonstrated a simple strategy to rationally convert the functional RNA switch to switches responsive to natural metabolites thiamine pyrophosphate, S-adenosyl methionine, and adenine based on the predicted ΔΔG° values. The ΔΔG° values of the designed RNA switches proportionally correlated with interaction energy (ΔG°interaction) between the RNA and peptide, and we were able to tune the sensitivity of the RNA switches for the trigger molecule. The strategy demonstrated here will be generally applicable for construction of functional RNA switches and biosensors in which mechanisms are based on conformational transition of nucleic acids.

Photolithography and Selective Etching of an Array of Quartz Tuning Fork Resonators with Improved Impact Resistance Characteristics

NASA Astrophysics Data System (ADS)

Lee, Sungkyu

2001-08-01

Quartz tuning fork blanks with improved impact-resistant characteristics for use in Qualcomm mobile station modem (MSM)-3000 central processing unit (CPU) chips for code division multiple access (CDMA), personal communication system (PCS), and global system for mobile communication (GSM) systems were designed using finite element method (FEM) analysis and suitable processing conditions were determined for the reproducible precision etching of a Z-cut quartz wafer into an array of tuning forks. Negative photoresist photolithography for the additive process was used in preference to positive photoresist photolithography for the subtractive process to etch the array of quartz tuning forks. The tuning fork pattern was transferred via a conventional photolithographical chromium/quartz glass template using a standard single-sided aligner and subsequent negative photoresist development. A tightly adhering and pinhole-free 600/2000 Å chromium/gold mask was coated over the developed photoresist pattern which was subsequently stripped in acetone. This procedure was repeated on the back surface of the wafer. With the protective metallization area of the tuning fork geometry thus formed, etching through the quartz wafer was performed at 80°C in a ± 1.5°C controlled bath containing a concentrated solution of ammonium bifluoride to remove the unwanted areas of the quartz wafer. The quality of the quartz wafer surface finish after quartz etching depended primarily on the surface finish of the quartz wafer prior to etching and the quality of quartz crystals used. Selective etching of a 100 μm quartz wafer could be achieved within 90 min at 80°C. A selective etching procedure with reproducible precision has thus been established and enables the photolithographic mass production of miniature tuning fork resonators.

TCP performance in ATM networks: ABR parameter tuning and ABR/UBR comparisons

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

Chien Fang; Lin, A.

1996-02-27

This paper explores two issues on TOP performance over ATM networks: ABR parameter tuning and performance comparison of binary mode ABR with enhanced UBR services. Of the fifteen parameters defined for ABR, two parameters dominate binary mode ABR performance: Rate Increase Factor (RIF) and Rate Decrease Factor (RDF). Using simulations, we study the effects of these two parameters on TOP over ABR performance. We compare TOP performance with different ABR parameter settings in terms of through-puts and fairness. The effects of different buffer sizes and LAN/WAN distances are also examined. We then compare TOP performance with the best ABR parametermore » setting with corresponding UBR service enhanced with Early Packet Discard and also with a fair buffer allocation scheme. The results show that TOP performance over binary mode ABR is very sensitive to parameter value settings, and that a poor choice of parameters can result in ABR performance worse than that of the much less expensive UBR-EPD scheme.« less

Fine-tuning free paradigm of two-measures theory: k-essence, absence of initial singularity of the curvature, and inflation with graceful exit to the zero cosmological constant state

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

Guendelman, E. I.; Kaganovich, A. B.

2007-04-15

The dilaton-gravity sector of the two-measures field theory (TMT) is explored in detail in the context of spatially flat Friedman-Robertson-Walker (FRW) cosmology. The model possesses scale invariance which is spontaneously broken due to the intrinsic features of the TMT dynamics. The dilaton {phi} dependence of the effective Lagrangian appears only as a result of the spontaneous breakdown of the scale invariance. If no fine-tuning is made, the effective {phi}-Lagrangian p({phi},X) depends quadratically upon the kinetic term X. Hence TMT represents an explicit example of the effective k-essence resulting from first principles without any exotic term in the underlying action intendedmore » for obtaining this result. Depending of the choice of regions in the parameter space (but without fine-tuning), TMT exhibits different possible outputs for cosmological dynamics: (a) Absence of initial singularity of the curvature while its time derivative is singular. This is a sort of sudden singularities studied by Barrow on purely kinematic grounds. (b) Power law inflation in the subsequent stage of evolution. Depending on the region in the parameter space the inflation ends with a graceful exit either into the state with zero cosmological constant (CC) or into the state driven by both a small CC and the field {phi} with a quintessencelike potential. (c) Possibility of resolution of the old CC problem. From the point of view of TMT, it becomes clear why the old CC problem cannot be solved (without fine-tuning) in conventional field theories. (d) TMT enables two ways for achieving small CC without fine-tuning of dimensionful parameters: either by a seesaw type mechanism or due to a correspondence principle between TMT and conventional field theories (i.e. theories with only the measure of integration {radical}(-g) in the action). (e) There is a wide range of the parameters such that in the late time universe: the equation of state w=p/{rho}<-1; w asymptotically (as t{yields}{infinity}) approaches -1 from below; {rho} approaches a constant, the smallness of which does not require fine-tuning of dimensionful parameters.« less

The Role of Visual Area V4 in the Discrimination of Partially Occluded Shapes

PubMed Central

Kosai, Yoshito; El-Shamayleh, Yasmine; Fyall, Amber M.

2014-01-01

The primate brain successfully recognizes objects, even when they are partially occluded. To begin to elucidate the neural substrates of this perceptual capacity, we measured the responses of shape-selective neurons in visual area V4 while monkeys discriminated pairs of shapes under varying degrees of occlusion. We found that neuronal shape selectivity always decreased with increasing occlusion level, with some neurons being notably more robust to occlusion than others. The responses of neurons that maintained their selectivity across a wider range of occlusion levels were often sufficiently sensitive to support behavioral performance. Many of these same neurons were distinctively selective for the curvature of local boundary features and their shape tuning was well fit by a model of boundary curvature (curvature-tuned neurons). A significant subset of V4 neurons also signaled the animal's upcoming behavioral choices; these decision signals had short onset latencies that emerged progressively later for higher occlusion levels. The time course of the decision signals in V4 paralleled that of shape selectivity in curvature-tuned neurons: shape selectivity in curvature-tuned neurons, but not others, emerged earlier than the decision signals. These findings provide evidence for the involvement of contour-based mechanisms in the segmentation and recognition of partially occluded objects, consistent with psychophysical theory. Furthermore, they suggest that area V4 participates in the representation of the relevant sensory signals and the generation of decision signals underlying discrimination. PMID:24948811

Transverse fields to tune an Ising-nematic quantum phase transition [Transverse fields to tune an Ising-nematic quantum critical transition

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

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.

Here, the paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated withmore » spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.« less

Transverse fields to tune an Ising-nematic quantum phase transition [Transverse fields to tune an Ising-nematic quantum critical transition

DOE PAGES

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.; ...

2017-12-05

Here, the paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated withmore » spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.« less

Isotope enrichment by frequency-tripled temperature tuned neodymium laser photolysis of formaldehyde

DOEpatents

Marling, John B.

1977-01-01

Enrichment of carbon, hydrogen and/or oxygen isotopes by means of isotopically selective photo-predissociation of formaldehyde is achieved by irradiation provided by a frequency-tripled, temperature tuned neodymium laser.

Polarization and angle insensitive dual-band bandpass frequency selective surface using all-dielectric metamaterials

NASA Astrophysics Data System (ADS)

Yu, Fei; Wang, Jun; Wang, Jiafu; Ma, Hua; Du, Hongliang; Xu, Zhuo; Qu, Shaobo

2016-04-01

In this paper, we demonstrate a dual-band bandpass all-dielectric frequency selective surface (FSS), the building elements of which are high-permittivity ceramic particles rather than metallic patterns. With proper structural design and parameter adjustment, the resonant frequency can be tuned at will. Dual-band bandpass response can be realized due to the coupling between electric and magnetic resonances. As an example, a dual-band bandpass FSS is designed in Ku band, which is composed of two-dimensional periodic arrays of complementary quatrefoil structures (CQS) cut from dielectric plates. Moreover, cylindrical dielectric resonators are introduced and placed in the center of each CQS to broaden the bandwidth and to sharpen the cut-off frequency. Theoretical analysis shows that the bandpass response arises from impedance matching caused by electric and magnetic resonances. In addition, effective electromagnetic parameters and dynamic field distributions are presented to explain the mechanism of impedance matching. The proposed FSS has the merits of polarization independence, stable transmission, and sharp roll-off frequency. The method can also be used to design all-dielectric FSSs with continuum structures at other frequencies.

DEApp: an interactive web interface for differential expression analysis of next generation sequence data.

PubMed

Li, Yan; Andrade, Jorge

2017-01-01

A growing trend in the biomedical community is the use of Next Generation Sequencing (NGS) technologies in genomics research. The complexity of downstream differential expression (DE) analysis is however still challenging, as it requires sufficient computer programing and command-line knowledge. Furthermore, researchers often need to evaluate and visualize interactively the effect of using differential statistical and error models, assess the impact of selecting different parameters and cutoffs, and finally explore the overlapping consensus of cross-validated results obtained with different methods. This represents a bottleneck that slows down or impedes the adoption of NGS technologies in many labs. We developed DEApp, an interactive and dynamic web application for differential expression analysis of count based NGS data. This application enables models selection, parameter tuning, cross validation and visualization of results in a user-friendly interface. DEApp enables labs with no access to full time bioinformaticians to exploit the advantages of NGS applications in biomedical research. This application is freely available at https://yanli.shinyapps.io/DEAppand https://gallery.shinyapps.io/DEApp.

Parameter optimisation for a better representation of drought by LSMs: inverse modelling vs. sequential data assimilation

NASA Astrophysics Data System (ADS)

Dewaele, Hélène; Munier, Simon; Albergel, Clément; Planque, Carole; Laanaia, Nabil; Carrer, Dominique; Calvet, Jean-Christophe

2017-09-01

Soil maximum available water content (MaxAWC) is a key parameter in land surface models (LSMs). However, being difficult to measure, this parameter is usually uncertain. This study assesses the feasibility of using a 15-year (1999-2013) time series of satellite-derived low-resolution observations of leaf area index (LAI) to estimate MaxAWC for rainfed croplands over France. LAI interannual variability is simulated using the CO2-responsive version of the Interactions between Soil, Biosphere and Atmosphere (ISBA) LSM for various values of MaxAWC. Optimal value is then selected by using (1) a simple inverse modelling technique, comparing simulated and observed LAI and (2) a more complex method consisting in integrating observed LAI in ISBA through a land data assimilation system (LDAS) and minimising LAI analysis increments. The evaluation of the MaxAWC estimates from both methods is done using simulated annual maximum above-ground biomass (Bag) and straw cereal grain yield (GY) values from the Agreste French agricultural statistics portal, for 45 administrative units presenting a high proportion of straw cereals. Significant correlations (p value < 0.01) between Bag and GY are found for up to 36 and 53 % of the administrative units for the inverse modelling and LDAS tuning methods, respectively. It is found that the LDAS tuning experiment gives more realistic values of MaxAWC and maximum Bag than the inverse modelling experiment. Using undisaggregated LAI observations leads to an underestimation of MaxAWC and maximum Bag in both experiments. Median annual maximum values of disaggregated LAI observations are found to correlate very well with MaxAWC.

ANSYS simulation of the capacitance coupling of quartz tuning fork gyroscope

NASA Astrophysics Data System (ADS)

Zhang, Qing; Feng, Lihui; Zhao, Ke; Cui, Fang; Sun, Yu-nan

2013-12-01

Coupling error is one of the main error sources of the quartz tuning fork gyroscope. The mechanism of capacitance coupling error is analyzed in this article. Finite Element Method (FEM) is used to simulate the structure of the quartz tuning fork by ANSYS software. The voltage output induced by the capacitance coupling is simulated with the harmonic analysis and characteristics of electrical and mechanical parameters influenced by the capacitance coupling between drive electrodes and sense electrodes are discussed with the transient analysis.

Monolithic single mode interband cascade lasers with wide wavelength tunability

NASA Astrophysics Data System (ADS)

von Edlinger, M.; Weih, R.; Scheuermann, J.; Nähle, L.; Fischer, M.; Koeth, J.; Kamp, M.; Höfling, S.

2016-11-01

Monolithic two-section interband cascade lasers offering a wide wavelength tunability in the wavelength range around 3.7 μm are presented. Stable single mode emission in several wavelength channels was realized using the concept of binary superimposed gratings and two-segment Vernier-tuning. The wavelength selective elements in the two segments were based on specially designed lateral metal grating structures defined by electron beam lithography. A dual-step dry etch process provided electrical separation between the segments. Individual current control of the segments allowed wavelength channel selection as well as continuous wavelength tuning within channels. A discontinuous tuning range extending over 158 nm in up to six discrete wavelength channels was achieved. Mode hop free wavelength tuning up to 14 nm was observed within one channel. The devices can be operated in continuous wave mode up to 30 °C with the output powers of 3.5 mW around room temperature.

Optimizing of a high-order digital filter using PSO algorithm

NASA Astrophysics Data System (ADS)

Xu, Fuchun

2018-04-01

A self-adaptive high-order digital filter, which offers opportunity to simplify the process of tuning parameters and further improve the noise performance, is presented in this paper. The parameters of traditional digital filter are mainly tuned by complex calculation, whereas this paper presents a 5th order digital filter to obtain outstanding performance and the parameters of the proposed filter are optimized by swarm intelligent algorithm. Simulation results with respect to the proposed 5th order digital filter, SNR>122dB and the noise floor under -170dB are obtained in frequency range of [5-150Hz]. In further simulation, the robustness of the proposed 5th order digital is analyzed.

CALIBRATING NON-CONVEX PENALIZED REGRESSION IN ULTRA-HIGH DIMENSION.

PubMed

Wang, Lan; Kim, Yongdai; Li, Runze

2013-10-01

We investigate high-dimensional non-convex penalized regression, where the number of covariates may grow at an exponential rate. Although recent asymptotic theory established that there exists a local minimum possessing the oracle property under general conditions, it is still largely an open problem how to identify the oracle estimator among potentially multiple local minima. There are two main obstacles: (1) due to the presence of multiple minima, the solution path is nonunique and is not guaranteed to contain the oracle estimator; (2) even if a solution path is known to contain the oracle estimator, the optimal tuning parameter depends on many unknown factors and is hard to estimate. To address these two challenging issues, we first prove that an easy-to-calculate calibrated CCCP algorithm produces a consistent solution path which contains the oracle estimator with probability approaching one. Furthermore, we propose a high-dimensional BIC criterion and show that it can be applied to the solution path to select the optimal tuning parameter which asymptotically identifies the oracle estimator. The theory for a general class of non-convex penalties in the ultra-high dimensional setup is established when the random errors follow the sub-Gaussian distribution. Monte Carlo studies confirm that the calibrated CCCP algorithm combined with the proposed high-dimensional BIC has desirable performance in identifying the underlying sparsity pattern for high-dimensional data analysis.

CALIBRATING NON-CONVEX PENALIZED REGRESSION IN ULTRA-HIGH DIMENSION

PubMed Central

Wang, Lan; Kim, Yongdai; Li, Runze

2014-01-01

We investigate high-dimensional non-convex penalized regression, where the number of covariates may grow at an exponential rate. Although recent asymptotic theory established that there exists a local minimum possessing the oracle property under general conditions, it is still largely an open problem how to identify the oracle estimator among potentially multiple local minima. There are two main obstacles: (1) due to the presence of multiple minima, the solution path is nonunique and is not guaranteed to contain the oracle estimator; (2) even if a solution path is known to contain the oracle estimator, the optimal tuning parameter depends on many unknown factors and is hard to estimate. To address these two challenging issues, we first prove that an easy-to-calculate calibrated CCCP algorithm produces a consistent solution path which contains the oracle estimator with probability approaching one. Furthermore, we propose a high-dimensional BIC criterion and show that it can be applied to the solution path to select the optimal tuning parameter which asymptotically identifies the oracle estimator. The theory for a general class of non-convex penalties in the ultra-high dimensional setup is established when the random errors follow the sub-Gaussian distribution. Monte Carlo studies confirm that the calibrated CCCP algorithm combined with the proposed high-dimensional BIC has desirable performance in identifying the underlying sparsity pattern for high-dimensional data analysis. PMID:24948843

Implications for New Physics from Fine-Tuning Arguments: II. Little Higgs Models

NASA Astrophysics Data System (ADS)

Casas, J. A.; Espinosa, J. R.; Hidalgo, I.

2005-03-01

We examine the fine-tuning associated to electroweak breaking in Little Higgs scenarios and find it to be always substantial and, generically, much higher than suggested by the rough estimates usually made. This is due to implicit tunings between parameters that can be overlooked at first glance but show up in a more systematic analysis. Focusing on four popular and representative Little Higgs scenarios, we find that the fine-tuning is essentially comparable to that of the Little Hierarchy problem of the Standard Model (which these scenarios attempt to solve) and higher than in supersymmetric models. This does not demonstrate that all Little Higgs models are fine-tuned, but stresses the need of a careful analysis of this issue in model-building before claiming that a particular model is not fine-tuned. In this respect we identify the main sources of potential fine-tuning that should be watched out for, in order to construct a successful Little Higgs model, which seems to be a non-trivial goal.

Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation

PubMed Central

Li, Geng; Zhang, Pengfei; Wei, Guo; Xie, Yuanping; Yu, Xudong; Long, Xingwu

2015-01-01

To further improve ring laser gyroscope (RLG) bias stability, a multiple-point temperature gradient algorithm is proposed for RLG bias compensation in this paper. Based on the multiple-point temperature measurement system, a complete thermo-image of the RLG block is developed. Combined with the multiple-point temperature gradients between different points of the RLG block, the particle swarm optimization algorithm is used to tune the support vector machine (SVM) parameters, and an optimized design for selecting the thermometer locations is also discussed. The experimental results validate the superiority of the introduced method and enhance the precision and generalizability in the RLG bias compensation model. PMID:26633401

Spatial Moran models, II: cancer initiation in spatially structured tissue

PubMed Central

Foo, J; Leder, K

2016-01-01

We study the accumulation and spread of advantageous mutations in a spatial stochastic model of cancer initiation on a lattice. The parameters of this general model can be tuned to study a variety of cancer types and genetic progression pathways. This investigation contributes to an understanding of how the selective advantage of cancer cells together with the rates of mutations driving cancer, impact the process and timing of carcinogenesis. These results can be used to give insights into tumor heterogeneity and the “cancer field effect,” the observation that a malignancy is often surrounded by cells that have undergone premalignant transformation. PMID:26126947

Portable receiver for radar detection

DOEpatents

Lopes, Christopher D.; Kotter, Dale K.

2008-10-14

Various embodiments are described relating to a portable antenna-equipped device for multi-band radar detection. The detection device includes a plurality of antennas on a flexible substrate, a detection-and-control circuit, an indicator and a power source. The antenna may include one or more planar lithographic antennas that may be fabricated on a thin-film substrate. Each antenna may be tuned to a different selection frequency or band. The antennas may include a bolometer for radar detection. Each antenna may include a frequency selective surface for tuning to the selection frequency.

Automated respiratory cycles selection is highly specific and improves respiratory mechanics analysis.

PubMed

Rigo, Vincent; Graas, Estelle; Rigo, Jacques

2012-07-01

Selected optimal respiratory cycles should allow calculation of respiratory mechanic parameters focusing on patient-ventilator interaction. New computer software automatically selecting optimal breaths and respiratory mechanics derived from those cycles are evaluated. Retrospective study. University level III neonatal intensive care unit. Ten mins synchronized intermittent mandatory ventilation and assist/control ventilation recordings from ten newborns. The ventilator provided respiratory mechanic data (ventilator respiratory cycles) every 10 secs. Pressure, flow, and volume waves and pressure-volume, pressure-flow, and volume-flow loops were reconstructed from continuous pressure-volume recordings. Visual assessment determined assisted leak-free optimal respiratory cycles (selected respiratory cycles). New software graded the quality of cycles (automated respiratory cycles). Respiratory mechanic values were derived from both sets of optimal cycles. We evaluated quality selection and compared mean values and their variability according to ventilatory mode and respiratory mechanic provenance. To assess discriminating power, all 45 "t" values obtained from interpatient comparisons were compared for each respiratory mechanic parameter. A total of 11,724 breaths are evaluated. Automated respiratory cycle/selected respiratory cycle selections agreement is high: 88% of maximal κ with linear weighting. Specificity and positive predictive values are 0.98 and 0.96, respectively. Averaged values are similar between automated respiratory cycle and ventilator respiratory cycle. C20/C alone is markedly decreased in automated respiratory cycle (1.27 ± 0.37 vs. 1.81 ± 0.67). Tidal volume apparent similarity disappears in assist/control: automated respiratory cycle tidal volume (4.8 ± 1.0 mL/kg) is significantly lower than for ventilator respiratory cycle (5.6 ± 1.8 mL/kg). Coefficients of variation decrease for all automated respiratory cycle parameters in all infants. "t" values from ventilator respiratory cycle data are two to three times higher than ventilator respiratory cycles. Automated selection is highly specific. Automated respiratory cycle reflects most the interaction of both ventilator and patient. Improving discriminating power of ventilator monitoring will likely help in assessing disease status and following trends. Averaged parameters derived from automated respiratory cycles are more precise and could be displayed by ventilators to improve real-time fine tuning of ventilator settings.

Shape-selective synthesis of non-micellar cobalt oxide (CoO) nanomaterials by microwave irradiations

NASA Astrophysics Data System (ADS)

Kundu, Subrata; Jayachandran, M.

2013-04-01

Shape-selective formation of CoO nanoparticles has been developed using a simple one-step in situ non-micellar microwave (MW) heating method. CoO NPs were synthesized by mixing aqueous CoCl2·6H2O solution with poly (vinyl) alcohol (PVA) in the presence of sodium hydroxide (NaOH). The reaction mixture was irradiated using MW for a total time of 2 min. This process exclusively generated different shapes like nanosphere, nanosheet, and nanodendrite structures just by tuning the Co(II) ion to PVA molar ratios and controlling other reaction parameters. The proposed synthesis method is efficient, straightforward, reproducible, and robust. Other than in catalysis, these cobalt oxide nanomaterials can be used for making pigments, battery materials, for developing solid state sensors, and also as an anisotropy source for magnetic recording.

Cochlear-implant spatial selectivity with monopolar, bipolar and tripolar stimulation.

PubMed

Zhu, Ziyan; Tang, Qing; Zeng, Fan-Gang; Guan, Tian; Ye, Datian

2012-01-01

Sharp spatial selectivity is critical to auditory performance, particularly in pitch-related tasks. Most contemporary cochlear implants have employed monopolar stimulation that produces broad electric fields, which presumably contribute to poor pitch and pitch-related performance by implant users. Bipolar or tripolar stimulation can generate focused electric fields but requires higher current to reach threshold and, more interestingly, has not produced any apparent improvement in cochlear-implant performance. The present study addressed this dilemma by measuring psychophysical and physiological spatial selectivity with both broad and focused stimulations in the same cohort of subjects. Different current levels were adjusted by systematically measuring loudness growth for each stimulus, each stimulation mode, and in each subject. Both psychophysical and physiological measures showed that, although focused stimulation produced significantly sharper spatial tuning than monopolar stimulation, it could shift the tuning position or even split the tuning tips. The altered tuning with focused stimulation is interpreted as a result of poor electrode-to-neuron interface in the cochlea, and is suggested to be mainly responsible for the lack of consistent improvement in implant performance. A linear model could satisfactorily quantify the psychophysical and physiological data and derive the tuning width. Significant correlation was found between the individual physiological and psychophysical tuning widths, and the correlation was improved by log-linearly transforming the physiological data to predict the psychophysical data. Because the physiological measure took only one-tenth of the time of the psychophysical measure, the present model is of high clinical significance in terms of predicting and improving cochlear-implant performance. Copyright © 2011 Elsevier B.V. All rights reserved.

Cochlear Implant Spatial Selectivity with Monopolar, Bipolar and Tripolar Stimulation

PubMed Central

Zhu, Ziyan; Tang, Qing; Zeng, Fan-Gang; Guan, Tian; Ye, Datian

2011-01-01

Sharp spatial selectivity is critical to auditory performance, particularly in pitch related tasks. Most contemporary cochlear implants have employed monopolar stimulation that produces broad electric fields, which presumably contribute to poor pitch and pitch-related performance by implant users. Bipolar or tripolar stimulation can generate focused electric fields but requires higher current to reach threshold and, more interestingly, has not produced any apparent improvement in cochlear implant performance. The present study addressed this dilemma by measuring psychophysical and physiological spatial selectivity with both broad and focused stimulations in the same cohort of subjects. Different current levels were adjusted by systematically measuring loudness growth for each stimulus, each stimulation mode, and in each subject. Both psychophysical and physiological measures showed that, although focused stimulation produced significantly sharper spatial tuning than monopolar stimulation, it could shift the tuning position or even split the tuning tips. The altered tuning with focused stimulation is interpreted as a result of poor electrode-to-neuron interface in the cochlea, and is suggested to be mainly responsible for the lack of consistent improvement in implant performance. A linear model could satisfactorily quantify the psychophysical and physiological data and derive the tuning width. Significant correlation was found between the individual physiological and psychophysical tuning widths, and the correlation was improved by log-linearly transforming the physiological data to predict the psychophysical data. Because the physiological measure took only one-tenth of the time of the psychophysical measure, the present model is of high clinical significance in terms of predicting and improving cochlear implant performance. PMID:22138630

Neural Representation of a Target Auditory Memory in a Cortico-Basal Ganglia Pathway

PubMed Central

Bottjer, Sarah W.

2013-01-01

Vocal learning in songbirds, like speech acquisition in humans, entails a period of sensorimotor integration during which vocalizations are evaluated via auditory feedback and progressively refined to achieve an imitation of memorized vocal sounds. This process requires the brain to compare feedback of current vocal behavior to a memory of target vocal sounds. We report the discovery of two distinct populations of neurons in a cortico-basal ganglia circuit of juvenile songbirds (zebra finches, Taeniopygia guttata) during vocal learning: (1) one in which neurons are selectively tuned to memorized sounds and (2) another in which neurons are selectively tuned to self-produced vocalizations. These results suggest that neurons tuned to learned vocal sounds encode a memory of those target sounds, whereas neurons tuned to self-produced vocalizations encode a representation of current vocal sounds. The presence of neurons tuned to memorized sounds is limited to early stages of sensorimotor integration: after learning, the incidence of neurons encoding memorized vocal sounds was greatly diminished. In contrast to this circuit, neurons known to drive vocal behavior through a parallel cortico-basal ganglia pathway show little selective tuning until late in learning. One interpretation of these data is that representations of current and target vocal sounds in the shell circuit are used to compare ongoing patterns of vocal feedback to memorized sounds, whereas the parallel core circuit has a motor-related role in learning. Such a functional subdivision is similar to mammalian cortico-basal ganglia pathways in which associative-limbic circuits mediate goal-directed responses, whereas sensorimotor circuits support motor aspects of learning. PMID:24005299

Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID.

PubMed

Hammad, Mohanad M; Elshenawy, Ahmed K; El Singaby, M I

2017-01-01

In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results from the hydrodynamics and the coupled AUV dynamics makes the design of a stable controller a very difficult task. In this study, the control scheme in a simulation environment is validated using dynamic and kinematic equations for the AUV model and hydrodynamic damping equations. An AUV configuration with eight thrusters and an inverse kinematic model from a previous work is utilized in the simulation. In the proposed controller, Mamdani fuzzy rules are used to tune the parameters of the PID. Nonlinear fuzzy Gaussian membership functions are selected to give better performance and response in the non-linear system. A control architecture with two feedback loops is designed such that the inner loop is for velocity control and outer loop is for position control. Several test scenarios are executed to validate the controller performance including different complex trajectories with and without injection of ocean current disturbances. A comparison between the proposed FPID controller and the conventional PID controller is studied and shows that the FPID controller has a faster response to the reference signal and more stable behavior in a disturbed non-linear environment.

Trajectory following and stabilization control of fully actuated AUV using inverse kinematics and self-tuning fuzzy PID

PubMed Central

Elshenawy, Ahmed K.; El Singaby, M.I.

2017-01-01

In this work a design for self-tuning non-linear Fuzzy Proportional Integral Derivative (FPID) controller is presented to control position and speed of Multiple Input Multiple Output (MIMO) fully-actuated Autonomous Underwater Vehicles (AUV) to follow desired trajectories. Non-linearity that results from the hydrodynamics and the coupled AUV dynamics makes the design of a stable controller a very difficult task. In this study, the control scheme in a simulation environment is validated using dynamic and kinematic equations for the AUV model and hydrodynamic damping equations. An AUV configuration with eight thrusters and an inverse kinematic model from a previous work is utilized in the simulation. In the proposed controller, Mamdani fuzzy rules are used to tune the parameters of the PID. Nonlinear fuzzy Gaussian membership functions are selected to give better performance and response in the non-linear system. A control architecture with two feedback loops is designed such that the inner loop is for velocity control and outer loop is for position control. Several test scenarios are executed to validate the controller performance including different complex trajectories with and without injection of ocean current disturbances. A comparison between the proposed FPID controller and the conventional PID controller is studied and shows that the FPID controller has a faster response to the reference signal and more stable behavior in a disturbed non-linear environment. PMID:28683071

Stabilization and analytical tuning rule of double-loop control scheme for unstable dead-time process

NASA Astrophysics Data System (ADS)

Ugon, B.; Nandong, J.; Zang, Z.

2017-06-01

The presence of unstable dead-time systems in process plants often leads to a daunting challenge in the design of standard PID controllers, which are not only intended to provide close-loop stability but also to give good performance-robustness overall. In this paper, we conduct stability analysis on a double-loop control scheme based on the Routh-Hurwitz stability criteria. We propose to use this unstable double-loop control scheme which employs two P/PID controllers to control first-order or second-order unstable dead-time processes typically found in process industries. Based on the Routh-Hurwitz stability necessary and sufficient criteria, we establish several stability regions which enclose within them the P/PID parameter values that guarantee close-loop stability of the double-loop control scheme. A systematic tuning rule is developed for the purpose of obtaining the optimal P/PID parameter values within the established regions. The effectiveness of the proposed tuning rule is demonstrated using several numerical examples and the result are compared with some well-established tuning methods reported in the literature.

CO 2 hydrogenation over oxide-supported PtCo catalysts: The role of the oxide support in determining the product selectivity

DOE PAGES

Kattel, Shyam; Yu, Weiting; Yang, Xiaofang; ...

2016-05-09

By simply changing the oxide support, the selectivity of a metal–oxide catalysts can be tuned. For the CO 2 hydrogenation over PtCo bimetallic catalysts supported on different reducible oxides (CeO 2, ZrO 2, and TiO 2), replacing a TiO 2 support by CeO 2 or ZrO 2 selectively strengthens the binding of C,O-bound and O-bound species at the PtCo–oxide interface, leading to a different product selectivity. Lastly, these results reveal mechanistic insights into how the catalytic performance of metal–oxide catalysts can be fine-tuned.

Evaluation of the channelized Hotelling observer with an internal-noise model in a train-test paradigm for cardiac SPECT defect detection.

PubMed

Brankov, Jovan G

2013-10-21

The channelized Hotelling observer (CHO) has become a widely used approach for evaluating medical image quality, acting as a surrogate for human observers in early-stage research on assessment and optimization of imaging devices and algorithms. The CHO is typically used to measure lesion detectability. Its popularity stems from experiments showing that the CHO's detection performance can correlate well with that of human observers. In some cases, CHO performance overestimates human performance; to counteract this effect, an internal-noise model is introduced, which allows the CHO to be tuned to match human-observer performance. Typically, this tuning is achieved using example data obtained from human observers. We argue that this internal-noise tuning step is essentially a model training exercise; therefore, just as in supervised learning, it is essential to test the CHO with an internal-noise model on a set of data that is distinct from that used to tune (train) the model. Furthermore, we argue that, if the CHO is to provide useful insights about new imaging algorithms or devices, the test data should reflect such potential differences from the training data; it is not sufficient simply to use new noise realizations of the same imaging method. Motivated by these considerations, the novelty of this paper is the use of new model selection criteria to evaluate ten established internal-noise models, utilizing four different channel models, in a train-test approach. Though not the focus of the paper, a new internal-noise model is also proposed that outperformed the ten established models in the cases tested. The results, using cardiac perfusion SPECT data, show that the proposed train-test approach is necessary, as judged by the newly proposed model selection criteria, to avoid spurious conclusions. The results also demonstrate that, in some models, the optimal internal-noise parameter is very sensitive to the choice of training data; therefore, these models are prone to overfitting, and will not likely generalize well to new data. In addition, we present an alternative interpretation of the CHO as a penalized linear regression wherein the penalization term is defined by the internal-noise model.

A universal multilingual weightless neural network tagger via quantitative linguistics.

PubMed

Carneiro, Hugo C C; Pedreira, Carlos E; França, Felipe M G; Lima, Priscila M V

2017-07-01

In the last decade, given the availability of corpora in several distinct languages, research on multilingual part-of-speech tagging started to grow. Amongst the novelties there is mWANN-Tagger (multilingual weightless artificial neural network tagger), a weightless neural part-of-speech tagger capable of being used for mostly-suffix-oriented languages. The tagger was subjected to corpora in eight languages of quite distinct natures and had a remarkable accuracy with very low sample deviation in every one of them, indicating the robustness of weightless neural systems for part-of-speech tagging tasks. However, mWANN-Tagger needed to be tuned for every new corpus, since each one required a different parameter configuration. For mWANN-Tagger to be truly multilingual, it should be usable for any new language with no need of parameter tuning. This article proposes a study that aims to find a relation between the lexical diversity of a language and the parameter configuration that would produce the best performing mWANN-Tagger instance. Preliminary analyses suggested that a single parameter configuration may be applied to the eight aforementioned languages. The mWANN-Tagger instance produced by this configuration was as accurate as the language-dependent ones obtained through tuning. Afterwards, the weightless neural tagger was further subjected to new corpora in languages that range from very isolating to polysynthetic ones. The best performing instances of mWANN-Tagger are again the ones produced by the universal parameter configuration. Hence, mWANN-Tagger can be applied to new corpora with no need of parameter tuning, making it a universal multilingual part-of-speech tagger. Further experiments with Universal Dependencies treebanks reveal that mWANN-Tagger may be extended and that it has potential to outperform most state-of-the-art part-of-speech taggers if better word representations are provided. Copyright © 2017 Elsevier Ltd. All rights reserved.

Three-dimensional motion aftereffects reveal distinct direction-selective mechanisms for binocular processing of motion through depth.

PubMed

Czuba, Thaddeus B; Rokers, Bas; Guillet, Kyle; Huk, Alexander C; Cormack, Lawrence K

2011-09-26

Motion aftereffects are historically considered evidence for neuronal populations tuned to specific directions of motion. Despite a wealth of motion aftereffect studies investigating 2D (frontoparallel) motion mechanisms, there is a remarkable dearth of psychophysical evidence for neuronal populations selective for the direction of motion through depth (i.e., tuned to 3D motion). We compared the effects of prolonged viewing of unidirectional motion under dichoptic and monocular conditions and found large 3D motion aftereffects that could not be explained by simple inheritance of 2D monocular aftereffects. These results (1) demonstrate the existence of neurons tuned to 3D motion as distinct from monocular 2D mechanisms, (2) show that distinct 3D direction selectivity arises from both interocular velocity differences and changing disparities over time, and (3) provide a straightforward psychophysical tool for further probing 3D motion mechanisms. © ARVO

Three-dimensional motion aftereffects reveal distinct direction-selective mechanisms for binocular processing of motion through depth

PubMed Central

Czuba, Thaddeus B.; Rokers, Bas; Guillet, Kyle; Huk, Alexander C.; Cormack, Lawrence K.

2013-01-01

Motion aftereffects are historically considered evidence for neuronal populations tuned to specific directions of motion. Despite a wealth of motion aftereffect studies investigating 2D (frontoparallel) motion mechanisms, there is a remarkable dearth of psychophysical evidence for neuronal populations selective for the direction of motion through depth (i.e., tuned to 3D motion). We compared the effects of prolonged viewing of unidirectional motion under dichoptic and monocular conditions and found large 3D motion aftereffects that could not be explained by simple inheritance of 2D monocular aftereffects. These results (1) demonstrate the existence of neurons tuned to 3D motion as distinct from monocular 2D mechanisms, (2) show that distinct 3D direction selectivity arises from both interocular velocity differences and changing disparities over time, and (3) provide a straightforward psychophysical tool for further probing 3D motion mechanisms. PMID:21945967

On-Chip Electrolytic Chemistry for the Tuning of Graphene Devices

NASA Astrophysics Data System (ADS)

Schmucker, Scott; Ruppalt, Laura; Culbertson, James; Do, Jae Won; Lyding, Joseph; Robinson, Jeremy; Cress, Cory

2015-03-01

The inherent interfacial nature of two-dimensional materials has motivated the tuning of these films by choice of substrate or chemical functionalization. Such parameters are generally selected during fabrication, and therefore remain static during device operation. However, the possibility of dynamic chemistry in a tunable solid-state system will enable the development of new devices which fully leverage the rich chemistry of graphenic materials. Here, we fabricate a novel device for localized, dynamic doping and functionalization of graphene that is compatible with CMOS processing. The device is enabled by a top-gated, solid electrochemical cell designed with calcium fluoride (CaF2) substituting the oxide of a traditional MOSFET. When the CaF2 is gated, F flows from cathode to anode, segregating Ca and F. In this work, one electrode is graphene. When saturated with fluorine, graphene undergoes covalent modification, becoming a wide-bandgap semiconductor. In contrast, when functionalized with calcium or dilute fluorine, graphene is electron or hole doped, respectively. With transport, Raman, and XPS, we demonstrate this lithographically localized and reversible modulation of graphene's electronic and chemical character.

LS-APC v1.0: a tuning-free method for the linear inverse problem and its application to source-term determination

NASA Astrophysics Data System (ADS)

Tichý, Ondřej; Šmídl, Václav; Hofman, Radek; Stohl, Andreas

2016-11-01

Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. It is typically formalized as an inverse problem using a linear model that can explain observable quantities (e.g., concentrations or deposition values) as a product of the source-receptor sensitivity (SRS) matrix obtained from an atmospheric transport model multiplied by the unknown source-term vector. Since this problem is typically ill-posed, current state-of-the-art methods are based on regularization of the problem and solution of a formulated optimization problem. This procedure depends on manual settings of uncertainties that are often very poorly quantified, effectively making them tuning parameters. We formulate a probabilistic model, that has the same maximum likelihood solution as the conventional method using pre-specified uncertainties. Replacement of the maximum likelihood solution by full Bayesian estimation also allows estimation of all tuning parameters from the measurements. The estimation procedure is based on the variational Bayes approximation which is evaluated by an iterative algorithm. The resulting method is thus very similar to the conventional approach, but with the possibility to also estimate all tuning parameters from the observations. The proposed algorithm is tested and compared with the standard methods on data from the European Tracer Experiment (ETEX) where advantages of the new method are demonstrated. A MATLAB implementation of the proposed algorithm is available for download.

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

Liu, Shengqiang; Li, Jie; Yu, Junsheng, E-mail: jsyu@uestc.edu.cn

A color tuning index (I{sub CT}) parameter for evaluating the color change capability of color-tunable organic light-emitting diodes (CT-OLEDs) was proposed and formulated. And a series of CT-OLEDs, consisting of five different carrier/exciton adjusting interlayers (C/EALs) inserted between two complementary emitting layers, were fabricated and applied to disclose the relationship between I{sub CT} and C/EALs. The result showed that the trend of electroluminescence spectra behavior in CT-OLEDs has good accordance with I{sub CT} values, indicating that the I{sub CT} parameter is feasible for the evaluation of color variation. Meanwhile, by changing energy level and C/EAL thickness, the optimized device withmore » the widest color tuning range was based on N,N′-dicarbazolyl-3,5-benzene C/EAL, exhibiting the highest I{sub CT} value of 41.2%. Based on carrier quadratic hopping theory and exciton transfer model, two fitting I{sub CT} formulas derived from the highest occupied molecular orbital (HOMO) energy level and triplet energy level were simulated. Finally, a color tuning prediction (CTP) model was developed to deduce the I{sub CT} via C/EAL HOMO and triplet energy levels, and verified by the fabricated OLEDs with five different C/EALs. We believe that the CTP model assisted with I{sub CT} parameter will be helpful for fabricating high performance CT-OLEDs with a broad range of color tuning.« less

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

NASA Technical Reports Server (NTRS)

Armstrong, Jeffrey B.; Simon, Donald L.

2012-01-01

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Fast and wide tuning wavelength-swept source based on dispersion-tuned fiber optical parametric oscillator.

PubMed

Zhou, Yue; Cheung, Kim K Y; Li, Qin; Yang, Sigang; Chui, P C; Wong, Kenneth K Y

2010-07-15

We demonstrate a dispersion-tuned fiber optical parametric oscillator (FOPO)-based swept source with a sweep rate of 40 kHz and a wavelength tuning range of 109 nm around 1550 nm. The cumulative speed exceeds 4,000,000 nm/s. The FOPO is pumped by a sinusoidally modulated pump, which is driven by a clock sweeping linearly from 1 to 1.0006 GHz. A spool of dispersion-compensating fiber is added inside the cavity to perform dispersion tuning. The instantaneous linewidth is 0.8 nm without the use of any wavelength selective element inside the cavity. 1 GHz pulses with pulse width of 150 ps are generated.

Selection of optimum median-filter-based ambiguity removal algorithm parameters for NSCAT. [NASA scatterometer

NASA Technical Reports Server (NTRS)

Shaffer, Scott; Dunbar, R. Scott; Hsiao, S. Vincent; Long, David G.

1989-01-01

The NASA Scatterometer, NSCAT, is an active spaceborne radar designed to measure the normalized radar backscatter coefficient (sigma0) of the ocean surface. These measurements can, in turn, be used to infer the surface vector wind over the ocean using a geophysical model function. Several ambiguous wind vectors result because of the nature of the model function. A median-filter-based ambiguity removal algorithm will be used by the NSCAT ground data processor to select the best wind vector from the set of ambiguous wind vectors. This process is commonly known as dealiasing or ambiguity removal. The baseline NSCAT ambiguity removal algorithm and the method used to select the set of optimum parameter values are described. An extensive simulation of the NSCAT instrument and ground data processor provides a means of testing the resulting tuned algorithm. This simulation generates the ambiguous wind-field vectors expected from the instrument as it orbits over a set of realistic meoscale wind fields. The ambiguous wind field is then dealiased using the median-based ambiguity removal algorithm. Performance is measured by comparison of the unambiguous wind fields with the true wind fields. Results have shown that the median-filter-based ambiguity removal algorithm satisfies NSCAT mission requirements.

Bifilar analysis study, volume 1

NASA Technical Reports Server (NTRS)

Miao, W.; Mouzakis, T.

1980-01-01

A coupled rotor/bifilar/airframe analysis was developed and utilized to study the dynamic characteristics of the centrifugally tuned, rotor-hub-mounted, bifilar vibration absorber. The analysis contains the major components that impact the bifilar absorber performance, namely, an elastic rotor with hover aerodynamics, a flexible fuselage, and nonlinear individual degrees of freedom for each bifilar mass. Airspeed, rotor speed, bifilar mass and tuning variations are considered. The performance of the bifilar absorber is shown to be a function of its basic parameters: dynamic mass, damping and tuning, as well as the impedance of the rotor hub. The effect of the dissimilar responses of the individual bifilar masses which are caused by tolerance induced mass, damping and tuning variations is also examined.

Support vector machines and generalisation in HEP

NASA Astrophysics Data System (ADS)

Bevan, Adrian; Gamboa Goñi, Rodrigo; Hays, Jon; Stevenson, Tom

2017-10-01

We review the concept of Support Vector Machines (SVMs) and discuss examples of their use in a number of scenarios. Several SVM implementations have been used in HEP and we exemplify this algorithm using the Toolkit for Multivariate Analysis (TMVA) implementation. We discuss examples relevant to HEP including background suppression for H → τ + τ - at the LHC with several different kernel functions. Performance benchmarking leads to the issue of generalisation of hyper-parameter selection. The avoidance of fine tuning (over training or over fitting) in MVA hyper-parameter optimisation, i.e. the ability to ensure generalised performance of an MVA that is independent of the training, validation and test samples, is of utmost importance. We discuss this issue and compare and contrast performance of hold-out and k-fold cross-validation. We have extended the SVM functionality and introduced tools to facilitate cross validation in TMVA and present results based on these improvements.

Plasma-enhanced atomic layer deposition of titanium oxynitrides films: A comparative spectroscopic and electrical study

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

Sowińska, Małgorzata, E-mail: malgorzata.sowinska@b-tu.de; Henkel, Karsten; Schmeißer, Dieter

2016-01-15

The process parameters' impact of the plasma-enhanced atomic layer deposition (PE-ALD) method on the oxygen to nitrogen (O/N) ratio in titanium oxynitride (TiO{sub x}N{sub y}) films was studied. Titanium(IV)isopropoxide in combination with NH{sub 3} plasma and tetrakis(dimethylamino)titanium by applying N{sub 2} plasma processes were investigated. Samples were characterized by the in situ spectroscopic ellipsometry, x-ray photoelectron spectroscopy, and electrical characterization (current–voltage: I-V and capacitance–voltage: C-V) methods. The O/N ratio in the TiO{sub x}N{sub y} films is found to be very sensitive for their electric properties such as conductivity, dielectric breakdown, and permittivity. Our results indicate that these PE-ALD film propertiesmore » can be tuned, via the O/N ratio, by the selection of the process parameters and precursor/coreactant combination.« less

Quadruped Robot Locomotion using a Global Optimization Stochastic Algorithm

NASA Astrophysics Data System (ADS)

Oliveira, Miguel; Santos, Cristina; Costa, Lino; Ferreira, Manuel

2011-09-01

The problem of tuning nonlinear dynamical systems parameters, such that the attained results are considered good ones, is a relevant one. This article describes the development of a gait optimization system that allows a fast but stable robot quadruped crawl gait. We combine bio-inspired Central Patterns Generators (CPGs) and Genetic Algorithms (GA). CPGs are modelled as autonomous differential equations, that generate the necessar y limb movement to perform the required walking gait. The GA finds parameterizations of the CPGs parameters which attain good gaits in terms of speed, vibration and stability. Moreover, two constraint handling techniques based on tournament selection and repairing mechanism are embedded in the GA to solve the proposed constrained optimization problem and make the search more efficient. The experimental results, performed on a simulated Aibo robot, demonstrate that our approach allows low vibration with a high velocity and wide stability margin for a quadruped slow crawl gait.

Nonlinear gearshifts control of dual-clutch transmissions during inertia phase.

PubMed

Hu, Yunfeng; Tian, Lu; Gao, Bingzhao; Chen, Hong

2014-07-01

In this paper, a model-based nonlinear gearshift controller is designed by the backstepping method to improve the shift quality of vehicles with a dual-clutch transmission (DCT). Considering easy-implementation, the controller is rearranged into a concise structure which contains a feedforward control and a feedback control. Then, robustness of the closed-loop error system is discussed in the framework of the input to state stability (ISS) theory, where model uncertainties are considered as the additive disturbance inputs. Furthermore, due to the application of the backstepping method, the closed-loop error system is ordered as a linear system. Using the linear system theory, a guideline for selecting the controller parameters is deduced which could reduce the workload of parameters tuning. Finally, simulation results and Hardware in the Loop (HiL) simulation are presented to validate the effectiveness of the designed controller. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Recursive Branching Simulated Annealing Algorithm

NASA Technical Reports Server (NTRS)

Bolcar, Matthew; Smith, J. Scott; Aronstein, David

2012-01-01

This innovation is a variation of a simulated-annealing optimization algorithm that uses a recursive-branching structure to parallelize the search of a parameter space for the globally optimal solution to an objective. The algorithm has been demonstrated to be more effective at searching a parameter space than traditional simulated-annealing methods for a particular problem of interest, and it can readily be applied to a wide variety of optimization problems, including those with a parameter space having both discrete-value parameters (combinatorial) and continuous-variable parameters. It can take the place of a conventional simulated- annealing, Monte-Carlo, or random- walk algorithm. In a conventional simulated-annealing (SA) algorithm, a starting configuration is randomly selected within the parameter space. The algorithm randomly selects another configuration from the parameter space and evaluates the objective function for that configuration. If the objective function value is better than the previous value, the new configuration is adopted as the new point of interest in the parameter space. If the objective function value is worse than the previous value, the new configuration may be adopted, with a probability determined by a temperature parameter, used in analogy to annealing in metals. As the optimization continues, the region of the parameter space from which new configurations can be selected shrinks, and in conjunction with lowering the annealing temperature (and thus lowering the probability for adopting configurations in parameter space with worse objective functions), the algorithm can converge on the globally optimal configuration. The Recursive Branching Simulated Annealing (RBSA) algorithm shares some features with the SA algorithm, notably including the basic principles that a starting configuration is randomly selected from within the parameter space, the algorithm tests other configurations with the goal of finding the globally optimal solution, and the region from which new configurations can be selected shrinks as the search continues. The key difference between these algorithms is that in the SA algorithm, a single path, or trajectory, is taken in parameter space, from the starting point to the globally optimal solution, while in the RBSA algorithm, many trajectories are taken; by exploring multiple regions of the parameter space simultaneously, the algorithm has been shown to converge on the globally optimal solution about an order of magnitude faster than when using conventional algorithms. Novel features of the RBSA algorithm include: 1. More efficient searching of the parameter space due to the branching structure, in which multiple random configurations are generated and multiple promising regions of the parameter space are explored; 2. The implementation of a trust region for each parameter in the parameter space, which provides a natural way of enforcing upper- and lower-bound constraints on the parameters; and 3. The optional use of a constrained gradient- search optimization, performed on the continuous variables around each branch s configuration in parameter space to improve search efficiency by allowing for fast fine-tuning of the continuous variables within the trust region at that configuration point.

The Opponent Channel Population Code of Sound Location Is an Efficient Representation of Natural Binaural Sounds

PubMed Central

Młynarski, Wiktor

2015-01-01

In mammalian auditory cortex, sound source position is represented by a population of broadly tuned neurons whose firing is modulated by sounds located at all positions surrounding the animal. Peaks of their tuning curves are concentrated at lateral position, while their slopes are steepest at the interaural midline, allowing for the maximum localization accuracy in that area. These experimental observations contradict initial assumptions that the auditory space is represented as a topographic cortical map. It has been suggested that a “panoramic” code has evolved to match specific demands of the sound localization task. This work provides evidence suggesting that properties of spatial auditory neurons identified experimentally follow from a general design principle- learning a sparse, efficient representation of natural stimuli. Natural binaural sounds were recorded and served as input to a hierarchical sparse-coding model. In the first layer, left and right ear sounds were separately encoded by a population of complex-valued basis functions which separated phase and amplitude. Both parameters are known to carry information relevant for spatial hearing. Monaural input converged in the second layer, which learned a joint representation of amplitude and interaural phase difference. Spatial selectivity of each second-layer unit was measured by exposing the model to natural sound sources recorded at different positions. Obtained tuning curves match well tuning characteristics of neurons in the mammalian auditory cortex. This study connects neuronal coding of the auditory space with natural stimulus statistics and generates new experimental predictions. Moreover, results presented here suggest that cortical regions with seemingly different functions may implement the same computational strategy-efficient coding. PMID:25996373

Controllability of the Coulomb charging energy in close-packed nanoparticle arrays.

PubMed

Duan, Chao; Wang, Ying; Sun, Jinling; Guan, Changrong; Grunder, Sergio; Mayor, Marcel; Peng, Lianmao; Liao, Jianhui

2013-11-07

We studied the electronic transport properties of metal nanoparticle arrays, particularly focused on the Coulomb charging energy. By comparison, we confirmed that it is more reasonable to estimate the Coulomb charging energy using the activation energy from the temperature-dependent zero-voltage conductance. Based on this, we systematically and comprehensively investigated the parameters that could be used to tune the Coulomb charging energy in nanoparticle arrays. We found that four parameters, including the particle core size, the inter-particle distance, the nearest neighboring number, and the dielectric constant of ligand molecules, could significantly tune the Coulomb charging energy.

Dirac gauginos, R symmetry and the 125 GeV Higgs

DOE PAGES

Bertuzzo, Enrico; Frugiuele, Claudia; Gregoire, Thomas; ...

2015-04-20

We study a supersymmetric scenario with a quasi exact R-symmetry in light of the discovery of a Higgs resonance with a mass of 125 GeV. In such a framework, the additional adjoint superfields, needed to give Dirac masses to the gauginos, contribute both to the Higgs mass and to electroweak precision observables. We then analyze the interplay between the two aspects, finding regions in parameter space in which the contributions to the precision observables are under control and a 125 GeV Higgs boson can be accommodated. Furthermore, we estimate the fine-tuning of the model finding regions of the parameter spacemore » still unexplored by the LHC with a fine-tuning considerably improved with respect to the minimal supersymmetric scenario. In particular, sizable non-holomorphic (non-supersoft) adjoints masses are required to reduce the fine-tuning.« less

Modelling and tuning for a time-delayed vibration absorber with friction

NASA Astrophysics Data System (ADS)

Zhang, Xiaoxu; Xu, Jian; Ji, Jinchen

2018-06-01

This paper presents an integrated analytical and experimental study to the modelling and tuning of a time-delayed vibration absorber (TDVA) with friction. In system modelling, this paper firstly applies the method of averaging to obtain the frequency response function (FRF), and then uses the derived FRF to evaluate the fitness of different friction models. After the determination of the system model, this paper employs the obtained FRF to evaluate the vibration absorption performance with respect to tunable parameters. A significant feature of the TDVA with friction is that its stability is dependent on the excitation parameters. To ensure the stability of the time-delayed control, this paper defines a sufficient condition for stability estimation. Experimental measurements show that the dynamic response of the TDVA with friction can be accurately predicted and the time-delayed control can be precisely achieved by using the modelling and tuning technique provided in this paper.

Fibre-coupled red diode-pumped Alexandrite TEM00 laser with single and double-pass end-pumping

NASA Astrophysics Data System (ADS)

Arbabzadah, E. A.; Damzen, M. J.

2016-06-01

We report the investigation of an Alexandrite laser end-pumped by a fibre-coupled red diode laser module. Power, efficiency, spatial, spectral, and wavelength tuning performance are studied as a function of pump and laser cavity parameters. It is the first demonstration, to our knowledge, of greater than 1 W power and also highest laser slope efficiency (44.2%) in a diode-pumped Alexandrite laser with diffraction-limited TEM00 mode operation. Spatial quality was excellent with beam propagation parameter M 2 ~ 1.05. Wavelength tuning from 737-796 nm was demonstrated using an intracavity birefringent tuning filter. Using a novel double pass end-pumping scheme to get efficient absorption of both polarisation states of the scrambled fibre-delivered diode pump, a total output coupled power of 1.66 W is produced in TEM00 mode with 40% slope efficiency.

Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network

PubMed Central

Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui

2012-01-01

This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. PMID:22778587

Difference between BPM reading one bunch and the average of multi-bunch in Booster

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

Xi Yang

2004-08-18

Differences caused by BPM reading one bunch and multi-bunch average need to be well understood before the beam parameters, such as the synchrotron tune, betatron tune, and chromaticity, are extracted from those BPM data. It is easy to perform such a study using numerical simulation other than modifying the BPM electronics.

Note: a transimpedance amplifier for remotely located quartz tuning forks.

PubMed

Kleinbaum, Ethan; Csáthy, Gábor A

2012-12-01

The cable capacitance in cryogenic and high vacuum applications of quartz tuning forks imposes severe constraints on the bandwidth and noise performance of the measurement. We present a single stage low noise transimpedance amplifier with a bandwidth exceeding 1 MHz and provide an in-depth analysis of the dependence of the amplifier parameters on the cable capacitance.

Effects of timbre and tempo change on memory for music.

PubMed

Halpern, Andrea R; Müllensiefen, Daniel

2008-09-01

We investigated the effects of different encoding tasks and of manipulations of two supposedly surface parameters of music on implicit and explicit memory for tunes. In two experiments, participants were first asked to either categorize instrument or judge familiarity of 40 unfamiliar short tunes. Subsequently, participants were asked to give explicit and implicit memory ratings for a list of 80 tunes, which included 40 previously heard. Half of the 40 previously heard tunes differed in timbre (Experiment 1) or tempo (Experiment 2) in comparison with the first exposure. A third experiment compared similarity ratings of the tunes that varied in timbre or tempo. Analysis of variance (ANOVA) results suggest first that the encoding task made no difference for either memory mode. Secondly, timbre and tempo change both impaired explicit memory, whereas tempo change additionally made implicit tune recognition worse. Results are discussed in the context of implicit memory for nonsemantic materials and the possible differences in timbre and tempo in musical representations.

Supranormal orientation selectivity of visual neurons in orientation-restricted animals.

PubMed

Sasaki, Kota S; Kimura, Rui; Ninomiya, Taihei; Tabuchi, Yuka; Tanaka, Hiroki; Fukui, Masayuki; Asada, Yusuke C; Arai, Toshiya; Inagaki, Mikio; Nakazono, Takayuki; Baba, Mika; Kato, Daisuke; Nishimoto, Shinji; Sanada, Takahisa M; Tani, Toshiki; Imamura, Kazuyuki; Tanaka, Shigeru; Ohzawa, Izumi

2015-11-16

Altered sensory experience in early life often leads to remarkable adaptations so that humans and animals can make the best use of the available information in a particular environment. By restricting visual input to a limited range of orientations in young animals, this investigation shows that stimulus selectivity, e.g., the sharpness of tuning of single neurons in the primary visual cortex, is modified to match a particular environment. Specifically, neurons tuned to an experienced orientation in orientation-restricted animals show sharper orientation tuning than neurons in normal animals, whereas the opposite was true for neurons tuned to non-experienced orientations. This sharpened tuning appears to be due to elongated receptive fields. Our results demonstrate that restricted sensory experiences can sculpt the supranormal functions of single neurons tailored for a particular environment. The above findings, in addition to the minimal population response to orientations close to the experienced one, agree with the predictions of a sparse coding hypothesis in which information is represented efficiently by a small number of activated neurons. This suggests that early brain areas adopt an efficient strategy for coding information even when animals are raised in a severely limited visual environment where sensory inputs have an unnatural statistical structure.

Contrast invariance of orientation tuning in the lateral geniculate nucleus of the feline visual system.

PubMed

Viswanathan, Sivaram; Jayakumar, Jaikishan; Vidyasagar, Trichur R

2015-09-01

Responses of most neurons in the primary visual cortex of mammals are markedly selective for stimulus orientation and their orientation tuning does not vary with changes in stimulus contrast. The basis of such contrast invariance of orientation tuning has been shown to be the higher variability in the response for low-contrast stimuli. Neurons in the lateral geniculate nucleus (LGN), which provides the major visual input to the cortex, have also been shown to have higher variability in their response to low-contrast stimuli. Parallel studies have also long established mild degrees of orientation selectivity in LGN and retinal cells. In our study, we show that contrast invariance of orientation tuning is already present in the LGN. In addition, we show that the variability of spike responses of LGN neurons increases at lower stimulus contrasts, especially for non-preferred orientations. We suggest that such contrast- and orientation-sensitive variability not only explains the contrast invariance observed in the LGN but can also underlie the contrast-invariant orientation tuning seen at the level of the primary visual cortex. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Supranormal orientation selectivity of visual neurons in orientation-restricted animals

PubMed Central

Sasaki, Kota S.; Kimura, Rui; Ninomiya, Taihei; Tabuchi, Yuka; Tanaka, Hiroki; Fukui, Masayuki; Asada, Yusuke C.; Arai, Toshiya; Inagaki, Mikio; Nakazono, Takayuki; Baba, Mika; Kato, Daisuke; Nishimoto, Shinji; Sanada, Takahisa M.; Tani, Toshiki; Imamura, Kazuyuki; Tanaka, Shigeru; Ohzawa, Izumi

2015-01-01

Altered sensory experience in early life often leads to remarkable adaptations so that humans and animals can make the best use of the available information in a particular environment. By restricting visual input to a limited range of orientations in young animals, this investigation shows that stimulus selectivity, e.g., the sharpness of tuning of single neurons in the primary visual cortex, is modified to match a particular environment. Specifically, neurons tuned to an experienced orientation in orientation-restricted animals show sharper orientation tuning than neurons in normal animals, whereas the opposite was true for neurons tuned to non-experienced orientations. This sharpened tuning appears to be due to elongated receptive fields. Our results demonstrate that restricted sensory experiences can sculpt the supranormal functions of single neurons tailored for a particular environment. The above findings, in addition to the minimal population response to orientations close to the experienced one, agree with the predictions of a sparse coding hypothesis in which information is represented efficiently by a small number of activated neurons. This suggests that early brain areas adopt an efficient strategy for coding information even when animals are raised in a severely limited visual environment where sensory inputs have an unnatural statistical structure. PMID:26567927

Functional organization of glomerular maps in the mouse accessory olfactory bulb

PubMed Central

Hammen, Gary F.; Turaga, Diwakar; Holy, Timothy E.; Meeks, Julian P.

2014-01-01

Summary The mammalian accessory olfactory system (AOS) extracts information about species, sex, and individual identity from social odors, but its functional organization remains unclear. We imaged presynaptic Ca2+ signals in vomeronasal inputs to the accessory olfactory bulb (AOB) during peripheral stimulation using light sheet microscopy. Urine- and steroid-responsive glomeruli densely innervated the anterior AOB. Glomerular activity maps for sexually mature female mouse urine overlapped maps for juvenile and/or gonadectomized urine of both sexes, whereas maps for sexually mature male urine were highly distinct. Further spatial analysis revealed a complicated organization involving selective juxtaposition and dispersal of functionally-grouped glomerular classes. Glomeruli that were similarly tuned to urines were often closely associated, whereas more disparately tuned glomeruli were selectively dispersed. Maps to a panel of sulfated steroid odorants identified tightly-juxtaposed groups that were disparately tuned and dispersed groups that were similarly tuned. These results reveal a modular, non-chemotopic spatial organization in the AOB. PMID:24880215

Tuning Selectivity of CO 2 Hydrogenation Reactions at the Metal/Oxide Interface

DOE PAGES

Kattel, Shyam; Liu, Ping; Chen, Jingguang G.

2017-06-26

The chemical transformation of CO 2 not only mitigates the anthropogenic CO 2 emission into the Earth’s atmosphere but also produces carbon compounds that can be used as precursors for the production of chemicals and fuels. The activation and conversion of CO 2 can be achieved on multifunctional catalytic sites available at the metal/oxide interface by taking advantage of the synergy between the metal nanoparticles and oxide support. In this paper, we look at the recent progress in mechanistic studies of CO 2 hydrogenation to C1 (CO, CH 3OH, and CH 4) compounds on metal/oxide catalysts. On this basis, wemore » are able to provide a better understanding of the complex reaction network, grasp the capability of manipulating structure and combination of metal and oxide at the interface in tuning selectivity, and identify the key descriptors to control the activity and, in particular, the selectivity of catalysts. In conclusion, we also discuss challenges and future research opportunities for tuning the selective conversion of CO 2 on metal/oxide catalysts.« less

Efficient receiver tuning using differential evolution strategies

NASA Astrophysics Data System (ADS)

Wheeler, Caleb H.; Toland, Trevor G.

2016-08-01

Differential evolution (DE) is a powerful and computationally inexpensive optimization strategy that can be used to search an entire parameter space or to converge quickly on a solution. The Kilopixel Array Pathfinder Project (KAPPa) is a heterodyne receiver system delivering 5 GHz of instantaneous bandwidth in the tuning range of 645-695 GHz. The fully automated KAPPa receiver test system finds optimal receiver tuning using performance feedback and DE. We present an adaptation of DE for use in rapid receiver characterization. The KAPPa DE algorithm is written in Python 2.7 and is fully integrated with the KAPPa instrument control, data processing, and visualization code. KAPPa develops the technologies needed to realize heterodyne focal plane arrays containing 1000 pixels. Finding optimal receiver tuning by investigating large parameter spaces is one of many challenges facing the characterization phase of KAPPa. This is a difficult task via by-hand techniques. Characterizing or tuning in an automated fashion without need for human intervention is desirable for future large scale arrays. While many optimization strategies exist, DE is ideal for time and performance constraints because it can be set to converge to a solution rapidly with minimal computational overhead. We discuss how DE is utilized in the KAPPa system and discuss its performance and look toward the future of 1000 pixel array receivers and consider how the KAPPa DE system might be applied.

Selection and parameterization of cortical neurons for neuroprosthetic control.

PubMed

Wahnoun, Remy; He, Jiping; Helms Tillery, Stephen I

2006-06-01

When designing neuroprosthetic interfaces for motor function, it is crucial to have a system that can extract reliable information from available neural signals and produce an output suitable for real life applications. Systems designed to date have relied on establishing a relationship between neural discharge patterns in motor cortical areas and limb movement, an approach not suitable for patients who require such implants but who are unable to provide proper motor behavior to initially tune the system. We describe here a method that allows rapid tuning of a population vector-based system for neural control without arm movements. We trained highly motivated primates to observe a 3D center-out task as the computer played it very slowly. Based on only 10-12 s of neuronal activity observed in M1 and PMd, we generated an initial mapping between neural activity and device motion that the animal could successfully use for neuroprosthetic control. Subsequent tunings of the parameters led to improvements in control, but the initial selection of neurons and estimated preferred direction for those cells remained stable throughout the remainder of the day. Using this system, we have observed that the contribution of individual neurons to the overall control of the system is very heterogeneous. We thus derived a novel measure of unit quality and an indexing scheme that allowed us to rate each neuron's contribution to the overall control. In offline tests, we found that fewer than half of the units made positive contributions to the performance. We tested this experimentally by having the animals control the neuroprosthetic system using only the 20 best neurons. We found that performance in this case was better than when the entire set of available neurons was used. Based on these results, we believe that, with careful task design, it is feasible to parameterize control systems without any overt behaviors and that subsequent control system design will be enhanced with cautious unit selection. These improvements can lead to systems demanding lower bandwidth and computational power, and will pave the way for more feasible clinical systems.

Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

PubMed

Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

2014-11-01

This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system.

Engineering of the function of diamond-like carbon binding peptides through structural design.

PubMed

Gabryelczyk, Bartosz; Szilvay, Géza R; Singh, Vivek K; Mikkilä, Joona; Kostiainen, Mauri A; Koskinen, Jari; Linder, Markus B

2015-02-09

The use of phage display to select material-specific peptides provides a general route towards modification and functionalization of surfaces and interfaces. However, a rational structural engineering of the peptides for optimal affinity is typically not feasible because of insufficient structure-function understanding. Here, we investigate the influence of multivalency of diamond-like carbon (DLC) binding peptides on binding characteristics. We show that facile linking of peptides together using different lengths of spacers and multivalency leads to a tuning of affinity and kinetics. Notably, increased length of spacers in divalent systems led to significantly increased affinities. Making multimers influenced also kinetic aspects of surface competition. Additionally, the multivalent peptides were applied as surface functionalization components for a colloidal form of DLC. The work suggests the use of a set of linking systems to screen parameters for functional optimization of selected material-specific peptides.

Control of morphology and crystal purity of InP nanowires by variation of phosphine flux during selective area MOMBE

NASA Astrophysics Data System (ADS)

Kelrich, A.; Dubrovskii, V. G.; Calahorra, Y.; Cohen, S.; Ritter, D.

2015-02-01

We present experimental results showing how the growth rate, morphology and crystal structure of Au-catalyzed InP nanowires (NWs) fabricated by selective area metal organic molecular beam epitaxy can be tuned by the growth parameters: temperature and phosphine flux. The InP NWs with 20-65 nm diameters are grown at temperatures of 420 and 480 °C with the PH3 flow varying from 1 to 9 sccm. The NW tapering is suppressed at a higher temperature, while pure wurtzite crystal structure is preferred at higher phosphine flows. Therefore, by combining high temperature and high phosphine flux, we are able to fabricate non-tapered and stacking fault-free InP NWs with the quality that other methods rarely achieve. We also develop a model for NW growth and crystal structure which explains fairly well the observed experimental tendencies.

Low-dose patterning of platinum nanoclusters on carbon nanotubes by focused-electron-beam-induced deposition as studied by TEM

PubMed Central

Bittencourt, Carla; Bals, Sara; Van Tendeloo, Gustaaf

2013-01-01

Summary Focused-electron-beam-induced deposition (FEBID) is used as a direct-write approach to decorate ultrasmall Pt nanoclusters on carbon nanotubes at selected sites in a straightforward maskless manner. The as-deposited nanostructures are studied by transmission electron microscopy (TEM) in 2D and 3D, demonstrating that the Pt nanoclusters are well-dispersed, covering the selected areas of the CNT surface completely. The ability of FEBID to graft nanoclusters on multiple sides, through an electron-transparent target within one step, is unique as a physical deposition method. Using high-resolution TEM we have shown that the CNT structure can be well preserved thanks to the low dose used in FEBID. By tuning the electron-beam parameters, the density and distribution of the nanoclusters can be controlled. The purity of as-deposited nanoclusters can be improved by low-energy electron irradiation at room temperature. PMID:23399584

Automated model optimisation using the Cylc workflow engine (Cyclops v1.0)

NASA Astrophysics Data System (ADS)

Gorman, Richard M.; Oliver, Hilary J.

2018-06-01

Most geophysical models include many parameters that are not fully determined by theory, and can be tuned to improve the model's agreement with available data. We might attempt to automate this tuning process in an objective way by employing an optimisation algorithm to find the set of parameters that minimises a cost function derived from comparing model outputs with measurements. A number of algorithms are available for solving optimisation problems, in various programming languages, but interfacing such software to a complex geophysical model simulation presents certain challenges. To tackle this problem, we have developed an optimisation suite (Cyclops) based on the Cylc workflow engine that implements a wide selection of optimisation algorithms from the NLopt Python toolbox (Johnson, 2014). The Cyclops optimisation suite can be used to calibrate any modelling system that has itself been implemented as a (separate) Cylc model suite, provided it includes computation and output of the desired scalar cost function. A growing number of institutions are using Cylc to orchestrate complex distributed suites of interdependent cycling tasks within their operational forecast systems, and in such cases application of the optimisation suite is particularly straightforward. As a test case, we applied the Cyclops to calibrate a global implementation of the WAVEWATCH III (v4.18) third-generation spectral wave model, forced by ERA-Interim input fields. This was calibrated over a 1-year period (1997), before applying the calibrated model to a full (1979-2016) wave hindcast. The chosen error metric was the spatial average of the root mean square error of hindcast significant wave height compared with collocated altimeter records. We describe the results of a calibration in which up to 19 parameters were optimised.

Numerical study on characteristic of two-dimensional metal/dielectric photonic crystals

NASA Astrophysics Data System (ADS)

Zong, Yi-Xin; Xia, Jian-Bai; Wu, Hai-Bin

2017-04-01

An improved plan-wave expansion method is adopted to theoretically study the photonic band diagrams of two-dimensional (2D) metal/dielectric photonic crystals. Based on the photonic band structures, the dependence of flat bands and photonic bandgaps on two parameters (dielectric constant and filling factor) are investigated for two types of 2D metal/dielectric (M/D) photonic crystals, hole and cylinder photonic crystals. The simulation results show that band structures are affected greatly by these two parameters. Flat bands and bandgaps can be easily obtained by tuning these parameters and the bandgap width may reach to the maximum at certain parameters. It is worth noting that the hole-type photonic crystals show more bandgaps than the corresponding cylinder ones, and the frequency ranges of bandgaps also depend strongly on these parameters. Besides, the photonic crystals containing metallic medium can obtain more modulation of photonic bands, band gaps, and large effective refractive index, etc. than the dielectric/dielectric ones. According to the numerical results, the needs of optical devices for flat bands and bandgaps can be met by selecting the suitable geometry and material parameters. Project supported by the National Basic Research Program of China (Grant No. 2011CB922200) and the National Natural Science Foundation of China (Grant No. 605210010).

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches.

PubMed

Ließ, Mareike; Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils' carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms-including the model tuning and predictor selection-were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models' predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.

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

Serkland, Darwin K.; So, Haley M.; Peake, Gregory M.

Here, we report on mode selection and tuning properties of vertical-external-cavity surface-emitting lasers (VECSELs) containing coupled semiconductor and external cavities of total length less than 1 mm. Our goal is to create narrowlinewidth (<1MHz) single-frequency VECSELs that operate near 850 nm on a single longitudinal cavity resonance and tune versus temperature without mode hops. We have designed, fabricated, and measured VECSELs with external-cavity lengths ranging from 25 to 800 μm. Lastly, we compare simulated and measured coupled-cavity mode frequencies and discuss criteria for single mode selection.

Modal analysis using a Fourier analyzer, curve-fitting, and modal tuning

NASA Technical Reports Server (NTRS)

Craig, R. R., Jr.; Chung, Y. T.

1981-01-01

The proposed modal test program differs from single-input methods in that preliminary data may be acquired using multiple inputs, and modal tuning procedures may be employed to define closely spaced frquency modes more accurately or to make use of frequency response functions (FRF's) which are based on several input locations. In some respects the proposed modal test proram resembles earlier sine-sweep and sine-dwell testing in that broadband FRF's are acquired using several input locations, and tuning is employed to refine the modal parameter estimates. The major tasks performed in the proposed modal test program are outlined. Data acquisition and FFT processing, curve fitting, and modal tuning phases are described and examples are given to illustrate and evaluate them.

Tuning and Robustness Analysis for the Orion Absolute Navigation System

NASA Technical Reports Server (NTRS)

Holt, Greg N.; Zanetti, Renato; D'Souza, Christopher

2013-01-01

The Orion Multi-Purpose Crew Vehicle (MPCV) is currently under development as NASA's next-generation spacecraft for exploration missions beyond Low Earth Orbit. The MPCV is set to perform an orbital test flight, termed Exploration Flight Test 1 (EFT-1), some time in late 2014. The navigation system for the Orion spacecraft is being designed in a Multi-Organizational Design Environment (MODE) team including contractor and NASA personnel. The system uses an Extended Kalman Filter to process measurements and determine the state. The design of the navigation system has undergone several iterations and modifications since its inception, and continues as a work-in-progress. This paper seeks to show the efforts made to-date in tuning the filter for the EFT-1 mission and instilling appropriate robustness into the system to meet the requirements of manned space ight. Filter performance is affected by many factors: data rates, sensor measurement errors, tuning, and others. This paper focuses mainly on the error characterization and tuning portion. Traditional efforts at tuning a navigation filter have centered around the observation/measurement noise and Gaussian process noise of the Extended Kalman Filter. While the Orion MODE team must certainly address those factors, the team is also looking at residual edit thresholds and measurement underweighting as tuning tools. Tuning analysis is presented with open loop Monte-Carlo simulation results showing statistical errors bounded by the 3-sigma filter uncertainty covariance. The Orion filter design uses 24 Exponentially Correlated Random Variable (ECRV) parameters to estimate the accel/gyro misalignment and nonorthogonality. By design, the time constant and noise terms of these ECRV parameters were set to manufacturer specifications and not used as tuning parameters. They are included in the filter as a more analytically correct method of modeling uncertainties than ad-hoc tuning of the process noise. Tuning is explored for the powered-flight ascent phase, where measurements are scarce and unmodelled vehicle accelerations dominate. On orbit, there are important trade-off cases between process and measurement noise. On entry, there are considerations about trading performance accuracy for robustness. Process Noise is divided into powered flight and coasting ight and can be adjusted for each phase and mode of the Orion EFT-1 mission. Measurement noise is used for the integrated velocity measurements during pad alignment. It is also used for Global Positioning System (GPS) pseudorange and delta- range measurements during the rest of the flight. The robustness effort has been focused on maintaining filter convergence and performance in the presence of unmodeled error sources. These include unmodeled forces on the vehicle and uncorrected errors on the sensor measurements. Orion uses a single-frequency, non-keyed GPS receiver, so the effects due to signal distortion in Earth's ionosphere and troposphere are present in the raw measurements. Results are presented showing the efforts to compensate for these errors as well as characterize the residual effect for measurement noise tuning. Another robustness tool in use is tuning the residual edit thresholds. The trade-off between noise tuning and edit thresholds is explored in the context of robustness to errors in dynamics models and sensor measurements. Measurement underweighting is also presented as a method of additional robustness when processing highly accurate measurements in the presence of large filter uncertainties.

Inactivation of the infragranular striate cortex broadens orientation tuning of supragranular visual neurons in the cat.

PubMed

Allison, J D; Bonds, A B

1994-01-01

Intracortical inhibition is believed to enhance the orientation tuning of striate cortical neurons, but the origin of this inhibition is unclear. To examine the possible influence of ascending inhibitory projections from the infragranular layers of striate cortex on the orientation selectivity of neurons in the supragranular layers, we measured the spatiotemporal response properties of 32 supragranular neurons in the cat before, during, and after neural activity in the infragranular layers beneath the recorded cells was inactivated by iontophoretic administration of GABA. During GABA iontophoresis, the orientation tuning bandwidth of 15 (46.9%) supragranular neurons broadened as a result of increases in response amplitude to stimuli oriented about +/- 20 degrees away from the preferred stimulus angle. The mean (+/- SD) baseline orientation tuning bandwidth (half width at half height) of these neurons was 13.08 +/- 2.3 degrees. Their mean tuning bandwidth during inactivation of the infragranular layers increased to 19.59 +/- 2.54 degrees, an increase of 49.7%. The mean percentage increase in orientation tuning bandwidth of the individual neurons was 47.4%. Four neurons exhibited symmetrical changes in their orientation tuning functions, while 11 neurons displayed asymmetrical changes. The change in form of the orientation tuning functions appeared to depend on the relative vertical alignment of the recorded neuron and the infragranular region of inactivation. Neurons located in close vertical register with the inactivated infragranular tissue exhibited symmetric changes in their orientation tuning functions. The neurons exhibiting asymmetric changes in their orientation tuning functions were located just outside the vertical register. Eight of these 11 neurons also demonstrated a mean shift of 6.67 +/- 5.77 degrees in their preferred stimulus orientation. The magnitude of change in the orientation tuning functions increased as the delivery of GABA was prolonged. Responses returned to normal approximately 30 min after the delivery of GABA was discontinued. We conclude that inhibitory projections from neurons within the infragranular layers of striate cortex in cats can enhance the orientation selectivity of supragranular striate cortical neurons.

A satellite digital controller or 'play that PID tune again, Sam'. [Position, Integral, Derivative feedback control algorithm for design strategy

NASA Technical Reports Server (NTRS)

Seltzer, S. M.

1976-01-01

The problem discussed is to design a digital controller for a typical satellite. The controlled plant is considered to be a rigid body acting in a plane. The controller is assumed to be a digital computer which, when combined with the proposed control algorithm, can be represented as a sampled-data system. The objective is to present a design strategy and technique for selecting numerical values for the control gains (assuming position, integral, and derivative feedback) and the sample rate. The technique is based on the parameter plane method and requires that the system be amenable to z-transform analysis.

Generation of sub-optical-cycle, carrier-envelope-phase--insensitive, extreme-uv pulses via nonlinear stabilization in a waveguide

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

Sandhu, Arvinder S.; Gagnon, Etienne; Paul, Ariel

2006-12-15

We present evidence for a new regime of high-harmonic generation in a waveguide where bright, sub-optical-cycle, quasimonochromatic, extreme ultraviolet (EUV) light is generated via a mechanism that is relatively insensitive to carrier-envelope phase fluctuations. The interplay between the transient plasma which determines the phase matching conditions and the instantaneous laser intensity which drives harmonic generation gives rise to a new nonlinear stabilization mechanism in the waveguide, localizing the phase-matched EUV emission to within sub-optical-cycle duration. The sub-optical-cycle EUV emission generated by this mechanism can also be selectively optimized in the spectral domain by simple tuning of parameters.

Multiple mobility edges in a 1D Aubry chain with Hubbard interaction in presence of electric field: Controlled electron transport

NASA Astrophysics Data System (ADS)

Saha, Srilekha; Maiti, Santanu K.; Karmakar, S. N.

2016-09-01

Electronic behavior of a 1D Aubry chain with Hubbard interaction is critically analyzed in presence of electric field. Multiple energy bands are generated as a result of Hubbard correlation and Aubry potential, and, within these bands localized states are developed under the application of electric field. Within a tight-binding framework we compute electronic transmission probability and average density of states using Green's function approach where the interaction parameter is treated under Hartree-Fock mean field scheme. From our analysis we find that selective transmission can be obtained by tuning injecting electron energy, and thus, the present model can be utilized as a controlled switching device.

Separability of stimulus parameter encoding by on-off directionally selective rabbit retinal ganglion cells

PubMed Central

Nowak, Przemyslaw; Dobbins, Allan C.; Gawne, Timothy J.; Grzywacz, Norberto M.

2011-01-01

The ganglion cell output of the retina constitutes a bottleneck in sensory processing in that ganglion cells must encode multiple stimulus parameters in their responses. Here we investigate encoding strategies of On-Off directionally selective retinal ganglion cells (On-Off DS RGCs) in rabbits, a class of cells dedicated to representing motion. The exquisite axial discrimination of these cells to preferred vs. null direction motion is well documented: it is invariant with respect to speed, contrast, spatial configuration, spatial frequency, and motion extent. However, these cells have broad direction tuning curves and their responses also vary as a function of other parameters such as speed and contrast. In this study, we examined whether the variation in responses across multiple stimulus parameters is systematic, that is the same for all cells, and separable, such that the response to a stimulus is a product of the effects of each stimulus parameter alone. We extracellularly recorded single On-Off DS RGCs in a superfused eyecup preparation while stimulating them with moving bars. We found that spike count responses of these cells scaled as independent functions of direction, speed, and luminance. Moreover, the speed and luminance functions were common across the whole sample of cells. Based on these findings, we developed a model that accurately predicted responses of On-Off DS RGCs as products of separable functions of direction, speed, and luminance (r = 0.98; P < 0.0001). Such a multiplicatively separable encoding strategy may simplify the decoding of these cells' outputs by the higher visual centers. PMID:21325684

Supernatural MSSM

NASA Astrophysics Data System (ADS)

Du, Guangle; Li, Tianjun; Nanopoulos, D. V.; Raza, Shabbar

2015-07-01

We point out that the electroweak fine-tuning problem in the supersymmetric standard models (SSMs) is mainly due to the high energy definition of the fine-tuning measure. We propose supernatural supersymmetry which has an order one high energy fine-tuning measure automatically. The key point is that all the mass parameters in the SSMs arise from a single supersymmetry breaking parameter. In this paper, we show that there is no supersymmetry electroweak fine-tuning problem explicitly in the minimal SSM (MSSM) with no-scale supergravity and Giudice-Masiero mechanism. We demonstrate that the Z -boson mass, the supersymmetric Higgs mixing parameter μ at the unification scale, and the sparticle spectrum can be given as functions of the universal gaugino mass M1 /2. Because the light stau is the lightest supersymmetric particle (LSP) in the no-scale MSSM, to preserve R parity, we introduce a non-thermally generated axino as the LSP dark matter candidate. We estimate the lifetime of the light stau by calculating its two-body and three-body decays to the LSP axino for several values of axion decay constant fa, and find that the light stau has a lifetime ττ ˜1 in [10-4,100 ] s for an fa range [109,1012] GeV . We show that our next to the LSP stau solutions are consistent with all the current experimental constraints, including the sparticle mass bounds, B-physics bounds, Higgs mass, cosmological bounds, and the bounds on long-lived charged particles at the LHC.

Automation of extrusion of porous cable products based on a digital controller

NASA Astrophysics Data System (ADS)

Chostkovskii, B. K.; Mitroshin, V. N.

2017-07-01

This paper presents a new approach to designing an automated system for monitoring and controlling the process of applying porous insulation material on a conductive cable core, which is based on using structurally and parametrically optimized digital controllers of an arbitrary order instead of calculating typical PID controllers using known methods. The digital controller is clocked by signals from the clock length sensor of a measuring wheel, instead of a timer signal, and this provides the robust properties of the system with respect to the changing insulation speed. Digital controller parameters are tuned to provide the operating parameters of the manufactured cable using a simulation model of stochastic extrusion and are minimized by moving a regular simplex in the parameter space of the tuned controller.

Contributions of Rod and Cone Pathways to Retinal Direction Selectivity Through Development

PubMed Central

Rosa, Juliana M.; Morrie, Ryan D.; Baertsch, Hans C.

2016-01-01

Direction selectivity is a robust computation across a broad stimulus space that is mediated by activity of both rod and cone photoreceptors through the ON and OFF pathways. However, rods, S-cones, and M-cones activate the ON and OFF circuits via distinct pathways and the relative contribution of each to direction selectivity is unknown. Using a variety of stimulation paradigms, pharmacological agents, and knockout mice that lack rod transduction, we found that inputs from the ON pathway were critical for strong direction-selective (DS) tuning in the OFF pathway. For UV light stimulation, the ON pathway inputs to the OFF pathway originated with rod signaling, whereas for visible stimulation, the ON pathway inputs to the OFF pathway originated with both rod and M-cone signaling. Whole-cell voltage-clamp recordings revealed that blocking the ON pathway reduced directional tuning in the OFF pathway via a reduction in null-side inhibition, which is provided by OFF starburst amacrine cells (SACs). Consistent with this, our recordings from OFF SACs confirmed that signals originating in the ON pathway contribute to their excitation. Finally, we observed that, for UV stimulation, ON contributions to OFF DS tuning matured earlier than direct signaling via the OFF pathway. These data indicate that the retina uses multiple strategies for computing DS responses across different colors and stages of development. SIGNIFICANCE STATEMENT The retina uses parallel pathways to encode different features of the visual scene. In some cases, these distinct pathways converge on circuits that mediate a distinct computation. For example, rod and cone pathways enable direction-selective (DS) ganglion cells to encode motion over a wide range of light intensities. Here, we show that although direction selectivity is robust across light intensities, motion discrimination for OFF signals is dependent upon ON signaling. At eye opening, ON directional tuning is mature, whereas OFF DS tuning is significantly reduced due to a delayed maturation of S-cone to OFF cone bipolar signaling. These results provide evidence that the retina uses multiple strategies for computing DS responses across different stimulus conditions. PMID:27629718

Object-based classification of earthquake damage from high-resolution optical imagery using machine learning

NASA Astrophysics Data System (ADS)

Bialas, James; Oommen, Thomas; Rebbapragada, Umaa; Levin, Eugene

2016-07-01

Object-based approaches in the segmentation and classification of remotely sensed images yield more promising results compared to pixel-based approaches. However, the development of an object-based approach presents challenges in terms of algorithm selection and parameter tuning. Subjective methods are often used, but yield less than optimal results. Objective methods are warranted, especially for rapid deployment in time-sensitive applications, such as earthquake damage assessment. Herein, we used a systematic approach in evaluating object-based image segmentation and machine learning algorithms for the classification of earthquake damage in remotely sensed imagery. We tested a variety of algorithms and parameters on post-event aerial imagery for the 2011 earthquake in Christchurch, New Zealand. Results were compared against manually selected test cases representing different classes. In doing so, we can evaluate the effectiveness of the segmentation and classification of different classes and compare different levels of multistep image segmentations. Our classifier is compared against recent pixel-based and object-based classification studies for postevent imagery of earthquake damage. Our results show an improvement against both pixel-based and object-based methods for classifying earthquake damage in high resolution, post-event imagery.

Origin and Function of Tuning Diversity in Macaque Visual Cortex

PubMed Central

Goris, Robbe L.T.; Simoncelli, Eero P.; Movshon, J. Anthony

2016-01-01

SUMMARY Neurons in visual cortex vary in their orientation selectivity. We measured responses of V1 and V2 cells to orientation mixtures and fit them with a model whose stimulus selectivity arises from the combined effects of filtering, suppression, and response nonlinearity. The model explains the diversity of orientation selectivity with neuron-to-neuron variability in all three mechanisms, of which variability in the orientation bandwidth of linear filtering is the most important. The model also accounts for the cells’ diversity of spatial frequency selectivity. Tuning diversity is matched to the needs of visual encoding. The orientation content found in natural scenes is diverse, and neurons with different selectivities are adapted to different stimulus configurations. Single orientations are better encoded by highly selective neurons, while orientation mixtures are better encoded by less selective neurons. A diverse population of neurons therefore provides better overall discrimination capabilities for natural images than any homogeneous population. PMID:26549331

"What" precedes "which": developmental neural tuning in face- and place-related cortex.

PubMed

Scherf, K Suzanne; Luna, Beatriz; Avidan, Galia; Behrmann, Marlene

2011-09-01

Although category-specific activation for faces in the ventral visual pathway appears adult-like in adolescence, recognition abilities for individual faces are still immature. We investigated how the ability to represent "individual" faces and houses develops at the neural level. Category-selective regions of interest (ROIs) for faces in the fusiform gyrus (FG) and for places in the parahippocampal place area (PPA) were identified individually in children, adolescents, and adults. Then, using an functional magnetic resonance imaging adaptation paradigm, we measured category selectivity and individual-level adaptation for faces and houses in each ROI. Only adults exhibited both category selectivity and individual-level adaptation bilaterally for faces in the FG and for houses in the PPA. Adolescents showed category selectivity bilaterally for faces in the FG and houses in the PPA. Despite this profile of category selectivity, adolescents only exhibited individual-level adaptation for houses bilaterally in the PPA and for faces in the "left" FG. Children only showed category-selective responses for houses in the PPA, and they failed to exhibit category-selective responses for faces in the FG and individual-level adaptation effects anywhere in the brain. These results indicate that category-level neural tuning develops prior to individual-level neural tuning and that face-related cortex is disproportionately slower in this developmental transition than is place-related cortex.

“What” Precedes “Which”: Developmental Neural Tuning in Face- and Place-Related Cortex

PubMed Central

Luna, Beatriz; Avidan, Galia; Behrmann, Marlene

2011-01-01

Although category-specific activation for faces in the ventral visual pathway appears adult-like in adolescence, recognition abilities for individual faces are still immature. We investigated how the ability to represent “individual” faces and houses develops at the neural level. Category-selective regions of interest (ROIs) for faces in the fusiform gyrus (FG) and for places in the parahippocampal place area (PPA) were identified individually in children, adolescents, and adults. Then, using an functional magnetic resonance imaging adaptation paradigm, we measured category selectivity and individual-level adaptation for faces and houses in each ROI. Only adults exhibited both category selectivity and individual-level adaptation bilaterally for faces in the FG and for houses in the PPA. Adolescents showed category selectivity bilaterally for faces in the FG and houses in the PPA. Despite this profile of category selectivity, adolescents only exhibited individual-level adaptation for houses bilaterally in the PPA and for faces in the “left” FG. Children only showed category-selective responses for houses in the PPA, and they failed to exhibit category-selective responses for faces in the FG and individual-level adaptation effects anywhere in the brain. These results indicate that category-level neural tuning develops prior to individual-level neural tuning and that face-related cortex is disproportionately slower in this developmental transition than is place-related cortex. PMID:21257673

Selective tuning of high-Q silicon photonic crystal nanocavities via laser-assisted local oxidation.

PubMed

Chen, Charlton J; Zheng, Jiangjun; Gu, Tingyi; McMillan, James F; Yu, Mingbin; Lo, Guo-Qiang; Kwong, Dim-Lee; Wong, Chee Wei

2011-06-20

We examine the cavity resonance tuning of high-Q silicon photonic crystal heterostructures by localized laser-assisted thermal oxidation using a 532 nm continuous wave laser focused to a 2.5 μm radius spot-size. The total shift is consistent with the parabolic rate law. A tuning range of up to 8.7 nm is achieved with ∼ 30 mW laser powers. Over this tuning range, the cavity Qs decreases from 3.2×10(5) to 1.2×10(5). Numerical simulations model the temperature distributions in the silicon photonic crystal membrane and the cavity resonance shift from oxidation.

Development of a tuned interfacial force field parameter set for the simulation of protein adsorption to silica glass.

PubMed

Snyder, James A; Abramyan, Tigran; Yancey, Jeremy A; Thyparambil, Aby A; Wei, Yang; Stuart, Steven J; Latour, Robert A

2012-12-01

Adsorption free energies for eight host-guest peptides (TGTG-X-GTGT, with X = N, D, G, K, F, T, W, and V) on two different silica surfaces [quartz (100) and silica glass] were calculated using umbrella sampling and replica exchange molecular dynamics and compared with experimental values determined by atomic force microscopy. Using the CHARMM force field, adsorption free energies were found to be overestimated (i.e., too strongly adsorbing) by about 5-9 kcal/mol compared to the experimental data for both types of silica surfaces. Peptide adsorption behavior for the silica glass surface was then adjusted using a modified version of the CHARMM program, which we call dual force-field CHARMM, which allows separate sets of nonbonded parameters (i.e., partial charge and Lennard-Jones parameters) to be used to represent intra-phase and inter-phase interactions within a given molecular system. Using this program, interfacial force field (IFF) parameters for the peptide-silica glass systems were corrected to obtain adsorption free energies within about 0.5 kcal/mol of their respective experimental values, while IFF tuning for the quartz (100) surface remains for future work. The tuned IFF parameter set for silica glass will subsequently be used for simulations of protein adsorption behavior on silica glass with greater confidence in the balance between relative adsorption affinities of amino acid residues and the aqueous solution for the silica glass surface.

Development of a Tuned Interfacial Force Field Parameter Set for the Simulation of Protein Adsorption to Silica Glass

PubMed Central

Snyder, James A.; Abramyan, Tigran; Yancey, Jeremy A.; Thyparambil, Aby A.; Wei, Yang; Stuart, Steven J.; Latour, Robert A.

2012-01-01

Adsorption free energies for eight host–guest peptides (TGTG-X-GTGT, with X = N, D, G, K, F, T, W, and V) on two different silica surfaces [quartz (100) and silica glass] were calculated using umbrella sampling and replica exchange molecular dynamics and compared with experimental values determined by atomic force microscopy. Using the CHARMM force field, adsorption free energies were found to be overestimated (i.e., too strongly adsorbing) by about 5–9 kcal/mol compared to the experimental data for both types of silica surfaces. Peptide adsorption behavior for the silica glass surface was then adjusted using a modified version of the CHARMM program, which we call dual force-field CHARMM, which allows separate sets of nonbonded parameters (i.e., partial charge and Lennard-Jones parameters) to be used to represent intra-phase and inter-phase interactions within a given molecular system. Using this program, interfacial force field (IFF) parameters for the peptide-silica glass systems were corrected to obtain adsorption free energies within about 0.5 kcal/mol of their respective experimental values, while IFF tuning for the quartz (100) surface remains for future work. The tuned IFF parameter set for silica glass will subsequently be used for simulations of protein adsorption behavior on silica glass with greater confidence in the balance between relative adsorption affinities of amino acid residues and the aqueous solution for the silica glass surface. PMID:22941539

Tuning selective reflection of light by surface anchoring in cholesteric cells with oblique helicoidal structures

NASA Astrophysics Data System (ADS)

Iadlovska, Olena S.; Maxwell, Graham R.; Babakhanova, Greta; Mehl, Georg H.; Welch, Christopher; Shiyanovskii, Sergij V.; Lavrentovich, Oleg D.

2018-04-01

Selective reflection of light by oblique helicoidal cholesteric (ChOH) can be tuned in a very broad spectral range by an applied electric field. In this work, we demonstrate that the peak wavelength of the selective reflection can be controlled by surface alignment of the director in sandwich cells. The peak wavelength is blue-shifted when the surface alignment is perpendicular to the bounding plates and red-shifted when it is planar. The effect is explained by the electric field redistribution within the cell caused by spatially varying heliconical ChOH structure. The observed phenomenon can be used in sensing applications.

Fast ultrasonic wavelength tuning in X-ray experiment

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

Blagov, A. E., E-mail: blagov-ae@mail.ru; Pisarevskii, Yu. V.; Koval’chuk, M. V.

2016-03-15

A method of tuning (scanning) X-ray beam wavelength based on modulation of the lattice parameter of X-ray optical crystal by an ultrasonic standing wave excited in it has been proposed and experimentally implemented. The double-crystal antiparallel scheme of X-ray diffraction, in which an ultrasonic wave is excited in the second crystal, is used in the experiment. The profile of characteristic line k{sub α1} of an X-ray tube with a molybdenum anode is recorded using both the proposed tuning scheme and conventional mechanical rotation of crystal. The results obtained by both techniques are in good agreement.

Radical kinetics in sub- and supercritical carbon dioxide: thermodynamic rate tuning.

PubMed

Ghandi, Khashayar; McFadden, Ryan M L; Cormier, Philip J; Satija, Paras; Smith, Marisa

2012-06-28

We report rate constants for muonium addition to 1,1-difluoroethylene (vinylidene fluoride) in CO2 at 290-530 K, 40-360 bar, and 0.05-0.90 g cm(-3). Rate constants are mapped against their thermodynamic conditions, demonstrating the kinetic tuning ability of the solvent. The reaction exhibits critical slowing near conditions of maximum solvent isothermal compressibility, where activation volumes of unprecedentedly large magnitudes on the order of ±10(6) cm(3) mol(-1) are observed. Such values are suggestive of pressure being a significant parameter for tuning fluorolkene reactivity.

Deformation-Aware Log-Linear Models

NASA Astrophysics Data System (ADS)

Gass, Tobias; Deselaers, Thomas; Ney, Hermann

In this paper, we present a novel deformation-aware discriminative model for handwritten digit recognition. Unlike previous approaches our model directly considers image deformations and allows discriminative training of all parameters, including those accounting for non-linear transformations of the image. This is achieved by extending a log-linear framework to incorporate a latent deformation variable. The resulting model has an order of magnitude less parameters than competing approaches to handling image deformations. We tune and evaluate our approach on the USPS task and show its generalization capabilities by applying the tuned model to the MNIST task. We gain interesting insights and achieve highly competitive results on both tasks.

Hairy black holes in scalar extended massive gravity

NASA Astrophysics Data System (ADS)

Tolley, Andrew J.; Wu, De-Jun; Zhou, Shuang-Yong

2015-12-01

We construct static, spherically symmetric black hole solutions in scalar extended ghost-free massive gravity and show the existence of hairy black holes in this class of extension. While the existence seems to be a generic feature, we focus on the simplest models of this extension and find that asymptotically flat hairy black holes can exist without fine-tuning the theory parameters, unlike the bi-gravity extension, where asymptotical flatness requires fine-tuning in the parameter space. Like the bi-gravity extension, we are unable to obtain asymptotically dS regular black holes in the simplest models considered, but it is possible to obtain asymptotically AdS black holes.

On the fusion of tuning parameters of fuzzy rules and neural network

NASA Astrophysics Data System (ADS)

Mamuda, Mamman; Sathasivam, Saratha

2017-08-01

Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.

Effective cancer laser-therapy design through the integration of nanotechnology and computational treatment planning models

NASA Astrophysics Data System (ADS)

Fisher, Jessica W.; Rylander, Marissa Nichole

2008-02-01

Laser therapies can provide a minimally invasive treatment alternative to surgical resection of tumors. However, the effectiveness of these therapies is limited due to nonspecific heating of target tissue which often leads to healthy tissue injury and extended treatment durations. These therapies can be further compromised due to heat shock protein (HSP) induction in tumor regions where non-lethal temperature elevation occurs, thereby imparting enhanced tumor cell viability and resistance to subsequent chemotherapy and radiation treatments. Introducing multi-walled nanotubes (MWNT) into target tissue prior to laser irradiation increases heating selectivity permitting more precise thermal energy delivery to the tumor region and enhances thermal deposition thereby increasing tumor injury and reducing HSP expression induction. This study investigated the impact of MWNT inclusion in untreated and laser irradiated monolayer cell culture and cell phantom model. Cell viability remained high for all samples with MWNT inclusion and cells integrated into alginate phantoms, demonstrating the non-toxic nature of both MWNTs and alginate phantom models. Following, laser irradiation samples with MWNT inclusion exhibited dramatic temperature elevations and decreased cell viability compared to samples without MWNT. In the cell monolayer studies, laser irradiation of samples with MWNT inclusion experienced up-regulated HSP27, 70 and 90 expression as compared to laser only or untreated samples due to greater temperature increases albeit below the threshold for cell death. Further tuning of laser parameters will permit effective cell killing and down-regulation of HSP. Due to optimal tuning of laser parameters and inclusion of MWNT in phantom models, extensive temperature elevations and cell death occurred, demonstrating MWNT-mediated laser therapy as a viable therapy option when parameters are optimized. In conclusion, MWNT-mediated laser therapies show great promise for effective tumor destruction, but require determination of appropriate MWNT characteristics and laser parameters for maximum tumor destruction.

Compact silicon photonic wavelength-tunable laser diode with ultra-wide wavelength tuning range

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

Kita, Tomohiro, E-mail: tkita@ecei.tohoku.ac.jp; Tang, Rui; Yamada, Hirohito

2015-03-16

We present a wavelength-tunable laser diode with a 99-nm-wide wavelength tuning range. It has a compact wavelength-tunable filter with high wavelength selectivity fabricated using silicon photonics technology. The silicon photonic wavelength-tunable filter with wide wavelength tuning range was realized using two ring resonators and an asymmetric Mach-Zehnder interferometer. The wavelength-tunable laser diode fabricated by butt-joining a silicon photonic filter and semiconductor optical amplifier shows stable single-mode operation over a wide wavelength range.

All-fibre ytterbium laser tunable within 45 nm

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

Abdullina, S R; Babin, S A; Vlasov, A A

2007-12-31

A tunable ytterbium-doped fibre laser is fabricated. The laser is tuned by using a tunable fibre Bragg grating (FBG) as a selecting intracavity element. The laser is tunable within 45 nm (from 1063 to 1108 nm) and emits {approx}6 W in the line of width {approx}0.15 nm, the output power and linewidth being virtually invariable within the tuning range. The method is proposed for synchronous tuning the highly reflecting and output FBGs, and a tunable ytterbium all-fibre laser is built. (lasers)

Cue Reliability Represented in the Shape of Tuning Curves in the Owl's Sound Localization System

PubMed Central

Fischer, Brian J.; Peña, Jose L.

2016-01-01

Optimal use of sensory information requires that the brain estimates the reliability of sensory cues, but the neural correlate of cue reliability relevant for behavior is not well defined. Here, we addressed this issue by examining how the reliability of spatial cue influences neuronal responses and behavior in the owl's auditory system. We show that the firing rate and spatial selectivity changed with cue reliability due to the mechanisms generating the tuning to the sound localization cue. We found that the correlated variability among neurons strongly depended on the shape of the tuning curves. Finally, we demonstrated that the change in the neurons' selectivity was necessary and sufficient for a network of stochastic neurons to predict behavior when sensory cues were corrupted with noise. This study demonstrates that the shape of tuning curves can stand alone as a coding dimension of environmental statistics. SIGNIFICANCE STATEMENT In natural environments, sensory cues are often corrupted by noise and are therefore unreliable. To make the best decisions, the brain must estimate the degree to which a cue can be trusted. The behaviorally relevant neural correlates of cue reliability are debated. In this study, we used the barn owl's sound localization system to address this question. We demonstrated that the mechanisms that account for spatial selectivity also explained how neural responses changed with degraded signals. This allowed for the neurons' selectivity to capture cue reliability, influencing the population readout commanding the owl's sound-orienting behavior. PMID:26888922

Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous response.

PubMed

Binder, Harald; Sauerbrei, Willi; Royston, Patrick

2013-06-15

In observational studies, many continuous or categorical covariates may be related to an outcome. Various spline-based procedures or the multivariable fractional polynomial (MFP) procedure can be used to identify important variables and functional forms for continuous covariates. This is the main aim of an explanatory model, as opposed to a model only for prediction. The type of analysis often guides the complexity of the final model. Spline-based procedures and MFP have tuning parameters for choosing the required complexity. To compare model selection approaches, we perform a simulation study in the linear regression context based on a data structure intended to reflect realistic biomedical data. We vary the sample size, variance explained and complexity parameters for model selection. We consider 15 variables. A sample size of 200 (1000) and R(2)  = 0.2 (0.8) is the scenario with the smallest (largest) amount of information. For assessing performance, we consider prediction error, correct and incorrect inclusion of covariates, qualitative measures for judging selected functional forms and further novel criteria. From limited information, a suitable explanatory model cannot be obtained. Prediction performance from all types of models is similar. With a medium amount of information, MFP performs better than splines on several criteria. MFP better recovers simpler functions, whereas splines better recover more complex functions. For a large amount of information and no local structure, MFP and the spline procedures often select similar explanatory models. Copyright © 2012 John Wiley & Sons, Ltd.

Vibration isolation by exploring bio-inspired structural nonlinearity.

PubMed

Wu, Zhijing; Jing, Xingjian; Bian, Jing; Li, Fengming; Allen, Robert

2015-10-08

Inspired by the limb structures of animals/insects in motion vibration control, a bio-inspired limb-like structure (LLS) is systematically studied for understanding and exploring its advantageous nonlinear function in passive vibration isolation. The bio-inspired system consists of asymmetric articulations (of different rod lengths) with inside vertical and horizontal springs (as animal muscle) of different linear stiffness. Mathematical modeling and analysis of the proposed LLS reveal that, (a) the system has very beneficial nonlinear stiffness which can provide flexible quasi-zero, zero and/or negative stiffness, and these nonlinear stiffness properties are adjustable or designable with structure parameters; (b) the asymmetric rod-length ratio and spring-stiffness ratio present very beneficial factors for tuning system equivalent stiffness; (c) the system loading capacity is also adjustable with the structure parameters which presents another flexible benefit in application. Experiments and comparisons with existing quasi-zero-stiffness isolators validate the advantageous features above, and some discussions are also given about how to select structural parameters for practical applications. The results would provide an innovative bio-inspired solution to passive vibration control in various engineering practice.

Partial least squares for efficient models of fecal indicator bacteria on Great Lakes beaches

USGS Publications Warehouse

Brooks, Wesley R.; Fienen, Michael N.; Corsi, Steven R.

2013-01-01

At public beaches, it is now common to mitigate the impact of water-borne pathogens by posting a swimmer's advisory when the concentration of fecal indicator bacteria (FIB) exceeds an action threshold. Since culturing the bacteria delays public notification when dangerous conditions exist, regression models are sometimes used to predict the FIB concentration based on readily-available environmental measurements. It is hard to know which environmental parameters are relevant to predicting FIB concentration, and the parameters are usually correlated, which can hurt the predictive power of a regression model. Here the method of partial least squares (PLS) is introduced to automate the regression modeling process. Model selection is reduced to the process of setting a tuning parameter to control the decision threshold that separates predicted exceedances of the standard from predicted non-exceedances. The method is validated by application to four Great Lakes beaches during the summer of 2010. Performance of the PLS models compares favorably to that of the existing state-of-the-art regression models at these four sites.

Random forests and stochastic gradient boosting for predicting tree canopy cover: Comparing tuning processes and model performance

Treesearch

E. Freeman; G. Moisen; J. Coulston; B. Wilson

2014-01-01

Random forests (RF) and stochastic gradient boosting (SGB), both involving an ensemble of classification and regression trees, are compared for modeling tree canopy cover for the 2011 National Land Cover Database (NLCD). The objectives of this study were twofold. First, sensitivity of RF and SGB to choices in tuning parameters was explored. Second, performance of the...

Tuning of Schottky barrier height of Al/n-Si by electron beam irradiation

NASA Astrophysics Data System (ADS)

Vali, Indudhar Panduranga; Shetty, Pramoda Kumara; Mahesha, M. G.; Petwal, V. C.; Dwivedi, Jishnu; Choudhary, R. J.

2017-06-01

The effect of electron beam irradiation (EBI) on Al/n-Si Schottky diode has been studied by I-V characterization at room temperature. The behavior of the metal-semiconductor (MS) interface is analyzed by means of variations in the MS contact parameters such as, Schottky barrier height (ΦB), ideality factor (n) and series resistance (Rs). These parameters were found to depend on the EBI dose having a fixed incident beam of energy 7.5 MeV. At different doses (500, 1000, 1500 kGy) of EBI, the Schottky contacts were prepared and extracted their contact parameters by applying thermionic emission and Cheung models. Remarkably, the tuning of ΦB was observed as a function of EBI dose. The improved n with increased ΦB is seen for all the EBI doses. As a consequence of which the thermionic emission is more favored. However, the competing transport mechanisms such as space charge limited emission, tunneling and tunneling through the trap states were ascribed due to n > 1. The analysis of XPS spectra have shown the presence of native oxide and increased radiation induced defect states. The thickness variation in the MS interface contributing to Schottky contact behavior is discussed. This study explains a new technique to tune Schottky contact parameters by metal deposition on the electron beam irradiated n-Si wafers.

McMillan Lens in a System with Space Charge

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

Lobach, I.; Nagaitsev, S.; Stern, E.

Space charge (SC) in a circulating beam in a ring produces both betatron tune shift and betatron tune spread. These effects make some particles move on to a machine resonance and become unstable. Linear elements of beam optics cannot reduce the tune spread induced by SC because of its intrinsic nonlinear nature. We investigate the possibility to mitigate it by a thin McMillan lens providing a nonlinear axially symmetric kick, which is qualitatively opposite to the accumulated kick by SC. Experimentally, the proposed concept can be tested in Fermilab's IOTA ring. A thin McMillan lens can be implemented by amore » short (70 cm) insertion of an electron beam with specifically chosen density distribution in transverse directions. In this article, to see if McMillan lenses reduce the tune spread induced by SC, we make several simulations with particle tracking code Synergia. We choose such beam and lattice parameters that tune spread is roughly 0.5 and a beam instability due to the half-integer resonance 0.5 is observed. Then, we try to reduce emittance growth by shifting betatron tunes by adjusting quadrupoles and reducing the tune spread by McMillan lenses.« less

Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise.

PubMed

Ahveninen, Jyrki; Hämäläinen, Matti; Jääskeläinen, Iiro P; Ahlfors, Seppo P; Huang, Samantha; Lin, Fa-Hsuan; Raij, Tommi; Sams, Mikko; Vasios, Christos E; Belliveau, John W

2011-03-08

How can we concentrate on relevant sounds in noisy environments? A "gain model" suggests that auditory attention simply amplifies relevant and suppresses irrelevant afferent inputs. However, it is unclear whether this suffices when attended and ignored features overlap to stimulate the same neuronal receptive fields. A "tuning model" suggests that, in addition to gain, attention modulates feature selectivity of auditory neurons. We recorded magnetoencephalography, EEG, and functional MRI (fMRI) while subjects attended to tones delivered to one ear and ignored opposite-ear inputs. The attended ear was switched every 30 s to quantify how quickly the effects evolve. To produce overlapping inputs, the tones were presented alone vs. during white-noise masking notch-filtered ±1/6 octaves around the tone center frequencies. Amplitude modulation (39 vs. 41 Hz in opposite ears) was applied for "frequency tagging" of attention effects on maskers. Noise masking reduced early (50-150 ms; N1) auditory responses to unattended tones. In support of the tuning model, selective attention canceled out this attenuating effect but did not modulate the gain of 50-150 ms activity to nonmasked tones or steady-state responses to the maskers themselves. These tuning effects originated at nonprimary auditory cortices, purportedly occupied by neurons that, without attention, have wider frequency tuning than ±1/6 octaves. The attentional tuning evolved rapidly, during the first few seconds after attention switching, and correlated with behavioral discrimination performance. In conclusion, a simple gain model alone cannot explain auditory selective attention. In nonprimary auditory cortices, attention-driven short-term plasticity retunes neurons to segregate relevant sounds from noise.

Parametrization of turbulence models using 3DVAR data assimilation in laboratory conditions

NASA Astrophysics Data System (ADS)

Olbert, A. I.; Nash, S.; Ragnoli, E.; Hartnett, M.

2013-12-01

In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ɛ model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ɛ model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. Such analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows. This research further demonstrates how 3DVAR can be utilized to identify and quantify shortcomings of the numerical model and consequently to improve forecasting by correct parameterization of the turbulence models. Such improvements may greatly benefit physical oceanography in terms of understanding and monitoring of coastal systems and the engineering sector through applications in coastal structure design, marine renewable energy and pollutant transport.

Radio frequency measurements and tuning of the China Material Irradiation Facility RFQ

NASA Astrophysics Data System (ADS)

Li, Chenxing; He, Yuan; Wang, Fengfeng; Yu, Peiyan; Yang, Lei; Li, Chunlong; Wang, Wenbin; Xu, Xianbo; Shi, Longbo; Ma, Wei; Sun, Liepeng; Lu, Liang; Wang, Zhijun; Shi, Aimin; Wang, Tieshan

2018-05-01

The full assembly and alignment of the China Material Irradiation Facility RFQ have been completed. Before the completion, the assembly and braze of single segments had been done. Radio frequency measurements of each module with dummy extension undercuts were performed before and after braze. The results reveal that there is no unexpected deformation after braze. After the full assembly, RF measurements and tuning have been performed in order to compensate the errors originated from the fabrication, braze and assembly. The impact of these errors on the field distribution is depressed to a level that is restricted by beam dynamics simulation. In this paper, the procedure of radio frequency measurement and tuning will be expatiated and the ultimate RF parameters of the cavity after tuning will be presented.

Development of orientation tuning in simple cells of primary visual cortex

PubMed Central

Moore, Bartlett D.

2012-01-01

Orientation selectivity and its development are basic features of visual cortex. The original model of orientation selectivity proposes that elongated simple cell receptive fields are constructed from convergent input of an array of lateral geniculate nucleus neurons. However, orientation selectivity of simple cells in the visual cortex is generally greater than the linear contributions based on projections from spatial receptive field profiles. This implies that additional selectivity may arise from intracortical mechanisms. The hierarchical processing idea implies mainly linear connections, whereas cortical contributions are generally considered to be nonlinear. We have explored development of orientation selectivity in visual cortex with a focus on linear and nonlinear factors in a population of anesthetized 4-wk postnatal kittens and adult cats. Linear contributions are estimated from receptive field maps by which orientation tuning curves are generated and bandwidth is quantified. Nonlinear components are estimated as the magnitude of the power function relationship between responses measured from drifting sinusoidal gratings and those predicted from the spatial receptive field. Measured bandwidths for kittens are slightly larger than those in adults, whereas predicted bandwidths are substantially broader. These results suggest that relatively strong nonlinearities in early postnatal stages are substantially involved in the development of orientation tuning in visual cortex. PMID:22323631

Frontal crashworthiness characterisation of a vehicle segment using curve comparison metrics.

PubMed

Abellán-López, D; Sánchez-Lozano, M; Martínez-Sáez, L

2018-08-01

The objective of this work is to propose a methodology for the characterization of the collision behaviour and crashworthiness of a segment of vehicles, by selecting the vehicle that best represents that group. It would be useful in the development of deformable barriers, to be used in crash tests intended to study vehicle compatibility, as well as for the definition of the representative standard pulses used in numerical simulations or component testing. The characterisation and selection of representative vehicles is based on the objective comparison of the occupant compartment acceleration and barrier force pulses, obtained during crash tests, by using appropriate comparison metrics. This method is complemented with another one, based exclusively on the comparison of a few characteristic parameters of crash behaviour obtained from the previous curves. The method has been applied to different vehicle groups, using test data from a sample of vehicles. During this application, the performance of several metrics usually employed in the validation of simulation models have been analysed, and the most efficient ones have been selected for the task. The methodology finally defined is useful for vehicle segment characterization, taken into account aspects of crash behaviour related to the shape of the curves, difficult to represent by simple numerical parameters, and it may be tuned in future works when applied to larger and different samples. Copyright © 2018 Elsevier Ltd. All rights reserved.

Loss-induced super scattering and gain-induced absorption.

PubMed

Feng, Simin

2016-01-25

Giant transmission and reflection of a finite bandwidth are demonstrated at the same wavelength when the electromagnetic wave is incident on a subwavelength array of parity-time (PT) symmetric dimers embedded in a metallic film. Remarkably, this phenomenon vanishes if the metallic substrate is lossless while keeping other parameters unchanged. Moreover super scattering can also occur when increasing the loss of the dimers while keeping the gain unchanged. When the metafilm is adjusted to the vicinity of an exceptional point, tuning either the substrate dissipation or the loss of the dimers can lead to supper scattering in stark contrast to what would be expected in conventional systems. In addition, increasing the gain of the dimers can increase the absorption near the exceptional point. These phenomena indicate that the PT-synthetic plasmonic metafilm can function as a thinfilm PT-plasmonic laser or absorber depending on the tuning parameter. One implication is that super radiation is possible from a cavity by tuning cavity dissipation or lossy element inside the cavity.

The Parametric Study and Fine-Tuning of Bow-Tie Slot Antenna with Loaded Stub

PubMed Central

2017-01-01

A printed Bow-Tie slot antenna with loaded stub is proposed and the effects of changing the dimensions of the slot area, the stub and load sizes are considered in this paper. These parameters have a considerable effect on the antenna characteristics as well as its performance. An in-depth parametric study of these dimensions is presented. This paper proposes the necessary conditions for initial approximation of dimensions needed to design this antenna. In order to achieve the desired performance of the antenna fine tuning of all sizes of these parameters is required. The parametric studies used in this paper provide proper trends for initiation and tuning the design. A prototype of the antenna for 1.7GHz to 2.6GHz band is fabricated. Measurements conducted verify that the designed antenna has wideband characteristics with 50% bandwidth around the center frequency of 2.1GHz. Conducted measurements for reflection coefficient (S11) and radiation pattern also validate our simulation results. PMID:28114354

The Parametric Study and Fine-Tuning of Bow-Tie Slot Antenna with Loaded Stub.

PubMed

Shafiei, M M; Moghavvemi, Mahmoud; Wan Mahadi, Wan Nor Liza

2017-01-01

A printed Bow-Tie slot antenna with loaded stub is proposed and the effects of changing the dimensions of the slot area, the stub and load sizes are considered in this paper. These parameters have a considerable effect on the antenna characteristics as well as its performance. An in-depth parametric study of these dimensions is presented. This paper proposes the necessary conditions for initial approximation of dimensions needed to design this antenna. In order to achieve the desired performance of the antenna fine tuning of all sizes of these parameters is required. The parametric studies used in this paper provide proper trends for initiation and tuning the design. A prototype of the antenna for 1.7GHz to 2.6GHz band is fabricated. Measurements conducted verify that the designed antenna has wideband characteristics with 50% bandwidth around the center frequency of 2.1GHz. Conducted measurements for reflection coefficient (S11) and radiation pattern also validate our simulation results.

Receptor heteromeric assembly-how it works and why it matters: the case of ionotropic glutamate receptors.

PubMed

Herguedas, Beatriz; Krieger, James; Greger, Ingo H

2013-01-01

The composition and spatial arrangement of subunits in ion channels are essential for their function. Diverse stoichiometries are possible in a multitude of channels. These depend upon cell type-specific subunit expression, which can be tuned in a developmentally regulated manner and in response to activity, on subunit stability in the endoplasmic reticulum, intersubunit affinities, and potentially subunit diffusion within the ER membrane. In concert, these parameters shape channel biogenesis and ultimately tune cellular response properties. The complexity of this assembly process is particularly well illustrated by the ionotropic glutamate receptors, the main mediators of excitatory neurotransmission. These tetrameric cation channels predominantly assemble into heteromers, which is "obligatory" for some iGluR subfamilies but "preferential" for others. Here, we discuss recent insights into the rules underlying these two pathways, the role of individual domains based on an ever increasing list of crystal structures, and how these assembly parameters tune assembly across diverse receptor oligomers. Copyright © 2013 Elsevier Inc. All rights reserved.

Composite multi-parameter ranking of real and virtual compounds for design of MC4R agonists: renaissance of the Free-Wilson methodology.

PubMed

Nilsson, Ingemar; Polla, Magnus O

2012-10-01

Drug design is a multi-parameter task present in the analysis of experimental data for synthesized compounds and in the prediction of new compounds with desired properties. This article describes the implementation of a binned scoring and composite ranking scheme for 11 experimental parameters that were identified as key drivers in the MC4R project. The composite ranking scheme was implemented in an AstraZeneca tool for analysis of project data, thereby providing an immediate re-ranking as new experimental data was added. The automated ranking also highlighted compounds overlooked by the project team. The successful implementation of a composite ranking on experimental data led to the development of an equivalent virtual score, which was based on Free-Wilson models of the parameters from the experimental ranking. The individual Free-Wilson models showed good to high predictive power with a correlation coefficient between 0.45 and 0.97 based on the external test set. The virtual ranking adds value to the selection of compounds for synthesis but error propagation must be controlled. The experimental ranking approach adds significant value, is parameter independent and can be tuned and applied to any drug discovery project.

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches

PubMed Central

Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils’ carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms—including the model tuning and predictor selection—were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models’ predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction. PMID:27128736

Gene selection in cancer classification using sparse logistic regression with Bayesian regularization.

PubMed

Cawley, Gavin C; Talbot, Nicola L C

2006-10-01

Gene selection algorithms for cancer classification, based on the expression of a small number of biomarker genes, have been the subject of considerable research in recent years. Shevade and Keerthi propose a gene selection algorithm based on sparse logistic regression (SLogReg) incorporating a Laplace prior to promote sparsity in the model parameters, and provide a simple but efficient training procedure. The degree of sparsity obtained is determined by the value of a regularization parameter, which must be carefully tuned in order to optimize performance. This normally involves a model selection stage, based on a computationally intensive search for the minimizer of the cross-validation error. In this paper, we demonstrate that a simple Bayesian approach can be taken to eliminate this regularization parameter entirely, by integrating it out analytically using an uninformative Jeffrey's prior. The improved algorithm (BLogReg) is then typically two or three orders of magnitude faster than the original algorithm, as there is no longer a need for a model selection step. The BLogReg algorithm is also free from selection bias in performance estimation, a common pitfall in the application of machine learning algorithms in cancer classification. The SLogReg, BLogReg and Relevance Vector Machine (RVM) gene selection algorithms are evaluated over the well-studied colon cancer and leukaemia benchmark datasets. The leave-one-out estimates of the probability of test error and cross-entropy of the BLogReg and SLogReg algorithms are very similar, however the BlogReg algorithm is found to be considerably faster than the original SLogReg algorithm. Using nested cross-validation to avoid selection bias, performance estimation for SLogReg on the leukaemia dataset takes almost 48 h, whereas the corresponding result for BLogReg is obtained in only 1 min 24 s, making BLogReg by far the more practical algorithm. BLogReg also demonstrates better estimates of conditional probability than the RVM, which are of great importance in medical applications, with similar computational expense. A MATLAB implementation of the sparse logistic regression algorithm with Bayesian regularization (BLogReg) is available from http://theoval.cmp.uea.ac.uk/~gcc/cbl/blogreg/

Mode selection in square resonator microlasers for widely tunable single mode lasing.

PubMed

Tang, Ming-Ying; Sui, Shao-Shuai; Yang, Yue-De; Xiao, Jin-Long; Du, Yun; Huang, Yong-Zhen

2015-10-19

Mode selection in square resonator semiconductor microlasers is demonstrated by adjusting the width of the output waveguide coupled to the midpoint of one side. The simulation and experimental results reveal that widely tunable single mode lasing can be realized in square resonator microlasers. Through adjusting the width of the output waveguide, the mode interval of the high-Q modes can reach four times of the longitudinal mode interval. Therefore, mode hopping can be efficiently avoided and the lasing wavelength can be tuned continuously by tuning the injection current. For a 17.8-μm-side-length square microlaser with a 1.4-μm-width output waveguide, mode-hopping-free single-mode operation is achieved with a continuous tuning range of 9.2 nm. As a result, the control of the lasing mode is realized for the square microlasers.

Parameter Estimation of a Spiking Silicon Neuron

PubMed Central

Russell, Alexander; Mazurek, Kevin; Mihalaş, Stefan; Niebur, Ernst; Etienne-Cummings, Ralph

2012-01-01

Spiking neuron models are used in a multitude of tasks ranging from understanding neural behavior at its most basic level to neuroprosthetics. Parameter estimation of a single neuron model, such that the model’s output matches that of a biological neuron is an extremely important task. Hand tuning of parameters to obtain such behaviors is a difficult and time consuming process. This is further complicated when the neuron is instantiated in silicon (an attractive medium in which to implement these models) as fabrication imperfections make the task of parameter configuration more complex. In this paper we show two methods to automate the configuration of a silicon (hardware) neuron’s parameters. First, we show how a Maximum Likelihood method can be applied to a leaky integrate and fire silicon neuron with spike induced currents to fit the neuron’s output to desired spike times. We then show how a distance based method which approximates the negative log likelihood of the lognormal distribution can also be used to tune the neuron’s parameters. We conclude that the distance based method is better suited for parameter configuration of silicon neurons due to its superior optimization speed. PMID:23852978

Mechanisms underlying intensity-dependent changes in cortical selectivity for frequency-modulated sweeps.

PubMed

Razak, K A

2012-04-01

Frequency-modulated (FM) sweeps are common components of species-specific vocalizations. The intensity of FM sweeps can cover a wide range in the natural environment, but whether intensity affects neural selectivity for FM sweeps is unclear. Bats, such as the pallid bat, which use FM sweeps for echolocation, are suited to address this issue, because the intensity of echoes will vary with target distance. In this study, FM sweep rate selectivity of pallid bat auditory cortex neurons was measured using downward sweeps at different intensities. Neurons became more selective for FM sweep rates present in the bat's echolocation calls as intensity increased. Increased selectivity resulted from stronger inhibition of responses to slower sweep rates. The timing and bandwidth of inhibition generated by frequencies on the high side of the excitatory tuning curve [sideband high-frequency inhibition (HFI)] shape rate selectivity in cortical neurons in the pallid bat. To determine whether intensity-dependent changes in FM rate selectivity were due to altered inhibition, the timing and bandwidth of HFI were quantified at multiple intensities using the two-tone inhibition paradigm. HFI arrived faster relative to excitation as sound intensity increased. The bandwidth of HFI also increased with intensity. The changes in HFI predicted intensity-dependent changes in FM rate selectivity. These data suggest that neural selectivity for a sweep parameter is not static but shifts with intensity due to changes in properties of sideband inhibition.

Explicit analytical tuning rules for digital PID controllers via the magnitude optimum criterion.

PubMed

Papadopoulos, Konstantinos G; Yadav, Praveen K; Margaris, Nikolaos I

2017-09-01

Analytical tuning rules for digital PID type-I controllers are presented regardless of the process complexity. This explicit solution allows control engineers 1) to make an accurate examination of the effect of the controller's sampling time to the control loop's performance both in the time and frequency domain 2) to decide when the control has to be I, PI and when the derivative, D, term has to be added or omitted 3) apply this control action to a series of stable benchmark processes regardless of their complexity. The former advantages are considered critical in industry applications, since 1) most of the times the choice of the digital controller's sampling time is based on heuristics and past criteria, 2) there is little a-priori knowledge of the controlled process making the choice of the type of the controller a trial and error exercise 3) model parameters change often depending on the control loop's operating point making in this way, the problem of retuning the controller's parameter a much challenging issue. Basis of the proposed control law is the principle of the PID tuning via the Magnitude Optimum criterion. The final control law involves the controller's sampling time T s within the explicit solution of the controller's parameters. Finally, the potential of the proposed method is justified by comparing its performance with the conventional PID tuning when controlling the same process. Further investigation regarding the choice of the controller's sampling time T s is also presented and useful conclusions for control engineers are derived. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

[Long-term memory, neurogenesis and novelty signal].

PubMed

Sokolova, E N; Nezlina, N I

2003-01-01

In accordance with the advanced hypothesis the long-term memory is a collection of "gnostic units" selectively tuned to experienced events. The long-term memory is continuously supplemented by new neurons differentiated from stem cells during neurogenesis (particularly, in adults). The transformation of neuronal progenitors into event-selective gnostic units is accomplished with participation of hippocampal "novelty neurons" emphasizing information inputs to be stored in the long-term memory. The formation of the gnostic units is preceded by informational processes occurring in the ventral ("what?") and dorsal ("where?") systems. The formation of a new gnostic unit selectively tuned to a particular event is a result of combination of feature-detector excitation and novelty signal generated by hippocampal novelty neurons.

Neuroelectric Tuning of Cortical Oscillations by Apical Dendrites in Loop Circuits

PubMed Central

LaBerge, David; Kasevich, Ray S.

2017-01-01

Bundles of relatively long apical dendrites dominate the neurons that make up the thickness of the cerebral cortex. It is proposed that a major function of the apical dendrite is to produce sustained oscillations at a specific frequency that can serve as a common timing unit for the processing of information in circuits connected to that apical dendrite. Many layer 5 and 6 pyramidal neurons are connected to thalamic neurons in loop circuits. A model of the apical dendrites of these pyramidal neurons has been used to simulate the electric activity of the apical dendrite. The results of that simulation demonstrated that subthreshold electric pulses in these apical dendrites can be tuned to specific frequencies and also can be fine-tuned to narrow bandwidths of less than one Hertz (1 Hz). Synchronous pulse outputs from the circuit loops containing apical dendrites can tune subthreshold membrane oscillations of neurons they contact. When the pulse outputs are finely tuned, they function as a local “clock,” which enables the contacted neurons to synchronously communicate with each other. Thus, a shared tuning frequency can select neurons for membership in a circuit. Unlike layer 6 apical dendrites, layer 5 apical dendrites can produce burst firing in many of their neurons, which increases the amplitude of signals in the neurons they contact. This difference in amplitude of signals serves as basis of selecting a sub-circuit for specialized processing (e.g., sustained attention) within the typically larger layer 6-based circuit. After examining the sustaining of oscillations in loop circuits and the processing of spikes in network circuits, we propose that cortical functioning can be globally viewed as two systems: a loop system and a network system. The loop system oscillations influence the network system’s timing and amplitude of pulse signals, both of which can select circuits that are momentarily dominant in cortical activity. PMID:28659768

Neuroelectric Tuning of Cortical Oscillations by Apical Dendrites in Loop Circuits.

PubMed

LaBerge, David; Kasevich, Ray S

2017-01-01

Bundles of relatively long apical dendrites dominate the neurons that make up the thickness of the cerebral cortex. It is proposed that a major function of the apical dendrite is to produce sustained oscillations at a specific frequency that can serve as a common timing unit for the processing of information in circuits connected to that apical dendrite. Many layer 5 and 6 pyramidal neurons are connected to thalamic neurons in loop circuits. A model of the apical dendrites of these pyramidal neurons has been used to simulate the electric activity of the apical dendrite. The results of that simulation demonstrated that subthreshold electric pulses in these apical dendrites can be tuned to specific frequencies and also can be fine-tuned to narrow bandwidths of less than one Hertz (1 Hz). Synchronous pulse outputs from the circuit loops containing apical dendrites can tune subthreshold membrane oscillations of neurons they contact. When the pulse outputs are finely tuned, they function as a local "clock," which enables the contacted neurons to synchronously communicate with each other. Thus, a shared tuning frequency can select neurons for membership in a circuit. Unlike layer 6 apical dendrites, layer 5 apical dendrites can produce burst firing in many of their neurons, which increases the amplitude of signals in the neurons they contact. This difference in amplitude of signals serves as basis of selecting a sub-circuit for specialized processing (e.g., sustained attention) within the typically larger layer 6-based circuit. After examining the sustaining of oscillations in loop circuits and the processing of spikes in network circuits, we propose that cortical functioning can be globally viewed as two systems: a loop system and a network system. The loop system oscillations influence the network system's timing and amplitude of pulse signals, both of which can select circuits that are momentarily dominant in cortical activity.

JetWeb: A WWW interface and database for Monte Carlo tuning and validation

NASA Astrophysics Data System (ADS)

Butterworth, J. M.; Butterworth, S.

2003-06-01

A World Wide Web interface to a Monte Carlo tuning facility is described. The aim of the package is to allow rapid and reproducible comparisons to be made between detailed measurements at high-energy physics colliders and general physics simulation packages. The package includes a relational database, a Java servlet query and display facility, and clean interfaces to simulation packages and their parameters.

Electrical birefringence tuning of VCSELs

NASA Astrophysics Data System (ADS)

Pusch, Tobias; Lindemann, Markus; Gerhardt, Nils C.; Hofmann, Martin R.; Michalzik, Rainer

2018-02-01

The birefringence splitting B, which is the frequency difference between the two fundamental linear polarization modes in vertical-cavity surface-emitting lasers (VCSELs), is the key parameter determining the polarization dynamics of spin-VCSELs that can be much faster than the intensity dynamics. For easy handling and control, electrical tuning of B is favored. This was realized in an integrated chip by thermally induced strain via asymmetric heating with a birefringence tuning range of 45 GHz. In this paper we present our work on VCSEL structures mounted on piezoelectric transducers for strain generation. Furthermore we show a combination of both techniques, namely VCSELs with piezo-thermal birefringence tunability.

An express method for optimally tuning an analog controller with respect to integral quality criteria

NASA Astrophysics Data System (ADS)

Golinko, I. M.; Kovrigo, Yu. M.; Kubrak, A. I.

2014-03-01

An express method for optimally tuning analog PI and PID controllers is considered. An integral quality criterion with minimizing the control output is proposed for optimizing control systems. The suggested criterion differs from existing ones in that the control output applied to the technological process is taken into account in a correct manner, due to which it becomes possible to maximally reduce the expenditure of material and/or energy resources in performing control of industrial equipment sets. With control organized in such manner, smaller wear and longer service life of control devices are achieved. A unimodal nature of the proposed criterion for optimally tuning a controller is numerically demonstrated using the methods of optimization theory. A functional interrelation between the optimal controller parameters and dynamic properties of a controlled plant is numerically determined for a single-loop control system. The results obtained from simulation of transients in a control system carried out using the proposed and existing functional dependences are compared with each other. The proposed calculation formulas differ from the existing ones by a simple structure and highly accurate search for the optimal controller tuning parameters. The obtained calculation formulas are recommended for being used by specialists in automation for design and optimization of control systems.

Analysis and design of negative resistance oscillators using surface transverse wave-based single port resonators.

PubMed

Avramov, Ivan D

2003-03-01

This practically oriented paper presents the fundamentals for analysis, optimization, and design of negative resistance oscillators (NRO) stabilized with surface transverse wave (STW)-based single-port resonators (SPR). Data on a variety of high-Q, low-loss SPR devices in the 900- to 2000-MHz range, suitable for NRO applications, are presented, and a simple method for SPR parameter extraction through Pi-circuit measurements is outlined. Negative resistance analysis, based on S-parameter data of the active device, is performed on a tuned-base, grounded collector transistor NRO, known for its good stability and tuning at microwave frequencies. By adding a SPR in the emitter network, the static transducer capacitance is absorbed by the circuit and is used to generate negative resistance only over the narrow bandwidth of the acoustic device, eliminating the risk of spurious oscillations. The analysis allows exact prediction of the oscillation frequency, tuning range, loaded Q, and excess gain. Simulation and experimental data on a 915-MHz fixed-frequency NRO and a wide tuning range, voltage-controlled STW oscillator, built and tested experimentally, are presented. Practical design aspects including the choice of transistor, negative feedback circuits, load coupling, and operation at the highest phase slope for minimum phase noise are discussed.

Adaptive Control of Synchronization in Delay-Coupled Heterogeneous Networks of FitzHugh-Nagumo Nodes

NASA Astrophysics Data System (ADS)

Plotnikov, S. A.; Lehnert, J.; Fradkov, A. L.; Schöll, E.

We study synchronization in delay-coupled neural networks of heterogeneous nodes. It is well known that heterogeneities in the nodes hinder synchronization when becoming too large. We show that an adaptive tuning of the overall coupling strength can be used to counteract the effect of the heterogeneity. Our adaptive controller is demonstrated on ring networks of FitzHugh-Nagumo systems which are paradigmatic for excitable dynamics but can also — depending on the system parameters — exhibit self-sustained periodic firing. We show that the adaptively tuned time-delayed coupling enables synchronization even if parameter heterogeneities are so large that excitable nodes coexist with oscillatory ones.

Investigation of earthquake factor for optimum tuned mass dampers

NASA Astrophysics Data System (ADS)

Nigdeli, Sinan Melih; Bekdaş, Gebrail

2012-09-01

In this study the optimum parameters of tuned mass dampers (TMD) are investigated under earthquake excitations. An optimization strategy was carried out by using the Harmony Search (HS) algorithm. HS is a metaheuristic method which is inspired from the nature of musical performances. In addition to the HS algorithm, the results of the optimization objective are compared with the results of the other documented method and the corresponding results are eliminated. In that case, the best optimum results are obtained. During the optimization, the optimum TMD parameters were searched for single degree of freedom (SDOF) structure models with different periods. The optimization was done for different earthquakes separately and the results were compared.

Simultaneous gains tuning in boiler/turbine PID-based controller clusters using iterative feedback tuning methodology.

PubMed

Zhang, Shu; Taft, Cyrus W; Bentsman, Joseph; Hussey, Aaron; Petrus, Bryan

2012-09-01

Tuning a complex multi-loop PID based control system requires considerable experience. In today's power industry the number of available qualified tuners is dwindling and there is a great need for better tuning tools to maintain and improve the performance of complex multivariable processes. Multi-loop PID tuning is the procedure for the online tuning of a cluster of PID controllers operating in a closed loop with a multivariable process. This paper presents the first application of the simultaneous tuning technique to the multi-input-multi-output (MIMO) PID based nonlinear controller in the power plant control context, with the closed-loop system consisting of a MIMO nonlinear boiler/turbine model and a nonlinear cluster of six PID-type controllers. Although simplified, the dynamics and cross-coupling of the process and the PID cluster are similar to those used in a real power plant. The particular technique selected, iterative feedback tuning (IFT), utilizes the linearized version of the PID cluster for signal conditioning, but the data collection and tuning is carried out on the full nonlinear closed-loop system. Based on the figure of merit for the control system performance, the IFT is shown to deliver performance favorably comparable to that attained through the empirical tuning carried out by an experienced control engineer. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Fine-tuning gene networks using simple sequence repeats

PubMed Central

Egbert, Robert G.; Klavins, Eric

2012-01-01

The parameters in a complex synthetic gene network must be extensively tuned before the network functions as designed. Here, we introduce a simple and general approach to rapidly tune gene networks in Escherichia coli using hypermutable simple sequence repeats embedded in the spacer region of the ribosome binding site. By varying repeat length, we generated expression libraries that incrementally and predictably sample gene expression levels over a 1,000-fold range. We demonstrate the utility of the approach by creating a bistable switch library that programmatically samples the expression space to balance the two states of the switch, and we illustrate the need for tuning by showing that the switch’s behavior is sensitive to host context. Further, we show that mutation rates of the repeats are controllable in vivo for stability or for targeted mutagenesis—suggesting a new approach to optimizing gene networks via directed evolution. This tuning methodology should accelerate the process of engineering functionally complex gene networks. PMID:22927382

Practice and philosophy of climate model tuning across six US modeling centers

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

Schmidt, Gavin A.; Bader, David; Donner, Leo J.

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less

Practice and philosophy of climate model tuning across six US modeling centers

NASA Astrophysics Data System (ADS)

Schmidt, Gavin A.; Bader, David; Donner, Leo J.; Elsaesser, Gregory S.; Golaz, Jean-Christophe; Hannay, Cecile; Molod, Andrea; Neale, Richard B.; Saha, Suranjana

2017-09-01

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean-atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientific missions, tuning targets, and tunable parameters, there is a core commonality of approaches. However, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.

Practice and philosophy of climate model tuning across six US modeling centers

DOE PAGES

Schmidt, Gavin A.; Bader, David; Donner, Leo J.; ...

2017-09-01

Model calibration (or tuning) is a necessary part of developing and testing coupled ocean–atmosphere climate models regardless of their main scientific purpose. There is an increasing recognition that this process needs to become more transparent for both users of climate model output and other developers. Knowing how and why climate models are tuned and which targets are used is essential to avoiding possible misattributions of skillful predictions to data accommodation and vice versa. This paper describes the approach and practice of model tuning for the six major US climate modeling centers. While details differ among groups in terms of scientificmore » missions, tuning targets, and tunable parameters, there is a core commonality of approaches. Furthermore, practices differ significantly on some key aspects, in particular, in the use of initialized forecast analyses as a tool, the explicit use of the historical transient record, and the use of the present-day radiative imbalance vs. the implied balance in the preindustrial era as a target.« less

Frequency-specific attentional modulation in human primary auditory cortex and midbrain.

PubMed

Riecke, Lars; Peters, Judith C; Valente, Giancarlo; Poser, Benedikt A; Kemper, Valentin G; Formisano, Elia; Sorger, Bettina

2018-07-01

Paying selective attention to an audio frequency selectively enhances activity within primary auditory cortex (PAC) at the tonotopic site (frequency channel) representing that frequency. Animal PAC neurons achieve this 'frequency-specific attentional spotlight' by adapting their frequency tuning, yet comparable evidence in humans is scarce. Moreover, whether the spotlight operates in human midbrain is unknown. To address these issues, we studied the spectral tuning of frequency channels in human PAC and inferior colliculus (IC), using 7-T functional magnetic resonance imaging (FMRI) and frequency mapping, while participants focused on different frequency-specific sounds. We found that shifts in frequency-specific attention alter the response gain, but not tuning profile, of PAC frequency channels. The gain modulation was strongest in low-frequency channels and varied near-monotonically across the tonotopic axis, giving rise to the attentional spotlight. We observed less prominent, non-tonotopic spatial patterns of attentional modulation in IC. These results indicate that the frequency-specific attentional spotlight in human PAC as measured with FMRI arises primarily from tonotopic gain modulation, rather than adapted frequency tuning. Moreover, frequency-specific attentional modulation of afferent sound processing in human IC seems to be considerably weaker, suggesting that the spotlight diminishes toward this lower-order processing stage. Our study sheds light on how the human auditory pathway adapts to the different demands of selective hearing. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Inflation expels runaways

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

Bachlechner, Thomas C.

We argue that moduli stabilization generically restricts the evolution following transitions between weakly coupled de Sitter vacua and can induce a strong selection bias towards inflationary cosmologies. The energy density of domain walls between vacua typically destabilizes Kähler moduli and triggers a runaway towards large volume. This decompactification phase can collapse the new de Sitter region unless a minimum amount of inflation occurs after the transition. A stable vacuum transition is guaranteed only if the inflationary expansion generates overlapping past light cones for all observable modes originating from the reheating surface, which leads to an approximately flat and isotropic universe.more » High scale inflation is vastly favored. Finally, our results point towards a framework for studying parameter fine-tuning and inflationary initial conditions in flux compactifications.« less

Vortex lattices and defect-mediated viscosity reduction in active liquids

NASA Astrophysics Data System (ADS)

Slomka, Jonasz; Dunkel, Jorn

2016-11-01

Generic pattern-formation and viscosity-reduction mechanisms in active fluids are investigated using a generalized Navier-Stokes model that captures the experimentally observed bulk vortex dynamics in microbial suspensions. We present exact analytical solutions including stress-free vortex lattices and introduce a computational framework that allows the efficient treatment of previously intractable higher-order shear boundary conditions. Large-scale parameter scans identify the conditions for spontaneous flow symmetry breaking, defect-mediated low-viscosity phases and negative-viscosity states amenable to energy harvesting in confined suspensions. The theory uses only generic assumptions about the symmetries and long-wavelength structure of active stress tensors, suggesting that inviscid phases may be achievable in a broad class of non-equilibrium fluids by tuning confinement geometry and pattern scale selection.

Geometry-dependent viscosity reduction in sheared active fluids

NASA Astrophysics Data System (ADS)

Słomka, Jonasz; Dunkel, Jörn

2017-04-01

We investigate flow pattern formation and viscosity reduction mechanisms in active fluids by studying a generalized Navier-Stokes model that captures the experimentally observed bulk vortex dynamics in microbial suspensions. We present exact analytical solutions including stress-free vortex lattices and introduce a computational framework that allows the efficient treatment of higher-order shear boundary conditions. Large-scale parameter scans identify the conditions for spontaneous flow symmetry breaking, geometry-dependent viscosity reduction, and negative-viscosity states amenable to energy harvesting in confined suspensions. The theory uses only generic assumptions about the symmetries and long-wavelength structure of active stress tensors, suggesting that inviscid phases may be achievable in a broad class of nonequilibrium fluids by tuning confinement geometry and pattern scale selection.

Inflation expels runaways

NASA Astrophysics Data System (ADS)

Bachlechner, Thomas C.

2016-12-01

We argue that moduli stabilization generically restricts the evolution following transitions between weakly coupled de Sitter vacua and can induce a strong selection bias towards inflationary cosmologies. The energy density of domain walls between vacua typically destabilizes Kähler moduli and triggers a runaway towards large volume. This decompactification phase can collapse the new de Sitter region unless a minimum amount of inflation occurs after the transition. A stable vacuum transition is guaranteed only if the inflationary expansion generates overlapping past light cones for all observable modes originating from the reheating surface, which leads to an approximately flat and isotropic universe. High scale inflation is vastly favored. Our results point towards a framework for studying parameter fine-tuning and inflationary initial conditions in flux compactifications.

Inflation expels runaways

DOE PAGES

Bachlechner, Thomas C.

2016-12-30

We argue that moduli stabilization generically restricts the evolution following transitions between weakly coupled de Sitter vacua and can induce a strong selection bias towards inflationary cosmologies. The energy density of domain walls between vacua typically destabilizes Kähler moduli and triggers a runaway towards large volume. This decompactification phase can collapse the new de Sitter region unless a minimum amount of inflation occurs after the transition. A stable vacuum transition is guaranteed only if the inflationary expansion generates overlapping past light cones for all observable modes originating from the reheating surface, which leads to an approximately flat and isotropic universe.more » High scale inflation is vastly favored. Finally, our results point towards a framework for studying parameter fine-tuning and inflationary initial conditions in flux compactifications.« less

Cue Reliability Represented in the Shape of Tuning Curves in the Owl's Sound Localization System.

PubMed

Cazettes, Fanny; Fischer, Brian J; Peña, Jose L

2016-02-17

Optimal use of sensory information requires that the brain estimates the reliability of sensory cues, but the neural correlate of cue reliability relevant for behavior is not well defined. Here, we addressed this issue by examining how the reliability of spatial cue influences neuronal responses and behavior in the owl's auditory system. We show that the firing rate and spatial selectivity changed with cue reliability due to the mechanisms generating the tuning to the sound localization cue. We found that the correlated variability among neurons strongly depended on the shape of the tuning curves. Finally, we demonstrated that the change in the neurons' selectivity was necessary and sufficient for a network of stochastic neurons to predict behavior when sensory cues were corrupted with noise. This study demonstrates that the shape of tuning curves can stand alone as a coding dimension of environmental statistics. In natural environments, sensory cues are often corrupted by noise and are therefore unreliable. To make the best decisions, the brain must estimate the degree to which a cue can be trusted. The behaviorally relevant neural correlates of cue reliability are debated. In this study, we used the barn owl's sound localization system to address this question. We demonstrated that the mechanisms that account for spatial selectivity also explained how neural responses changed with degraded signals. This allowed for the neurons' selectivity to capture cue reliability, influencing the population readout commanding the owl's sound-orienting behavior. Copyright © 2016 the authors 0270-6474/16/362101-10$15.00/0.

Recording evoked potentials during deep brain stimulation: development and validation of instrumentation to suppress the stimulus artefact

PubMed Central

Kent, A R; Grill, W M

2012-01-01

Deep brain stimulation (DBS) is an effective treatment for movement disorders, but the selection of stimulus parameters is a clinical burden and often yields sub-optimal outcomes for patients. Measurement of electrically evoked compound action potentials (ECAPs) during DBS could offer insight into the type and spatial extent of neural element activation and provide a potential feedback signal for the rational selection of stimulus parameters and closed-loop DBS. However, recording ECAPs presents a significant technical challenge due to the large stimulus artefact, which can saturate recording amplifiers and distort short latency ECAP signals. We developed DBS-ECAP recording instrumentation combining commercial amplifiers and circuit elements in a serial configuration to reduce the stimulus artefact and enable high fidelity recording. We used an electrical circuit equivalent model of the instrumentation to understand better the sources of the stimulus artefact and the mechanisms of artefact reduction by the circuit elements. In vitro testing validated the capability of the instrumentation to suppress the stimulus artefact and increase gain by a factor of 1,000 to 5,000 compared to a conventional biopotential amplifier. The distortion of mock ECAP (mECAP) signals was measured across stimulation parameters, and the instrumentation enabled high fidelity recording of mECAPs with latencies of only 0.5 ms for DBS pulse widths of 50 to 100 μs/phase. Subsequently, the instrumentation was used to record in vivo ECAPs, without contamination by the stimulus artefact, during thalamic DBS in an anesthetized cat. The characteristics of the physiological ECAP were dependent on stimulation parameters. The novel instrumentation enables high fidelity ECAP recording and advances the potential use of the ECAP as a feedback signal for the tuning of DBS parameters. PMID:22510375

Testing inferior colliculus neurons for selectivity to the rate or duration of frequency modulated sweeps

NASA Astrophysics Data System (ADS)

Faure, Paul A.; Morrison, James A.; Valdizón-Rodríguez, Roberto

2018-05-01

Here we propose a method for testing how the responses of so-called "FM duration-tuned neurons (DTNs)" encode temporal properties of frequency modulated (FM) sweeps to determine if the responses of so-called "FM duration-tuned neurons (DTNs)" are tuned to FM rate or FM duration. Based on previous studies it was unclear if the responses of "FM DTNs" were tuned to signal duration, like pure-tone DTNs, or FM sweep rate. We tested this using single-unit extracellular recording in the inferior colliculus (IC) of the big brown bat (Eptesicus fuscus). We presented IC cells with linear FM sweeps that were varied in FM center frequency (CEF) and spectral bandwidth (BW) to measure the FM rate tuning responses of a cell. We also varied FM signal duration to measure the best duration (BD) and temporal BW of duration tuning of a cell. We then doubled (and halved) the best FM BW, while keeping the CEF constant, and remeasured the BD and temporal BW of duration tuning with FM bandwidth manipulated signals. We reasoned that the range of excitatory signal durations should not change in a true FM DTN whose responses are tuned to signal duration; however, when stimulated with bandwidth manipulated FM sounds the range of excitatory signal durations should predictably vary in a FM rate-tuned cell. Preliminary data indicate that our stimulus paradigm can disambiguate whether the evoked responses of an IC neuron are FM sweep rate tuned or FM duration tuned.

Fault tolerant control of multivariable processes using auto-tuning PID controller.

PubMed

Yu, Ding-Li; Chang, T K; Yu, Ding-Wen

2005-02-01

Fault tolerant control of dynamic processes is investigated in this paper using an auto-tuning PID controller. A fault tolerant control scheme is proposed composing an auto-tuning PID controller based on an adaptive neural network model. The model is trained online using the extended Kalman filter (EKF) algorithm to learn system post-fault dynamics. Based on this model, the PID controller adjusts its parameters to compensate the effects of the faults, so that the control performance is recovered from degradation. The auto-tuning algorithm for the PID controller is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The method is applied to a simulated two-input two-output continuous stirred tank reactor (CSTR) with various faults, which demonstrate the applicability of the developed scheme to industrial processes.

Origin and Function of Tuning Diversity in Macaque Visual Cortex.

PubMed

Goris, Robbe L T; Simoncelli, Eero P; Movshon, J Anthony

2015-11-18

Neurons in visual cortex vary in their orientation selectivity. We measured responses of V1 and V2 cells to orientation mixtures and fit them with a model whose stimulus selectivity arises from the combined effects of filtering, suppression, and response nonlinearity. The model explains the diversity of orientation selectivity with neuron-to-neuron variability in all three mechanisms, of which variability in the orientation bandwidth of linear filtering is the most important. The model also accounts for the cells' diversity of spatial frequency selectivity. Tuning diversity is matched to the needs of visual encoding. The orientation content found in natural scenes is diverse, and neurons with different selectivities are adapted to different stimulus configurations. Single orientations are better encoded by highly selective neurons, while orientation mixtures are better encoded by less selective neurons. A diverse population of neurons therefore provides better overall discrimination capabilities for natural images than any homogeneous population. Copyright © 2015 Elsevier Inc. All rights reserved.

Tune-out wavelengths and landscape-modulated polarizabilities of alkali-metal Rydberg atoms in infrared optical lattices

NASA Astrophysics Data System (ADS)

Topcu, Turker; Derevianko, Andrei

2013-11-01

Intensity-modulated optical lattice potentials can change sign for an alkali-metal Rydberg atom, and the atoms are not always attracted to intensity minima in optical lattices with wavelengths near the CO2 laser band. Here we demonstrate that such IR lattices can be tuned so that the trapping potential experienced by the Rydberg atom can be made to vanish for atoms in “targeted” Rydberg states. Such state-selective trapping of Rydberg atoms can be useful in controlled cold Rydberg collisions, cooling Rydberg states, and species-selective trapping and transport of Rydberg atoms in optical lattices. We tabulate wavelengths at which the trapping potential vanishes for the ns, np, and nd Rydberg states of Na and Rb atoms and discuss advantages of using such optical lattices for state-selective trapping of Rydberg atoms. We also develop exact analytical expressions for the lattice-induced polarizability for the mz=0 Rydberg states and derive an accurate formula predicting tune-out wavelengths at which the optical trapping potential becomes invisible to Rydberg atoms in targeted l=0 states.

Two single-point mutations shift the ligand selectivity of a pheromone receptor between two closely related moth species

PubMed Central

Yang, Ke; Huang, Ling-Qiao; Ning, Chao

2017-01-01

Male moths possess highly sensitive and selective olfactory systems that detect sex pheromones produced by their females. Pheromone receptors (PRs) play a key role in this process. The PR HassOr14b is found to be tuned to (Z)−9-hexadecenal, the major sex-pheromone component, in Helicoverpa assulta. HassOr14b is co-localized with HassOr6 or HassOr16 in two olfactory sensory neurons within the same sensilla. As HarmOr14b, the ortholog of HassOr14b in the closely related species Helicoverpa armigera, is tuned to another chemical (Z)−9-tetradecenal, we study the amino acid residues that determine their ligand selectivity. Two amino acids located in the intracellular domains F232I and T355I together determine the functional difference between the two orthologs. We conclude that species-specific changes in the tuning specificity of the PRs in the two Helicoverpa moth species could be achieved with just a few amino acid substitutions, which provides new insights into the evolution of closely related moth species. PMID:29063835

Blue Shifting Tuning of the Selective Reflection of Polymer Stabilized Cholesteric Liquid Crystals (Postprint)

DTIC Science & Technology

2017-08-08

deformation then affects the anchoring of the low-molar mass CLC mixture resulting in broadening of the reflection band due to nonuniformity in the pitch...confirmed that the tuning is a result of nonuniform pitch displacement across the cell gap.17 In this contribution, we report on the realization of yet

Individual and age-related variation in chromatic contrast adaptation

PubMed Central

Elliott, Sarah L.; Werner, John S.; Webster, Michael A.

2012-01-01

Precortical color channels are tuned primarily to the LvsM (stimulation of L and M cones varied, but S cone stimulation held constant) or SvsLM (stimulation of S cones varied, but L and M cone stimulation held constant) cone-opponent (cardinal) axes, but appear elaborated in the cortex to form higher-order mechanisms tuned to both cardinal and intermediate directions. One source of evidence for these higher-order mechanisms has been the selectivity of color contrast adaptation for noncardinal directions, yet the degree of this selectivity has varied widely across the small sample of observers tested in previous studies. This study explored the possible bases for this variation, and in particular tested whether it reflected age-related changes in the distribution or tuning of color mechanisms. Observers included 15 younger (18–22 years of age) and 15 older individuals (66–82), who adapted to temporal modulations along one of four chromatic axes (two cardinal and two intermediate axes) and then matched the hue and contrast of test stimuli lying along eight different directions in the equiluminant plane. All observers exhibited aftereffects that were selective for both the cardinal and intermediate directions, although selectivity was weaker for the intermediate axes. The degree of selectivity increased with the magnitude of adaptation for all axes, and thus adaptation strength alone may account for much of the variance in selectivity among observers. Older observers showed a stronger magnitude of adaptation thus, surprisingly, more conspicuous evidence for higher-order mechanisms. For both age groups the aftereffects were well predicted by response changes in chromatic channels with linear spectral sensitivities, and there was no evidence for weakened channel tuning with aging. The results suggest that higher-order mechanisms may become more exposed in observers or conditions in which the strength of adaptation is greater, and that both chromatic contrast adaptation and the cortical color coding it reflects remain largely intact in the aging visual system. PMID:22904356

Feature-Selective Attention Adaptively Shifts Noise Correlations in Primary Auditory Cortex.

PubMed

Downer, Joshua D; Rapone, Brittany; Verhein, Jessica; O'Connor, Kevin N; Sutter, Mitchell L

2017-05-24

Sensory environments often contain an overwhelming amount of information, with both relevant and irrelevant information competing for neural resources. Feature attention mediates this competition by selecting the sensory features needed to form a coherent percept. How attention affects the activity of populations of neurons to support this process is poorly understood because population coding is typically studied through simulations in which one sensory feature is encoded without competition. Therefore, to study the effects of feature attention on population-based neural coding, investigations must be extended to include stimuli with both relevant and irrelevant features. We measured noise correlations ( r noise ) within small neural populations in primary auditory cortex while rhesus macaques performed a novel feature-selective attention task. We found that the effect of feature-selective attention on r noise depended not only on the population tuning to the attended feature, but also on the tuning to the distractor feature. To attempt to explain how these observed effects might support enhanced perceptual performance, we propose an extension of a simple and influential model in which shifts in r noise can simultaneously enhance the representation of the attended feature while suppressing the distractor. These findings present a novel mechanism by which attention modulates neural populations to support sensory processing in cluttered environments. SIGNIFICANCE STATEMENT Although feature-selective attention constitutes one of the building blocks of listening in natural environments, its neural bases remain obscure. To address this, we developed a novel auditory feature-selective attention task and measured noise correlations ( r noise ) in rhesus macaque A1 during task performance. Unlike previous studies showing that the effect of attention on r noise depends on population tuning to the attended feature, we show that the effect of attention depends on the tuning to the distractor feature as well. We suggest that these effects represent an efficient process by which sensory cortex simultaneously enhances relevant information and suppresses irrelevant information. Copyright © 2017 the authors 0270-6474/17/375378-15$15.00/0.

Feature-Selective Attention Adaptively Shifts Noise Correlations in Primary Auditory Cortex

PubMed Central

2017-01-01

Sensory environments often contain an overwhelming amount of information, with both relevant and irrelevant information competing for neural resources. Feature attention mediates this competition by selecting the sensory features needed to form a coherent percept. How attention affects the activity of populations of neurons to support this process is poorly understood because population coding is typically studied through simulations in which one sensory feature is encoded without competition. Therefore, to study the effects of feature attention on population-based neural coding, investigations must be extended to include stimuli with both relevant and irrelevant features. We measured noise correlations (rnoise) within small neural populations in primary auditory cortex while rhesus macaques performed a novel feature-selective attention task. We found that the effect of feature-selective attention on rnoise depended not only on the population tuning to the attended feature, but also on the tuning to the distractor feature. To attempt to explain how these observed effects might support enhanced perceptual performance, we propose an extension of a simple and influential model in which shifts in rnoise can simultaneously enhance the representation of the attended feature while suppressing the distractor. These findings present a novel mechanism by which attention modulates neural populations to support sensory processing in cluttered environments. SIGNIFICANCE STATEMENT Although feature-selective attention constitutes one of the building blocks of listening in natural environments, its neural bases remain obscure. To address this, we developed a novel auditory feature-selective attention task and measured noise correlations (rnoise) in rhesus macaque A1 during task performance. Unlike previous studies showing that the effect of attention on rnoise depends on population tuning to the attended feature, we show that the effect of attention depends on the tuning to the distractor feature as well. We suggest that these effects represent an efficient process by which sensory cortex simultaneously enhances relevant information and suppresses irrelevant information. PMID:28432139

Attention-driven auditory cortex short-term plasticity helps segregate relevant sounds from noise

PubMed Central

Ahveninen, Jyrki; Hämäläinen, Matti; Jääskeläinen, Iiro P.; Ahlfors, Seppo P.; Huang, Samantha; Raij, Tommi; Sams, Mikko; Vasios, Christos E.; Belliveau, John W.

2011-01-01

How can we concentrate on relevant sounds in noisy environments? A “gain model” suggests that auditory attention simply amplifies relevant and suppresses irrelevant afferent inputs. However, it is unclear whether this suffices when attended and ignored features overlap to stimulate the same neuronal receptive fields. A “tuning model” suggests that, in addition to gain, attention modulates feature selectivity of auditory neurons. We recorded magnetoencephalography, EEG, and functional MRI (fMRI) while subjects attended to tones delivered to one ear and ignored opposite-ear inputs. The attended ear was switched every 30 s to quantify how quickly the effects evolve. To produce overlapping inputs, the tones were presented alone vs. during white-noise masking notch-filtered ±1/6 octaves around the tone center frequencies. Amplitude modulation (39 vs. 41 Hz in opposite ears) was applied for “frequency tagging” of attention effects on maskers. Noise masking reduced early (50–150 ms; N1) auditory responses to unattended tones. In support of the tuning model, selective attention canceled out this attenuating effect but did not modulate the gain of 50–150 ms activity to nonmasked tones or steady-state responses to the maskers themselves. These tuning effects originated at nonprimary auditory cortices, purportedly occupied by neurons that, without attention, have wider frequency tuning than ±1/6 octaves. The attentional tuning evolved rapidly, during the first few seconds after attention switching, and correlated with behavioral discrimination performance. In conclusion, a simple gain model alone cannot explain auditory selective attention. In nonprimary auditory cortices, attention-driven short-term plasticity retunes neurons to segregate relevant sounds from noise. PMID:21368107

Two particle model for studying the effects of space-charge force on strong head-tail instabilities

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

Chin, Yong Ho; Chao, Alexander Wu; Blaskiewicz, Michael M.

In this paper, we present a new two particle model for studying the strong head-tail instabilities in the presence of the space-charge force. It is a simple expansion of the well-known two particle model for strong head-tail instability and is still analytically solvable. No chromaticity effect is included. It leads to a formula for the growth rate as a function of the two dimensionless parameters: the space-charge tune shift parameter (normalized by the synchrotron tune) and the wakefield strength, Upsilon. The three-dimensional contour plot of the growth rate as a function of those two dimensionless parameters reveals stopband structures. Manymore » simulation results generally indicate that a strong head-tail instability can be damped by a weak space-charge force, but the beam becomes unstable again when the space-charge force is further increased. The new two particle model indicates a similar behavior. In weak space-charge regions, additional tune shifts by the space-charge force dissolve the mode coupling. As the space-charge force is increased, they conversely restore the mode coupling, but then a further increase of the space-charge force decouples the modes again. Lastly, this mode coupling/decoupling behavior creates the stopband structures.« less

Two particle model for studying the effects of space-charge force on strong head-tail instabilities

DOE PAGES

Chin, Yong Ho; Chao, Alexander Wu; Blaskiewicz, Michael M.

2016-01-19

In this paper, we present a new two particle model for studying the strong head-tail instabilities in the presence of the space-charge force. It is a simple expansion of the well-known two particle model for strong head-tail instability and is still analytically solvable. No chromaticity effect is included. It leads to a formula for the growth rate as a function of the two dimensionless parameters: the space-charge tune shift parameter (normalized by the synchrotron tune) and the wakefield strength, Upsilon. The three-dimensional contour plot of the growth rate as a function of those two dimensionless parameters reveals stopband structures. Manymore » simulation results generally indicate that a strong head-tail instability can be damped by a weak space-charge force, but the beam becomes unstable again when the space-charge force is further increased. The new two particle model indicates a similar behavior. In weak space-charge regions, additional tune shifts by the space-charge force dissolve the mode coupling. As the space-charge force is increased, they conversely restore the mode coupling, but then a further increase of the space-charge force decouples the modes again. Lastly, this mode coupling/decoupling behavior creates the stopband structures.« less

Optimal placement of tuning masses for vibration reduction in helicopter rotor blades

NASA Technical Reports Server (NTRS)

Pritchard, Jocelyn I.; Adelman, Howard M.

1988-01-01

Described are methods for reducing vibration in helicopter rotor blades by determining optimum sizes and locations of tuning masses through formal mathematical optimization techniques. An optimization procedure is developed which employs the tuning masses and corresponding locations as design variables which are systematically changed to achieve low values of shear without a large mass penalty. The finite-element structural analysis of the blade and the optimization formulation require development of discretized expressions for two performance parameters: modal shaping parameter and modal shear amplitude. Matrix expressions for both quantities and their sensitivity derivatives are developed. Three optimization strategies are developed and tested. The first is based on minimizing the modal shaping parameter which indirectly reduces the modal shear amplitudes corresponding to each harmonic of airload. The second strategy reduces these amplitudes directly, and the third strategy reduces the shear as a function of time during a revolution of the blade. The first strategy works well for reducing the shear for one mode responding to a single harmonic of the airload, but has been found in some cases to be ineffective for more than one mode. The second and third strategies give similar results and show excellent reduction of the shear with a low mass penalty.

Simple graph models of information spread in finite populations

PubMed Central

Voorhees, Burton; Ryder, Bergerud

2015-01-01

We consider several classes of simple graphs as potential models for information diffusion in a structured population. These include biases cycles, dual circular flows, partial bipartite graphs and what we call ‘single-link’ graphs. In addition to fixation probabilities, we study structure parameters for these graphs, including eigenvalues of the Laplacian, conductances, communicability and expected hitting times. In several cases, values of these parameters are related, most strongly so for partial bipartite graphs. A measure of directional bias in cycles and circular flows arises from the non-zero eigenvalues of the antisymmetric part of the Laplacian and another measure is found for cycles as the value of the transition probability for which hitting times going in either direction of the cycle are equal. A generalization of circular flow graphs is used to illustrate the possibility of tuning edge weights to match pre-specified values for graph parameters; in particular, we show that generalizations of circular flows can be tuned to have fixation probabilities equal to the Moran probability for a complete graph by tuning vertex temperature profiles. Finally, single-link graphs are introduced as an example of a graph involving a bottleneck in the connection between two components and these are compared to the partial bipartite graphs. PMID:26064661

Differential Modulation of Excitatory and Inhibitory Neurons during Periodic Stimulation

PubMed Central

Mahmud, Mufti; Vassanelli, Stefano

2016-01-01

Non-invasive transcranial neuronal stimulation, in addition to deep brain stimulation, is seen as a promising therapeutic and diagnostic approach for an increasing number of neurological diseases such as epilepsy, cluster headaches, depression, specific type of blindness, and other central nervous system disfunctions. Improving its effectiveness and widening its range of use may strongly rely on development of proper stimulation protocols that are tailored to specific brain circuits and that are based on a deep knowledge of different neuron types response to stimulation. To this aim, we have performed a simulation study on the behavior of excitatory and inhibitory neurons subject to sinusoidal stimulation. Due to the intrinsic difference in membrane conductance properties of excitatory and inhibitory neurons, we show that their firing is differentially modulated by the wave parameters. We analyzed the behavior of the two neuronal types for a broad range of stimulus frequency and amplitude and demonstrated that, within a small-world network prototype, parameters tuning allow for a selective enhancement or suppression of the excitation/inhibition ratio. PMID:26941602

Neural Mechanisms for Acoustic Signal Detection under Strong Masking in an Insect

PubMed Central

Römer, Heiner

2015-01-01

Communication is fundamental for our understanding of behavior. In the acoustic modality, natural scenes for communication in humans and animals are often very noisy, decreasing the chances for signal detection and discrimination. We investigated the mechanisms enabling selective hearing under natural noisy conditions for auditory receptors and interneurons of an insect. In the studied katydid Mecopoda elongata species-specific calling songs (chirps) are strongly masked by signals of another species, both communicating in sympatry. The spectral properties of the two signals are similar and differ only in a small frequency band at 2 kHz present in the chirping species. Receptors sharply tuned to 2 kHz are completely unaffected by the masking signal of the other species, whereas receptors tuned to higher audio and ultrasonic frequencies show complete masking. Intracellular recordings of identified interneurons revealed two mechanisms providing response selectivity to the chirp. (1) Response selectivity is when several identified interneurons exhibit remarkably selective responses to the chirps, even at signal-to-noise ratios of −21 dB, since they are sharply tuned to 2 kHz. Their dendritic arborizations indicate selective connectivity with low-frequency receptors tuned to 2 kHz. (2) Novelty detection is when a second group of interneurons is broadly tuned but, because of strong stimulus-specific adaptation to the masker spectrum and “novelty detection” to the 2 kHz band present only in the conspecific signal, these interneurons start to respond selectively to the chirp shortly after the onset of the continuous masker. Both mechanisms provide the sensory basis for hearing at unfavorable signal-to-noise ratios. SIGNIFICANCE STATEMENT Animal and human acoustic communication may suffer from the same “cocktail party problem,” when communication happens in noisy social groups. We address solutions for this problem in a model system of two katydids, where one species produces an extremely noisy sound, yet the second species still detects its own song. Using intracellular recording techniques we identified two neural mechanisms underlying the surprising behavioral signal detection at the level of single identified interneurons. These neural mechanisms for signal detection are likely to be important for other sensory modalities as well, where noise in the communication channel creates similar problems. Also, they may be used for the development of algorithms for the filtering of specific signals in technical microphones or hearing aids. PMID:26203150

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction.

PubMed

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John Bo

2008-10-29

We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024-1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581-590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6 degrees C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, epsilon of 0.21) and an RMSE of 45.1 degrees C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3 degrees C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5 degrees C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors.

Tradeoff between magnet volume and tuning capacitor in a free piston Stirling engine power generation system

NASA Astrophysics Data System (ADS)

Fu, Z. X.; Nasar, S. A.; Rosswurm, Mark

This paper presents the criteria in selecting the size of the tuning capacitor, and the cost tradeoff between magnet volume and tuning capacitor in a free piston Stirling engine power generation system. The permissible range of capacitor size corresponding to different magnet volume, in order to prevent magnet demagnetization and stabilize the operation of the system, is determined. Within the permissible range suitable capacitor size may be selected to compensate the inductive load of the system to improve the overall power factor. If the capacitor size is not in the permissible range, there would exist a danger of losing magnet strength, or unstable operation of the engine that would destroy the engine due to unbounded amplitude of piston oscillations. The theory developed is then applied to a practical system, and the cost tradeoff between magnet volume and capacitor is studied.

Design and construction of a novel 1H/19F double-tuned coil system using PIN-diode switches at 9.4T.

PubMed

Choi, Chang-Hoon; Hong, Suk-Min; Ha, YongHyun; Shah, N Jon

2017-06-01

A double-tuned 1 H/ 19 F coil using PIN-diode switches was developed and its performance evaluated. The is a key difference from the previous developments being that this design used a PIN-diode switch in series with an additionally inserted inductor in parallel to one of the capacitors on the loop. The probe was adjusted to 19 F when the reverse bias voltage was applied (PIN-diode OFF), whilst it was switched to 1 H when forward current was flowing (PIN-diode ON). S-parameters and Q-factors of single- and double-tuned coils were examined and compared with/without a phantom on the bench. Imaging experiments were carried out on a 9.4T preclinical scanner. All coils were tuned at resonance frequencies and matched well. It is shown that the Q-ratio and SNR of double-tuned coil at 19 F frequency are nearly as good as those of a single-tuned coil. Since the operating frequency was tuned to 19 F when the PIN-diodes were turned off, losses due to PIN-diodes were substantially lower resulting in the provision of excellent image quality of X-nuclei. Copyright © 2017 Elsevier Inc. All rights reserved.

An automated method of tuning an attitude estimator

NASA Technical Reports Server (NTRS)

Mason, Paul A. C.; Mook, D. Joseph

1995-01-01

Attitude determination is a major element of the operation and maintenance of a spacecraft. There are several existing methods of determining the attitude of a spacecraft. One of the most commonly used methods utilizes the Kalman filter to estimate the attitude of the spacecraft. Given an accurate model of a system and adequate observations, a Kalman filter can produce accurate estimates of the attitude. If the system model, filter parameters, or observations are inaccurate, the attitude estimates may be degraded. Therefore, it is advantageous to develop a method of automatically tuning the Kalman filter to produce the accurate estimates. In this paper, a three-axis attitude determination Kalman filter, which uses only magnetometer measurements, is developed and tested using real data. The appropriate filter parameters are found via the Process Noise Covariance Estimator (PNCE). The PNCE provides an optimal criterion for determining the best filter parameters.

Fractional order sliding-mode control based on parameters auto-tuning for velocity control of permanent magnet synchronous motor.

PubMed

Zhang, BiTao; Pi, YouGuo; Luo, Ying

2012-09-01

A fractional order sliding mode control (FROSMC) scheme based on parameters auto-tuning for the velocity control of permanent magnet synchronous motor (PMSM) is proposed in this paper. The control law of the proposed F(R)OSMC scheme is designed according to Lyapunov stability theorem. Based on the property of transferring energy with adjustable type in F(R)OSMC, this paper analyzes the chattering phenomenon in classic sliding mode control (SMC) is attenuated with F(R)OSMC system. A fuzzy logic inference scheme (FLIS) is utilized to obtain the gain of switching control. Simulations and experiments demonstrate that the proposed FROSMC not only achieve better control performance with smaller chatting than that with integer order sliding mode control, but also is robust to external load disturbance and parameter variations. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Basic electronic properties of iron selenide under variation of structural parameters

NASA Astrophysics Data System (ADS)

Guterding, Daniel; Jeschke, Harald O.; Valentí, Roser

2017-09-01

Since the discovery of high-temperature superconductivity in the thin-film FeSe /SrTiO3 system, iron selenide and its derivates have been intensively scrutinized. Using ab initio density functional theory calculations we review the electronic structures that could be realized in iron selenide if the structural parameters could be tuned at liberty. We calculate the momentum dependence of the susceptibility and investigate the symmetry of electron pairing within the random phase approximation. Both the susceptibility and the symmetry of electron pairing depend on the structural parameters in a nontrivial way. These results are consistent with the known experimental behavior of binary iron chalcogenides and, at the same time, reveal two promising ways of tuning superconducting transition temperatures in these materials: on one hand by expanding the iron lattice of FeSe at constant iron-selenium distance and, on the other hand, by increasing the iron-selenium distance with unchanged iron lattice.

Temporal tuning in the bat auditory cortex is sharper when studied with natural echolocation sequences.

PubMed

Beetz, M Jerome; Hechavarría, Julio C; Kössl, Manfred

2016-06-30

Precise temporal coding is necessary for proper acoustic analysis. However, at cortical level, forward suppression appears to limit the ability of neurons to extract temporal information from natural sound sequences. Here we studied how temporal processing can be maintained in the bats' cortex in the presence of suppression evoked by natural echolocation streams that are relevant to the bats' behavior. We show that cortical neurons tuned to target-distance actually profit from forward suppression induced by natural echolocation sequences. These neurons can more precisely extract target distance information when they are stimulated with natural echolocation sequences than during stimulation with isolated call-echo pairs. We conclude that forward suppression does for time domain tuning what lateral inhibition does for selectivity forms such as auditory frequency tuning and visual orientation tuning. When talking about cortical processing, suppression should be seen as a mechanistic tool rather than a limiting element.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines.

PubMed

Khan, Arif Ul Maula; Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts.

A New Feedback-Based Method for Parameter Adaptation in Image Processing Routines

PubMed Central

Mikut, Ralf; Reischl, Markus

2016-01-01

The parametrization of automatic image processing routines is time-consuming if a lot of image processing parameters are involved. An expert can tune parameters sequentially to get desired results. This may not be productive for applications with difficult image analysis tasks, e.g. when high noise and shading levels in an image are present or images vary in their characteristics due to different acquisition conditions. Parameters are required to be tuned simultaneously. We propose a framework to improve standard image segmentation methods by using feedback-based automatic parameter adaptation. Moreover, we compare algorithms by implementing them in a feedforward fashion and then adapting their parameters. This comparison is proposed to be evaluated by a benchmark data set that contains challenging image distortions in an increasing fashion. This promptly enables us to compare different standard image segmentation algorithms in a feedback vs. feedforward implementation by evaluating their segmentation quality and robustness. We also propose an efficient way of performing automatic image analysis when only abstract ground truth is present. Such a framework evaluates robustness of different image processing pipelines using a graded data set. This is useful for both end-users and experts. PMID:27764213

Experimental design of a twin-column countercurrent gradient purification process.

PubMed

Steinebach, Fabian; Ulmer, Nicole; Decker, Lara; Aumann, Lars; Morbidelli, Massimo

2017-04-07

As typical for separation processes, single unit batch chromatography exhibits a trade-off between purity and yield. The twin-column MCSGP (multi-column countercurrent solvent gradient purification) process allows alleviating such trade-offs, particularly in the case of difficult separations. In this work an efficient and reliable procedure for the design of the twin-column MCSGP process is developed. This is based on a single batch chromatogram, which is selected as the design chromatogram. The derived MCSGP operation is not intended to provide optimal performance, but it provides the target product in the selected fraction of the batch chromatogram, but with higher yield. The design procedure is illustrated for the isolation of the main charge isoform of a monoclonal antibody from Protein A eluate with ion-exchange chromatography. The main charge isoform was obtained at a purity and yield larger than 90%. At the same time process related impurities such as HCP and leached Protein A as well as aggregates were at least equally well removed. Additionally, the impact of several design parameters on the process performance in terms of purity, yield, productivity and buffer consumption is discussed. The obtained results can be used for further fine-tuning of the process parameters so as to improve its performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Wavelength tuning of multimode interference bandpass filters by mechanical bending: experiment and theory in comparison

NASA Astrophysics Data System (ADS)

Walbaum, T.; Fallnich, C.

2012-07-01

We present the tuning of multimode interference bandpass filters made of standard fibers by mechanical bending. Our setup allows continuous adjustment of the bending radius from infinity down to about 5 cm. The impact of bending on the transmission spectrum and on polarization is investigated experimentally, and a filter with a continuous tuning range of 13.6 nm and 86 % peak transmission was realized. By use of numerical simulations employing a semi-analytical mode expansion approach, we obtain quantitative understanding of the underlying physics. Further breakdown of the governing equations enables us to identify the fiber parameters that are relevant for the design of customized filters.

Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

2014-07-01

The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

Tuned range separated hybrid functionals for solvated low bandgap oligomers

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

Queiroz, Thiago B. de, E-mail: thiago.branquinho-de-queiroz@uni-bayreuth.de; Kümmel, Stephan

2015-07-21

The description of charge transfer excitations has long been a challenge to time dependent density functional theory. The recently developed concept of “optimally tuned range separated hybrid (OT-RSH) functionals” has proven to describe charge transfer excitations accurately in many cases. However, describing solvated or embedded systems is yet a challenge. This challenge is not only computational but also conceptual, because the tuning requires identifying a specific orbital, typically the highest occupied one of the molecule under study. For solvated molecules, this orbital may be delocalized over the solvent. We here demonstrate that one way of overcoming this problem is tomore » use a locally projected self-consistent field diagonalization on an absolutely localized molecular orbital expansion. We employ this approach to determine ionization energies and the optical gap of solvated oligothiophenes, i.e., paradigm low gap systems that are of relevance in organic electronics. Dioxane solvent molecules are explicitly represented in our calculations, and the ambiguities of straightforward parameter tuning in solution are elucidated. We show that a consistent estimate of the optimal range separated parameter (ω) at the limit of bulk solvation can be obtained by gradually extending the solvated system. In particular, ω is influenced by the solvent beyond the first coordination sphere. For determining ionization energies, a considerable number of solvent molecules on the first solvation shell must be taken into account. We demonstrate that accurately calculating optical gaps of solvated systems using OT-RSH can be done in three steps: (i) including the chemical environment when determining the range-separation parameter, (ii) taking into account the screening due to the solvent, and (iii) using realistic molecular geometries.« less

Frequency pulling in a low-voltage medium-power gyrotron

NASA Astrophysics Data System (ADS)

Luo, Li; Du, Chao-Hai; Huang, Ming-Guang; Liu, Pu-Kun

2018-04-01

Many recent biomedical applications use medium-power frequency-tunable terahertz (THz) sources, such as sensitivity-enhanced nuclear magnetic resonance, THz imaging, and biomedical treatment. As a promising candidate, a low-voltage gyrotron can generate watt-level, continuous THz-wave radiation. In particular, the frequency-pulling effect in a gyrotron, namely, the effect of the electron beam parameters on the oscillation frequency, can be used to tune the operating frequency. Most previous investigations used complicated and time-consuming gyrotron nonlinear theory to study the influence of many beam parameters on the interaction performance. While gyrotron linear theory investigation demonstrates the advantages of rapidly and clearly revealing the physical influence of individual key beam parameters on the overall system performance, this paper demonstrates systematically the use of gyrotron linear theory to study the frequency-pulling effect in a low-voltage gyrotron with either a Gaussian or a sinusoidal axial-field profile. Furthermore, simulations of a gyrotron operating in the first axial mode are carried out in the framework of nonlinear theory as a contrast. Close agreement is achieved between the two theories. Besides, some interesting results are obtained. In a low-current sinusoidal-profile cavity, the ranges of frequency variation for different axial modes are isolated from each other, and the frequency tuning bandwidth for each axial mode increases by increasing either the beam voltage or pitch factor. Lowering the voltage, the total tuning ranges are squeezed and become concentrated. However, the isolated frequency regions of each axial mode cannot be linked up unless the beam current is increased, meaning that higher current operation is the key to achieving a wider and continuous tuning frequency range. The results presented in this paper can provide a reference for designing a broadband low-voltage gyrotron.

A multichip aVLSI system emulating orientation selectivity of primary visual cortical cells.

PubMed

Shimonomura, Kazuhiro; Yagi, Tetsuya

2005-07-01

In this paper, we designed and fabricated a multichip neuromorphic analog very large scale integrated (aVLSI) system, which emulates the orientation selective response of the simple cell in the primary visual cortex. The system consists of a silicon retina and an orientation chip. An image, which is filtered by a concentric center-surround (CS) antagonistic receptive field of the silicon retina, is transferred to the orientation chip. The image transfer from the silicon retina to the orientation chip is carried out with analog signals. The orientation chip selectively aggregates multiple pixels of the silicon retina, mimicking the feedforward model proposed by Hubel and Wiesel. The chip provides the orientation-selective (OS) outputs which are tuned to 0 degrees, 60 degrees, and 120 degrees. The feed-forward aggregation reduces the fixed pattern noise that is due to the mismatch of the transistors in the orientation chip. The spatial properties of the orientation selective response were examined in terms of the adjustable parameters of the chip, i.e., the number of aggregated pixels and size of the receptive field of the silicon retina. The multichip aVLSI architecture used in the present study can be applied to implement higher order cells such as the complex cell of the primary visual cortex.

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep convolutional networks against brain activity. The ability to use whole networks in a single encoding model yields state-of-the-art prediction accuracy. Our results suggest a wide variety of uses for the feature-weighted receptive field model, from retinotopic mapping with natural scenes, to regressing the activities of whole deep neural networks onto measured brain activity. Copyright © 2017. Published by Elsevier Inc.

A Tuning-AHELO Conceptual Framework of Expected Desired/Learning Outcomes in Engineering. OECD Education Working Papers, Number 60

ERIC Educational Resources Information Center

OECD Publishing (NJ1), 2011

2011-01-01

The OECD Secretariat, at the invitation of the AHELO Group of National Experts, contracted the Tuning Association to undertake initial development work on learning outcomes to be used for valid and reliable assessments of students from diverse institutions and countries. The two disciplines selected for the AEHLO Feasibility Study are engineering…

Multifunctional and Context-Dependent Control of Vocal Acoustics by Individual Muscles

PubMed Central

Srivastava, Kyle H.; Elemans, Coen P.H.

2015-01-01

The relationship between muscle activity and behavioral output determines how the brain controls and modifies complex skills. In vocal control, ensembles of muscles are used to precisely tune single acoustic parameters such as fundamental frequency and sound amplitude. If individual vocal muscles were dedicated to the control of single parameters, then the brain could control each parameter independently by modulating the appropriate muscle or muscles. Alternatively, if each muscle influenced multiple parameters, a more complex control strategy would be required to selectively modulate a single parameter. Additionally, it is unknown whether the function of single muscles is fixed or varies across different vocal gestures. A fixed relationship would allow the brain to use the same changes in muscle activation to, for example, increase the fundamental frequency of different vocal gestures, whereas a context-dependent scheme would require the brain to calculate different motor modifications in each case. We tested the hypothesis that single muscles control multiple acoustic parameters and that the function of single muscles varies across gestures using three complementary approaches. First, we recorded electromyographic data from vocal muscles in singing Bengalese finches. Second, we electrically perturbed the activity of single muscles during song. Third, we developed an ex vivo technique to analyze the biomechanical and acoustic consequences of single-muscle perturbations. We found that single muscles drive changes in multiple parameters and that the function of single muscles differs across vocal gestures, suggesting that the brain uses a complex, gesture-dependent control scheme to regulate vocal output. PMID:26490859

Oscillon in Einstein-scalar system with double well potential and its properties.

NASA Astrophysics Data System (ADS)

Ikeda, Taishi; Yoo, Chul-Moon; Cardoso, Vitor

2018-01-01

The dynamical evolution of self-interacting scalar field has many nontrivial behaviors, which tell us many lessons in a nonlinear dynamics. On Minkowski spacetime, the scalar field with double well potential has localized, non-singular, time-dependent, long-lived solutions, which are called oscillons. The lifetime of the oscillon depends on the initial conditions. Furthermore, when the initial parameter is fine-tuned, oscillons can be infinitely, and type I critical behavior is observed. Here, we investigate the Einstein-scalar system with double well potential. We show that oscillons exist in this system, and discuss the behavior when the initial parameter is fine-tuned. Our results suggests that a new type of critical behavior appears in this theory.

Many-body localization in a long range XXZ model with random-field

NASA Astrophysics Data System (ADS)

Li, Bo

2016-12-01

Many-body localization (MBL) in a long range interaction XXZ model with random field are investigated. Using the exact diagonal method, the MBL phase diagram with different tuning parameters and interaction range is obtained. It is found that the phase diagram of finite size results supplies strong evidence to confirm that the threshold interaction exponent α = 2. The tuning parameter Δ can efficiently change the MBL edge in high energy density stats, thus the system can be controlled to transfer from thermal phase to MBL phase by changing Δ. The energy level statistics data are consistent with result of the MBL phase diagram. However energy level statistics data cannot detect the thermal phase correctly in extreme long range case.

Tuning of PID controller using optimization techniques for a MIMO process

NASA Astrophysics Data System (ADS)

Thulasi dharan, S.; Kavyarasan, K.; Bagyaveereswaran, V.

2017-11-01

In this paper, two processes were considered one is Quadruple tank process and the other is CSTR (Continuous Stirred Tank Reactor) process. These are majorly used in many industrial applications for various domains, especially, CSTR in chemical plants.At first mathematical model of both the process is to be done followed by linearization of the system due to MIMO process and controllers are the major part to control the whole process to our desired point as per the applications so the tuning of the controller plays a major role among the whole process. For tuning of parameters we use two optimizations techniques like Particle Swarm Optimization, Genetic Algorithm. The above techniques are majorly used in different applications to obtain which gives the best among all, we use these techniques to obtain the best tuned values among many. Finally, we will compare the performance of the each process with both the techniques.

Model-Based Self-Tuning Multiscale Method for Combustion Control

NASA Technical Reports Server (NTRS)

Le, Dzu, K.; DeLaat, John C.; Chang, Clarence T.; Vrnak, Daniel R.

2006-01-01

A multi-scale representation of the combustor dynamics was used to create a self-tuning, scalable controller to suppress multiple instability modes in a liquid-fueled aero engine-derived combustor operating at engine-like conditions. Its self-tuning features designed to handle the uncertainties in the combustor dynamics and time-delays are essential for control performance and robustness. The controller was implemented to modulate a high-frequency fuel valve with feedback from dynamic pressure sensors. This scalable algorithm suppressed pressure oscillations of different instability modes by as much as 90 percent without the peak-splitting effect. The self-tuning logic guided the adjustment of controller parameters and converged quickly toward phase-lock for optimal suppression of the instabilities. The forced-response characteristics of the control model compare well with those of the test rig on both the frequency-domain and the time-domain.

Dynamical tuning for MPC using population games: A water supply network application.

PubMed

Barreiro-Gomez, Julian; Ocampo-Martinez, Carlos; Quijano, Nicanor

2017-07-01

Model predictive control (MPC) is a suitable strategy for the control of large-scale systems that have multiple design requirements, e.g., multiple physical and operational constraints. Besides, an MPC controller is able to deal with multiple control objectives considering them within the cost function, which implies to determine a proper prioritization for each of the objectives. Furthermore, when the system has time-varying parameters and/or disturbances, the appropriate prioritization might vary along the time as well. This situation leads to the need of a dynamical tuning methodology. This paper addresses the dynamical tuning issue by using evolutionary game theory. The advantages of the proposed method are highlighted and tested over a large-scale water supply network with periodic time-varying disturbances. Finally, results are analyzed with respect to a multi-objective MPC controller that uses static tuning. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Electronic frequency tuning of the acousto-optic mode-locking device of a laser

NASA Astrophysics Data System (ADS)

Magdich, L. N.; Balakshy, V. I.; Mantsevich, S. N.

2017-11-01

The effect of the electronic tuning of the acoustic resonances in an acousto-optic mode-locking device of a laser is investigated theoretically and experimentally. The problem of the excitation of a Fabry-Perot acoustic resonator by a plate-like piezoelectric transducer (PET) is solved in the approximation of plane acoustic waves taking into consideration the actual parameters of an RF generator and the elements for matching the PET to the generator. Resonances are tuned by changing the matching inductance that was connected in parallel to the transducer of the acousto-optic cell. The cell used in the experiment was manufactured from fused silica and included a lithium niobate PET. Changes in the matching inductance in the range of 0.025 to 0.2 μH provided the acoustic-resonance frequency tuning by 0.19 MHz, which exceeds the acoustic- resonance half-width.

Graphene Dirac point tuned by ferroelectric polarization field

NASA Astrophysics Data System (ADS)

Wang, Xudong; Chen, Yan; Wu, Guangjian; Wang, Jianlu; Tian, Bobo; Sun, Shuo; Shen, Hong; Lin, Tie; Hu, Weida; Kang, Tingting; Tang, Minghua; Xiao, Yongguang; Sun, Jinglan; Meng, Xiangjian; Chu, Junhao

2018-04-01

Graphene has received numerous attention for future nanoelectronics and optoelectronics. The Dirac point is a key parameter of graphene that provides information about its carrier properties. There are lots of methods to tune the Dirac point of graphene, such as chemical doping, impurities, defects, and disorder. In this study, we report a different approach to tune the Dirac point of graphene using a ferroelectric polarization field. The Dirac point can be adjusted to near the ferroelectric coercive voltage regardless its original position. We have ensured this phenomenon by temperature-dependent experiments, and analyzed its mechanism with the theory of impurity correlation in graphene. Additionally, with the modulation of ferroelectric polymer, the current on/off ratio and mobility of graphene transistor both have been improved. This work provides an effective method to tune the Dirac point of graphene, which can be readily used to configure functional devices such as p-n junctions and inverters.

Economy of scale: a motion sensor with variable speed tuning.

PubMed

Perrone, John A

2005-01-26

We have previously presented a model of how neurons in the primate middle temporal (MT/V5) area can develop selectivity for image speed by using common properties of the V1 neurons that precede them in the visual motion pathway (J. A. Perrone & A. Thiele, 2002). The motion sensor developed in this model is based on two broad classes of V1 complex neurons (sustained and transient). The S-type neuron has low-pass temporal frequency tuning, p(omega), and the T-type has band-pass temporal frequency tuning, m(omega). The outputs from the S and T neurons are combined in a special way (weighted intersection mechanism [WIM]) to generate a sensor tuned to a particular speed, v. Here I go on to show that if the S and T temporal frequency tuning functions have a particular form (i.e., p(omega)/(m(omega) = k/omega), then a motion sensor with variable speed tuning can be generated from just two V1 neurons. A simple scaling of the S- or T-type neuron output before it is incorporated into the WIM model produces a motion sensor that can be tuned to a wide continuous range of optimal speeds.

Wide range optofluidically tunable multimode interference fiber laser

NASA Astrophysics Data System (ADS)

Antonio-Lopez, J. E.; Sanchez-Mondragon, J. J.; LiKamWa, P.; May-Arrioja, D. A.

2014-08-01

An optofluidically tunable fiber laser based on multimode interference (MMI) effects with a wide tuning range is proposed and demonstrated. The tunable mechanism is based on an MMI fiber filter fabricated using a special fiber known as no-core fiber, which is a multimode fiber (MMF) without cladding. Therefore, when the MMI filter is covered by liquid the optical properties of the no-core fiber are modified, which allow us to tune the peak wavelength response of the MMI filter. Rather than applying the liquid on the entire no-core fiber, we change the liquid level along the no-core fiber, which provides a highly linear tuning response. In addition, by selecting the adequate refractive index of the liquid we can also choose the tuning range. We demonstrate the versatility of the optofluidically tunable MMI filter by wavelength tuning two different gain media, erbium doped fiber and a semiconductor optical amplifier, achieving tuning ranges of 55 and 90 nm respectively. In both cases, we achieve side-mode suppression ratios (SMSR) better than 50 dBm with output power variations of less than 0.76 dBm over the whole tuning range.

π-Clamp-mediated cysteine conjugation

NASA Astrophysics Data System (ADS)

Zhang, Chi; Welborn, Matthew; Zhu, Tianyu; Yang, Nicole J.; Santos, Michael S.; van Voorhis, Troy; Pentelute, Bradley L.

2016-02-01

Site-selective functionalization of complex molecules is one of the most significant challenges in chemistry. Typically, protecting groups or catalysts must be used to enable the selective modification of one site among many that are similarly reactive, and general strategies that selectively tune the local chemical environment around a target site are rare. Here, we show a four-amino-acid sequence (Phe-Cys-Pro-Phe), which we call the ‘π-clamp’, that tunes the reactivity of its cysteine thiol for site-selective conjugation with perfluoroaromatic reagents. We use the π-clamp to selectively modify one cysteine site in proteins containing multiple endogenous cysteine residues. These examples include antibodies and cysteine-based enzymes that would be difficult to modify selectively using standard cysteine-based methods. Antibodies modified using the π-clamp retained binding affinity to their targets, enabling the synthesis of site-specific antibody-drug conjugates for selective killing of HER2-positive breast cancer cells. The π-clamp is an unexpected approach to mediate site-selective chemistry and provides new avenues to modify biomolecules for research and therapeutics.

Seismic design of passive tuned mass damper parameters using active control algorithm

NASA Astrophysics Data System (ADS)

Chang, Chia-Ming; Shia, Syuan; Lai, Yong-An

2018-07-01

Tuned mass dampers are a widely-accepted control method to effectively reduce the vibrations of tall buildings. A tuned mass damper employs a damped harmonic oscillator with specific dynamic characteristics, thus the response of structures can be regulated by the additive dynamics. The additive dynamics are, however, similar to the feedback control system in active control. Therefore, the objective of this study is to develop a new tuned mass damper design procedure based on the active control algorithm, i.e., the H2/LQG control. This design facilitates the similarity of feedback control in the active control algorithm to determine the spring and damper in a tuned mass damper. Given a mass ratio between the damper and structure, the stiffness and damping coefficient of the tuned mass damper are derived by minimizing the response objective function of the primary structure, where the structural properties are known. Varying a single weighting in this objective function yields the optimal TMD design when the minimum peak in the displacement transfer function of the structure with the TMD is met. This study examines various objective functions as well as derives the associated equations to compute the stiffness and damping coefficient. The relationship between the primary structure and optimal tuned mass damper is parametrically studied. Performance is evaluated by exploring the h2-and h∞-norms of displacements and accelerations of the primary structure. In time-domain analysis, the damping effectiveness of the tune mass damper controlled structures is investigated under impulse excitation. Structures with the optimal tuned mass dampers are also assessed under seismic excitation. As a result, the proposed design procedure produces an effective tuned mass damper to be employed in a structure against earthquakes.

Lopsided gauge mediation

NASA Astrophysics Data System (ADS)

de Simone, Andrea; Franceschini, Roberto; Giudice, Gian Francesco; Pappadopulo, Duccio; Rattazzi, Riccardo

2011-05-01

It has been recently pointed out that the unavoidable tuning among supersymmetric parameters required to raise the Higgs boson mass beyond its experimental limit opens up new avenues for dealing with the so called μ- B μ problem of gauge mediation. In fact, it allows for accommodating, with no further parameter tuning, large values of B μ and of the other Higgs-sector soft masses, as predicted in models where both μ and B μ are generated at one-loop order. This class of models, called Lopsided Gauge Mediation, offers an interesting alternative to conventional gauge mediation and is characterized by a strikingly different phenomenology, with light higgsinos, very large Higgs pseudoscalar mass, and moderately light sleptons. We discuss general parametric relations involving the fine-tuning of the model and various observables such as the chargino mass and the value of tan β. We build an explicit model and we study the constraints coming from LEP and Tevatron. We show that in spite of new interactions between the Higgs and the messenger superfields, the theory can remain perturbative up to very large scales, thus retaining gauge coupling unification.

Intelligent Systems for Stabilizing Mode-Locked Lasers and Frequency Combs: Machine Learning and Equation-Free Control Paradigms for Self-Tuning Optics

NASA Astrophysics Data System (ADS)

Kutz, J. Nathan; Brunton, Steven L.

2015-12-01

We demonstrate that a software architecture using innovations in machine learning and adaptive control provides an ideal integration platform for self-tuning optics. For mode-locked lasers, commercially available optical telecom components can be integrated with servocontrollers to enact a training and execution software module capable of self-tuning the laser cavity even in the presence of mechanical and/or environmental perturbations, thus potentially stabilizing a frequency comb. The algorithm training stage uses an exhaustive search of parameter space to discover best regions of performance for one or more objective functions of interest. The execution stage first uses a sparse sensing procedure to recognize the parameter space before quickly moving to the near optimal solution and maintaining it using the extremum seeking control protocol. The method is robust and equationfree, thus requiring no detailed or quantitatively accurate model of the physics. It can also be executed on a broad range of problems provided only that suitable objective functions can be found and experimentally measured.

A Caveat Note on Tuning in the Development of Coupled Climate Models

NASA Astrophysics Data System (ADS)

Dommenget, Dietmar; Rezny, Michael

2018-01-01

State-of-the-art coupled general circulation models (CGCMs) have substantial errors in their simulations of climate. In particular, these errors can lead to large uncertainties in the simulated climate response (both globally and regionally) to a doubling of CO2. Currently, tuning of the parameterization schemes in CGCMs is a significant part of the developed. It is not clear whether such tuning actually improves models. The tuning process is (in general) neither documented, nor reproducible. Alternative methods such as flux correcting are not used nor is it clear if such methods would perform better. In this study, ensembles of perturbed physics experiments are performed with the Globally Resolved Energy Balance (GREB) model to test the impact of tuning. The work illustrates that tuning has, in average, limited skill given the complexity of the system, the limited computing resources, and the limited observations to optimize parameters. While tuning may improve model performance (such as reproducing observed past climate), it will not get closer to the "true" physics nor will it significantly improve future climate change projections. Tuning will introduce artificial compensating error interactions between submodels that will hamper further model development. In turn, flux corrections do perform well in most, but not all aspects. A main advantage of flux correction is that it is much cheaper, simpler, more transparent, and it does not introduce artificial error interactions between submodels. These GREB model experiments should be considered as a pilot study to motivate further CGCM studies that address the issues of model tuning.

Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis

PubMed Central

Dura-Bernal, S.; Neymotin, S. A.; Kerr, C. C.; Sivagnanam, S.; Majumdar, A.; Francis, J. T.; Lytton, W. W.

2017-01-01

Biomimetic simulation permits neuroscientists to better understand the complex neuronal dynamics of the brain. Embedding a biomimetic simulation in a closed-loop neuroprosthesis, which can read and write signals from the brain, will permit applications for amelioration of motor, psychiatric, and memory-related brain disorders. Biomimetic neuroprostheses require real-time adaptation to changes in the external environment, thus constituting an example of a dynamic data-driven application system. As model fidelity increases, so does the number of parameters and the complexity of finding appropriate parameter configurations. Instead of adapting synaptic weights via machine learning, we employed major biological learning methods: spike-timing dependent plasticity and reinforcement learning. We optimized the learning metaparameters using evolutionary algorithms, which were implemented in parallel and which used an island model approach to obtain sufficient speed. We employed these methods to train a cortical spiking model to utilize macaque brain activity, indicating a selected target, to drive a virtual musculoskeletal arm with realistic anatomical and biomechanical properties to reach to that target. The optimized system was able to reproduce macaque data from a comparable experimental motor task. These techniques can be used to efficiently tune the parameters of multiscale systems, linking realistic neuronal dynamics to behavior, and thus providing a useful tool for neuroscience and neuroprosthetics. PMID:29200477

Low-mass neutralino dark matter in supergravity scenarios: phenomenology and naturalness

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

Peiró, M.; Robles, S., E-mail: mpeirogarcia@gmail.com, E-mail: sandra.robles@uam.es

2017-05-01

The latest experimental results from the LHC and dark matter (DM) searches suggest that the parameter space allowed in supersymmetric theories is subject to strong reductions. These bounds are especially constraining for scenarios entailing light DM particles. Previous studies have shown that light neutralino DM in the Minimal Supersymmetric Standard Model (MSSM), with parameters defined at the electroweak scale, is still viable when the low energy spectrum of the model features light sleptons, in which case, the relic density constraint can be fulfilled. In view of this, we have investigated the viability of light neutralinos as DM candidates in themore » MSSM, with parameters defined at the grand unification scale. We have analysed the optimal choices of non-universalities in the soft supersymmetry-breaking parameters for both, gauginos and scalars, in order to avoid the stringent experimental constraints. We show that light neutralinos, with a mass as low as 25 GeV, are viable in supergravity scenarios if the gaugino mass parameters at high energy are very non universal, while the scalar masses can remain of the same order. These scenarios typically predict a very small cross section of neutralinos off protons and neutrons, thereby being very challenging for direct detection experiments. However, a potential detection of smuons and selectrons at the LHC, together with a hypothetical discovery of a gamma-ray signal from neutralino annihilations in dwarf spheroidal galaxies could shed light on this kind of solutions. Finally, we have investigated the naturalness of these scenarios, taking into account all the potential sources of tuning. Besides the electroweak fine-tuning, we have found that the tuning to reproduce the correct DM relic abundance and that to match the measured Higgs mass can also be important when estimating the total degree of naturalness.« less

Low-mass neutralino dark matter in supergravity scenarios: phenomenology and naturalness

NASA Astrophysics Data System (ADS)

Peiró, M.; Robles, S.

2017-05-01

The latest experimental results from the LHC and dark matter (DM) searches suggest that the parameter space allowed in supersymmetric theories is subject to strong reductions. These bounds are especially constraining for scenarios entailing light DM particles. Previous studies have shown that light neutralino DM in the Minimal Supersymmetric Standard Model (MSSM), with parameters defined at the electroweak scale, is still viable when the low energy spectrum of the model features light sleptons, in which case, the relic density constraint can be fulfilled. In view of this, we have investigated the viability of light neutralinos as DM candidates in the MSSM, with parameters defined at the grand unification scale. We have analysed the optimal choices of non-universalities in the soft supersymmetry-breaking parameters for both, gauginos and scalars, in order to avoid the stringent experimental constraints. We show that light neutralinos, with a mass as low as 25 GeV, are viable in supergravity scenarios if the gaugino mass parameters at high energy are very non universal, while the scalar masses can remain of the same order. These scenarios typically predict a very small cross section of neutralinos off protons and neutrons, thereby being very challenging for direct detection experiments. However, a potential detection of smuons and selectrons at the LHC, together with a hypothetical discovery of a gamma-ray signal from neutralino annihilations in dwarf spheroidal galaxies could shed light on this kind of solutions. Finally, we have investigated the naturalness of these scenarios, taking into account all the potential sources of tuning. Besides the electroweak fine-tuning, we have found that the tuning to reproduce the correct DM relic abundance and that to match the measured Higgs mass can also be important when estimating the total degree of naturalness.

Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models

USGS Publications Warehouse

Plant, Nathaniel G.; Holland, K. Todd

2011-01-01

A Bayesian network model has been developed to simulate a relatively simple problem of wave propagation in the surf zone (detailed in Part I). Here, we demonstrate that this Bayesian model can provide both inverse modeling and data-assimilation solutions for predicting offshore wave heights and depth estimates given limited wave-height and depth information from an onshore location. The inverse method is extended to allow data assimilation using observational inputs that are not compatible with deterministic solutions of the problem. These inputs include sand bar positions (instead of bathymetry) and estimates of the intensity of wave breaking (instead of wave-height observations). Our results indicate that wave breaking information is essential to reduce prediction errors. In many practical situations, this information could be provided from a shore-based observer or from remote-sensing systems. We show that various combinations of the assimilated inputs significantly reduce the uncertainty in the estimates of water depths and wave heights in the model domain. Application of the Bayesian network model to new field data demonstrated significant predictive skill (R2 = 0.7) for the inverse estimate of a month-long time series of offshore wave heights. The Bayesian inverse results include uncertainty estimates that were shown to be most accurate when given uncertainty in the inputs (e.g., depth and tuning parameters). Furthermore, the inverse modeling was extended to directly estimate tuning parameters associated with the underlying wave-process model. The inverse estimates of the model parameters not only showed an offshore wave height dependence consistent with results of previous studies but the uncertainty estimates of the tuning parameters also explain previously reported variations in the model parameters.

A fast BK-type KCa current acts as a postsynaptic modulator of temporal selectivity for communication signals.

PubMed

Kohashi, Tsunehiko; Carlson, Bruce A

2014-01-01

Temporal patterns of spiking often convey behaviorally relevant information. Various synaptic mechanisms and intrinsic membrane properties can influence neuronal selectivity to temporal patterns of input. However, little is known about how synaptic mechanisms and intrinsic properties together determine the temporal selectivity of neuronal output. We tackled this question by recording from midbrain electrosensory neurons in mormyrid fish, in which the processing of temporal intervals between communication signals can be studied in a reduced in vitro preparation. Mormyrids communicate by varying interpulse intervals (IPIs) between electric pulses. Within the midbrain posterior exterolateral nucleus (ELp), the temporal patterns of afferent spike trains are filtered to establish single-neuron IPI tuning. We performed whole-cell recording from ELp neurons in a whole-brain preparation and examined the relationship between intrinsic excitability and IPI tuning. We found that spike frequency adaptation of ELp neurons was highly variable. Postsynaptic potentials (PSPs) of strongly adapting (phasic) neurons were more sharply tuned to IPIs than weakly adapting (tonic) neurons. Further, the synaptic filtering of IPIs by tonic neurons was more faithfully converted into variation in spiking output, particularly at short IPIs. Pharmacological manipulation under current- and voltage-clamp revealed that tonic firing is mediated by a fast, large-conductance Ca(2+)-activated K(+) (KCa) current (BK) that speeds up action potential repolarization. These results suggest that BK currents can shape the temporal filtering of sensory inputs by modifying both synaptic responses and PSP-to-spike conversion. Slow SK-type KCa currents have previously been implicated in temporal processing. Thus, both fast and slow KCa currents can fine-tune temporal selectivity.

[Relation between frequency modulation direction selectivity and forward masking of inferior collicular neurons: a study on in vivo intracellular recording in mice].

PubMed

Fu, Zi-Ying; Zeng, Hong; Tang, Jia; Li, Jie; Li, Juan; Chen, Qi-Cai

2013-06-25

It has been reported that the frequency modulation (FM) or FM direction sensitivity and forward masking of central auditory neurons are related with the neural inhibition, but there are some arguments, because no direct evidence of inhibitory synaptic input was obtained in previous studies using extracellular recording. In the present study, we studied the relation between FM direction sensitivity and forward masking of the inferior collicular (IC) neurons using in vivo intracellular recordings in 20 Mus musculus Km mice. Thirty seven with complete data among 93 neurons were analyzed and discussed. There was an inhibitory area which consisted of inhibitory postsynaptic potentials (IPSP) at high frequency side of frequency tuning of up-sweep FM (FMU) sensitive neurons (n = 12) and at low frequency side of frequency tuning of down-sweep FM (FMD) selective neurons (n = 8), while there was no any inhibitory area at both sides of frequency tuning of non-FM sweep direction (FMN) sensitive neurons (n = 17). Therefore, these results show that the inhibitory area at low or high frequency side of frequency tuning is one of the mechanisms for forming FM sweep direction sensitivity of IC neurons. By comparison of forward masking produced by FMU and FMD sound stimuli in FMU, FMD and FMN neurons, the selective FM sounds could produce stronger forward masking than the non-selective in FMU and FMD neurons, while there was no forward masking difference between FMU and FMD stimuli in the FMN neurons. We suggest that the post-action potential IPSP is a potential mechanism for producing stronger forward masking in FMU and FMD neurons.

Spectroscopic Investigation of TW Dra: Improved Stellar and System Parameters

NASA Astrophysics Data System (ADS)

Tkachenko, A.; Lehmann, H.; Mkrtichian, D.

2010-12-01

We investigate the Algol-type system TW Dra by means of the new computer program Shellspec07_inverse which is specially designed for the fine-tuning of stellar and system parameters of eclipsing binaries. We derive precise atmospheric and system parameters of TW Dra with an accuracy comparable to that expected from photometric data, and give a short comparison of our results with previous determinations.

OpenSQUID: A Flexible Open-Source Software Framework for the Control of SQUID Electronics

DOE PAGES

Jaeckel, Felix T.; Lafler, Randy J.; Boyd, S. T. P.

2013-02-06

We report commercially available computer-controlled SQUID electronics are usually delivered with software providing a basic user interface for adjustment of SQUID tuning parameters, such as bias current, flux offset, and feedback loop settings. However, in a research context it would often be useful to be able to modify this code and/or to have full control over all these parameters from researcher-written software. In the case of the STAR Cryoelectronics PCI/PFL family of SQUID control electronics, the supplied software contains modules for automatic tuning and noise characterization, but does not provide an interface for user code. On the other hand, themore » Magnicon SQUIDViewer software package includes a public application programming interface (API), but lacks auto-tuning and noise characterization features. To overcome these and other limitations, we are developing an "open-source" framework for controlling SQUID electronics which should provide maximal interoperability with user software, a unified user interface for electronics from different manufacturers, and a flexible platform for the rapid development of customized SQUID auto-tuning and other advanced features. Finally, we have completed a first implementation for the STAR Cryoelectronics hardware and have made the source code for this ongoing project available to the research community on SourceForge (http://opensquid.sourceforge.net) under the GNU public license.« less

Structural transitions in hybrid improper ferroelectric C a3T i2O7 tuned by site-selective isovalent substitutions: A first-principles study

NASA Astrophysics Data System (ADS)

Li, C. F.; Zheng, S. H.; Wang, H. W.; Gong, J. J.; Li, X.; Zhang, Y.; Yang, K. L.; Lin, L.; Yan, Z. B.; Dong, Shuai; Liu, J.-M.

2018-05-01

C a3T i2O7 is an experimentally confirmed hybrid improper ferroelectric material, in which the electric polarization is induced by a combination of the coherent Ti O6 octahedral rotation and tilting. In this work, we investigate the tuning of ferroelectricity of C a3T i2O7 using isovalent substitutions on Ca sites. Due to the size mismatch, larger/smaller alkaline earths prefer A'/A sites, respectively, allowing the possibility for site-selective substitutions. Without extra carriers, such site-selected isovalent substitutions can significantly tune the Ti O6 octahedral rotation and tilting, and thus change the structure and polarization. Using the first-principles calculations, our study reveals that three substituted cases (Sr, Mg, and Sr+Mg) show divergent physical behaviors. In particular, (CaTiO3) 2SrO becomes nonpolar, which can reasonably explain the suppression of polarization upon Sr substitution observed in experiment. In contrast, the polarization in (MgTiO3) 2CaO is almost doubled upon substitutions, while the estimated coercivity for ferroelectric switching does not change. The (MgTiO3) 2SrO remains polar but its structural space group changes, with moderate increased polarization and possible different ferroelectric switching paths. Our study reveals the subtle ferroelectricity in the A3T i2O7 family and suggests one more practical route to tune hybrid improper ferroelectricity, in addition to the strain effect.

Light-Directed Tuning of Plasmon Resonances via Plasmon-Induced Polymerization Using Hot Electrons

PubMed Central

2017-01-01

The precise morphology of nanoscale gaps between noble-metal nanostructures controls their resonant wavelengths. Here we show photocatalytic plasmon-induced polymerization can locally enlarge the gap size and tune the plasmon resonances. We demonstrate light-directed programmable tuning of plasmons can be self-limiting. Selective control of polymer growth around individual plasmonic nanoparticles is achieved, with simultaneous real-time monitoring of the polymerization process in situ using dark-field spectroscopy. Even without initiators present, we show light-triggered chain growth of various monomers, implying plasmon initiation of free radicals via hot-electron transfer to monomers at the Au surface. This concept not only provides a programmable way to fine-tune plasmons for many applications but also provides a window on polymer chemistry at the sub-nanoscale. PMID:28670601

Estimating human cochlear tuning behaviorally via forward masking

NASA Astrophysics Data System (ADS)

Oxenham, Andrew J.; Kreft, Heather A.

2018-05-01

The cochlea is where sound vibrations are transduced into the initial neural code for hearing. Despite the intervening stages of auditory processing, a surprising number of auditory perceptual phenomena can be explained in terms of the cochlea's biomechanical transformations. The quest to relate perception to these transformations has a long and distinguished history. Given its long history, it is perhaps surprising that something as fundamental as the link between frequency tuning in the cochlea and perception remains a controversial and active topic of investigation. Here we review some recent developments in our understanding of the relationship between cochlear frequency tuning and behavioral measures of frequency selectivity in humans. We show that forward masking using the notched-noise technique can produce reliable estimates of tuning that are in line with predictions from stimulus frequency otoacoustic emissions.

Development of a fusion approach selection tool

NASA Astrophysics Data System (ADS)

Pohl, C.; Zeng, Y.

2015-06-01

During the last decades number and quality of available remote sensing satellite sensors for Earth observation has grown significantly. The amount of available multi-sensor images along with their increased spatial and spectral resolution provides new challenges to Earth scientists. With a Fusion Approach Selection Tool (FAST) the remote sensing community would obtain access to an optimized and improved image processing technology. Remote sensing image fusion is a mean to produce images containing information that is not inherent in the single image alone. In the meantime the user has access to sophisticated commercialized image fusion techniques plus the option to tune the parameters of each individual technique to match the anticipated application. This leaves the operator with an uncountable number of options to combine remote sensing images, not talking about the selection of the appropriate images, resolution and bands. Image fusion can be a machine and time-consuming endeavour. In addition it requires knowledge about remote sensing, image fusion, digital image processing and the application. FAST shall provide the user with a quick overview of processing flows to choose from to reach the target. FAST will ask for available images, application parameters and desired information to process this input to come out with a workflow to quickly obtain the best results. It will optimize data and image fusion techniques. It provides an overview on the possible results from which the user can choose the best. FAST will enable even inexperienced users to use advanced processing methods to maximize the benefit of multi-sensor image exploitation.

LRS Bianchi type-I cosmological model with constant deceleration parameter in f(R,T) gravity

NASA Astrophysics Data System (ADS)

Bishi, Binaya K.; Pacif, S. K. J.; Sahoo, P. K.; Singh, G. P.

A spatially homogeneous anisotropic LRS Bianchi type-I cosmological model is studied in f(R,T) gravity with a special form of Hubble's parameter, which leads to constant deceleration parameter. The parameters involved in the considered form of Hubble parameter can be tuned to match, our models with the ΛCDM model. With the present observed value of the deceleration parameter, we have discussed physical and kinematical properties of a specific model. Moreover, we have discussed the cosmological distances for our model.

Online tuning of impedance matching circuit for long pulse inductively coupled plasma source operation—An alternate approach

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

Sudhir, Dass; Bandyopadhyay, M., E-mail: mainak@ter-india.org; Chakraborty, A.

2014-01-15

Impedance matching circuit between radio frequency (RF) generator and the plasma load, placed between them, determines the RF power transfer from RF generator to the plasma load. The impedance of plasma load depends on the plasma parameters through skin depth and plasma conductivity or resistivity. Therefore, for long pulse operation of inductively coupled plasmas, particularly for high power (∼100 kW or more) where plasma load condition may vary due to different reasons (e.g., pressure, power, and thermal), online tuning of impedance matching circuit is necessary through feedback. In fusion grade ion source operation, such online methodology through feedback is notmore » present but offline remote tuning by adjusting the matching circuit capacitors and tuning the driving frequency of the RF generator between the ion source operation pulses is envisaged. The present model is an approach for remote impedance tuning methodology for long pulse operation and corresponding online impedance matching algorithm based on RF coil antenna current measurement or coil antenna calorimetric measurement may be useful in this regard.« less

Adaptive control with self-tuning for non-invasive beat-by-beat blood pressure measurement.

PubMed

Nogawa, Masamichi; Ogawa, Mitsuhiro; Yamakoshi, Takehiro; Tanaka, Shinobu; Yamakoshi, Ken-ichi

2011-01-01

Up to now, we have successfully carried out the non-invasive beat-by-beat measurement of blood pressure (BP) in the root of finger, superficial temporal and radial artery based on the volume-compensation technique with reasonable accuracy. The present study concerns with improvement of control method for this beat-by-beat BP measurement. The measurement system mainly consists of a partial pressurization cuff with a pair of LED and photo-diode for the detection of arterial blood volume, and a digital self-tuning control method. Using healthy subjects, the performance and accuracy of this system were evaluated through comparison experiments with the system using a conventional empirically tuned PID controller. The significant differences of BP measured in finger artery were not showed in systolic (SBP), p=0.52, and diastolic BP (DBP), p=0.35. With the advantage of the adaptive control with self-tuning method, which can tune the control parameters without disturbing the control system, the application area of the non-invasive beat-by-beat measurement method will be broadened.

An adjustable RF tuning element for microwave, millimeter wave, and submillimeter wave integrated circuits

NASA Technical Reports Server (NTRS)

Lubecke, Victor M.; Mcgrath, William R.; Rutledge, David B.

1991-01-01

Planar RF circuits are used in a wide range of applications from 1 GHz to 300 GHz, including radar, communications, commercial RF test instruments, and remote sensing radiometers. These circuits, however, provide only fixed tuning elements. This lack of adjustability puts severe demands on circuit design procedures and materials parameters. We have developed a novel tuning element which can be incorporated into the design of a planar circuit in order to allow active, post-fabrication tuning by varying the electrical length of a coplanar strip transmission line. It consists of a series of thin plates which can slide in unison along the transmission line, and the size and spacing of the plates are designed to provide a large reflection of RF power over a useful frequency bandwidth. Tests of this structure at 1 GHz to 3 Ghz showed that it produced a reflection coefficient greater than 0.90 over a 20 percent bandwidth. A 2 GHz circuit incorporating this tuning element was also tested to demonstrate practical tuning ranges. This structure can be fabricated for frequencies as high as 1000 GHz using existing micromachining techniques. Many commercial applications can benefit from this micromechanical RF tuning element, as it will aid in extending microwave integrated circuit technology into the high millimeter wave and submillimeter wave bands by easing constraints on circuit technology.

Atomic layer deposition overcoating: tuning catalyst selectivity for biomass conversion.

PubMed

Zhang, Hongbo; Gu, Xiang-Kui; Canlas, Christian; Kropf, A Jeremy; Aich, Payoli; Greeley, Jeffrey P; Elam, Jeffrey W; Meyers, Randall J; Dumesic, James A; Stair, Peter C; Marshall, Christopher L

2014-11-03

The terraces, edges, and facets of nanoparticles are all active sites for heterogeneous catalysis. These different active sites may cause the formation of various products during the catalytic reaction. Here we report that the step sites of Pd nanoparticles (NPs) can be covered precisely by the atomic layer deposition (ALD) method, whereas the terrace sites remain as active component for the hydrogenation of furfural. Increasing the thickness of the ALD-generated overcoats restricts the adsorption of furfural onto the step sites of Pd NPs and increases the selectivity to furan. Furan selectivities and furfural conversions are linearly correlated for samples with or without an overcoating, though the slopes differ. The ALD technique can tune the selectivity of furfural hydrogenation over Pd NPs and has improved our understanding of the reaction mechanism. The above conclusions are further supported by density functional theory (DFT) calculations. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Selective tuning of the right inferior frontal gyrus during target detection

PubMed Central

Hampshire, Adam; Thompson, Russell; Duncan, John; Owen, Adrian M.

2010-01-01

In the human brain, a network of frontal and parietal regions is commonly recruited during tasks that demand the deliberate, focused control of thought and action. Previously, using a simple target detection task, we reported striking differences in the selectivity of the BOLD response in anatomically distinct subregions of this network. In particular, it was observed that the right inferior frontal gyrus (IFG) followed a tightly tuned function, selectively responding only to the current target object. Here, we examine this functional specialization further, using adapted versions of our original task. Our results demonstrate that the response of the right IFG to targets is a strong and replicable phenomenon. It occurs under increased attentional load, when targets and distractors are equally frequent, and when controlling for inhibitory processes. These findings support the hypothesis that the right IFG responds selectively to those items that are of the most relevance to the currently intended task schema. PMID:19246331

Orientation selectivity sharpens motion detection in Drosophila

PubMed Central

Fisher, Yvette E.; Silies, Marion; Clandinin, Thomas R.

2015-01-01

SUMMARY Detecting the orientation and movement of edges in a scene is critical to visually guided behaviors of many animals. What are the circuit algorithms that allow the brain to extract such behaviorally vital visual cues? Using in vivo two-photon calcium imaging in Drosophila, we describe direction selective signals in the dendrites of T4 and T5 neurons, detectors of local motion. We demonstrate that this circuit performs selective amplification of local light inputs, an observation that constrains motion detection models and confirms a core prediction of the Hassenstein-Reichardt Correlator (HRC). These neurons are also orientation selective, responding strongly to static features that are orthogonal to their preferred axis of motion, a tuning property not predicted by the HRC. This coincident extraction of orientation and direction sharpens directional tuning through surround inhibition and reveals a striking parallel between visual processing in flies and vertebrate cortex, suggesting a universal strategy for motion processing. PMID:26456048

UV-mediated tuning of surface biorepulsivity in aqueous environment.

PubMed

Weber, Theresa; Meyerbröker, Nikolaus; Hira, Nuruzzaman Khan; Zharnikov, Michael; Terfort, Andreas

2014-04-28

While it is well-known that oligoethylene glycol (OEG) terminated self-assembled monolayers (SAMs) can be deteriorated by UV irradiation in air, we now report that the analogous modification can also be performed in water, opening the opportunity for in situ tuning of biorepulsive properties. Surprisingly, this deterioration also takes place even in the absence of molecular oxygen, resulting in a very selective process.

Contralateral Bias of High Spatial Frequency Tuning and Cardinal Direction Selectivity in Mouse Visual Cortex

PubMed Central

Zeitoun, Jack H.; Kim, Hyungtae

2017-01-01

Binocular mechanisms for visual processing are thought to enhance spatial acuity by combining matched input from the two eyes. Studies in the primary visual cortex of carnivores and primates have confirmed that eye-specific neuronal response properties are largely matched. In recent years, the mouse has emerged as a prominent model for binocular visual processing, yet little is known about the spatial frequency tuning of binocular responses in mouse visual cortex. Using calcium imaging in awake mice of both sexes, we show that the spatial frequency preference of cortical responses to the contralateral eye is ∼35% higher than responses to the ipsilateral eye. Furthermore, we find that neurons in binocular visual cortex that respond only to the contralateral eye are tuned to higher spatial frequencies. Binocular neurons that are well matched in spatial frequency preference are also matched in orientation preference. In contrast, we observe that binocularly mismatched cells are more mismatched in orientation tuning. Furthermore, we find that contralateral responses are more direction-selective than ipsilateral responses and are strongly biased to the cardinal directions. The contralateral bias of high spatial frequency tuning was found in both awake and anesthetized recordings. The distinct properties of contralateral cortical responses may reflect the functional segregation of direction-selective, high spatial frequency-preferring neurons in earlier stages of the central visual pathway. Moreover, these results suggest that the development of binocularity and visual acuity may engage distinct circuits in the mouse visual system. SIGNIFICANCE STATEMENT Seeing through two eyes is thought to improve visual acuity by enhancing sensitivity to fine edges. Using calcium imaging of cellular responses in awake mice, we find surprising asymmetries in the spatial processing of eye-specific visual input in binocular primary visual cortex. The contralateral visual pathway is tuned to higher spatial frequencies than the ipsilateral pathway. At the highest spatial frequencies, the contralateral pathway strongly prefers to respond to visual stimuli along the cardinal (horizontal and vertical) axes. These results suggest that monocular, and not binocular, mechanisms set the limit of spatial acuity in mice. Furthermore, they suggest that the development of visual acuity and binocularity in mice involves different circuits. PMID:28924011

An analytical method of estimating turbine performance

NASA Technical Reports Server (NTRS)

Kochendorfer, Fred D; Nettles, J Cary

1949-01-01

A method is developed by which the performance of a turbine over a range of operating conditions can be analytically estimated from the blade angles and flow areas. In order to use the method, certain coefficients that determine the weight flow and the friction losses must be approximated. The method is used to calculate the performance of the single-stage turbine of a commercial aircraft gas-turbine engine and the calculated performance is compared with the performance indicated by experimental data. For the turbine of the typical example, the assumed pressure losses and the tuning angles give a calculated performance that represents the trends of the experimental performance with reasonable accuracy. The exact agreement between analytical performance and experimental performance is contingent upon the proper selection of a blading-loss parameter.

Plasmonic gold nanostars as optical nano-additives for injection molded polymer composites

NASA Astrophysics Data System (ADS)

Boyne, Devon A.; Orlicki, Joshua A.; Walck, Scott D.; Savage, Alice M.; Li, Thomas; Griep, Mark H.

2017-10-01

Nanoscale engineering of noble metal particles has provided numerous material configurations to selectively confine and manipulate light across the electromagnetic spectrum. Transitioning these materials to a composite form while maintaining the desired resonance properties has proven challenging. In this work, the successful integration of plasmon-focusing gold nanostars (GNSs) into polymer nanocomposites (PNCs) is demonstrated. Tailored GNSs are produced with over a 90% yield and methods to control the branching structures are shown. A protective silica capping shell is employed on the nanomaterials to facilitate survivability in the high temperate/high shear processing parameters to create optically-tuned injection molded PNCs. The developed GNS PNCs possess dichroic scattering and absorption behavior, opening up potential applications in the fields of holographic imaging, optical filtering and photovoltaics.

Tuning of Kalman filter parameters via genetic algorithm for state-of-charge estimation in battery management system.

PubMed

Ting, T O; Man, Ka Lok; Lim, Eng Gee; Leach, Mark

2014-01-01

In this work, a state-space battery model is derived mathematically to estimate the state-of-charge (SoC) of a battery system. Subsequently, Kalman filter (KF) is applied to predict the dynamical behavior of the battery model. Results show an accurate prediction as the accumulated error, in terms of root-mean-square (RMS), is a very small value. From this work, it is found that different sets of Q and R values (KF's parameters) can be applied for better performance and hence lower RMS error. This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. In an online application, a GA can be applied to obtain the optimal parameters of the KF before its application to a real plant (system). This simply means that the instantaneous response of the KF is not affected by the time consuming GA as this approach is applied only once to obtain the optimal parameters. The relevant workable MATLAB source codes are given in the appendix to ease future work and analysis in this area.

Tuning of Kalman Filter Parameters via Genetic Algorithm for State-of-Charge Estimation in Battery Management System

PubMed Central

Ting, T. O.; Lim, Eng Gee

2014-01-01

In this work, a state-space battery model is derived mathematically to estimate the state-of-charge (SoC) of a battery system. Subsequently, Kalman filter (KF) is applied to predict the dynamical behavior of the battery model. Results show an accurate prediction as the accumulated error, in terms of root-mean-square (RMS), is a very small value. From this work, it is found that different sets of Q and R values (KF's parameters) can be applied for better performance and hence lower RMS error. This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. In an online application, a GA can be applied to obtain the optimal parameters of the KF before its application to a real plant (system). This simply means that the instantaneous response of the KF is not affected by the time consuming GA as this approach is applied only once to obtain the optimal parameters. The relevant workable MATLAB source codes are given in the appendix to ease future work and analysis in this area. PMID:25162041

Transverse fields to tune an Ising-nematic quantum phase transition

NASA Astrophysics Data System (ADS)

Maharaj, Akash V.; Rosenberg, Elliott W.; Hristov, Alexander T.; Berg, Erez; Fernandes, Rafael M.; Fisher, Ian R.; Kivelson, Steven A.

2017-12-01

The paradigmatic example of a continuous quantum phase transition is the transverse field Ising ferromagnet. In contrast to classical critical systems, whose properties depend only on symmetry and the dimension of space, the nature of a quantum phase transition also depends on the dynamics. In the transverse field Ising model, the order parameter is not conserved, and increasing the transverse field enhances quantum fluctuations until they become strong enough to restore the symmetry of the ground state. Ising pseudospins can represent the order parameter of any system with a twofold degenerate broken-symmetry phase, including electronic nematic order associated with spontaneous point-group symmetry breaking. Here, we show for the representative example of orbital-nematic ordering of a non-Kramers doublet that an orthogonal strain or a perpendicular magnetic field plays the role of the transverse field, thereby providing a practical route for tuning appropriate materials to a quantum critical point. While the transverse fields are conjugate to seemingly unrelated order parameters, their nontrivial commutation relations with the nematic order parameter, which can be represented by a Berry-phase term in an effective field theory, intrinsically intertwine the different order parameters.

Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data

PubMed Central

Zhao, Xin; Cheung, Leo Wang-Kit

2007-01-01

Background Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more important for our understanding of diseases at genomic level. Although many machine learning methods have been developed and applied to the area of microarray gene expression data analysis, the majority of them are based on linear models, which however are not necessarily appropriate for the underlying connection between the target disease and its associated explanatory genes. Linear model based methods usually also bring in false positive significant features more easily. Furthermore, linear model based algorithms often involve calculating the inverse of a matrix that is possibly singular when the number of potentially important genes is relatively large. This leads to problems of numerical instability. To overcome these limitations, a few non-linear methods have recently been introduced to the area. Many of the existing non-linear methods have a couple of critical problems, the model selection problem and the model parameter tuning problem, that remain unsolved or even untouched. In general, a unified framework that allows model parameters of both linear and non-linear models to be easily tuned is always preferred in real-world applications. Kernel-induced learning methods form a class of approaches that show promising potentials to achieve this goal. Results A hierarchical statistical model named kernel-imbedded Gaussian process (KIGP) is developed under a unified Bayesian framework for binary disease classification problems using microarray gene expression data. In particular, based on a probit regression setting, an adaptive algorithm with a cascading structure is designed to find the appropriate kernel, to discover the potentially significant genes, and to make the optimal class prediction accordingly. A Gibbs sampler is built as the core of the algorithm to make Bayesian inferences. Simulation studies showed that, even without any knowledge of the underlying generative model, the KIGP performed very close to the theoretical Bayesian bound not only in the case with a linear Bayesian classifier but also in the case with a very non-linear Bayesian classifier. This sheds light on its broader usability to microarray data analysis problems, especially to those that linear methods work awkwardly. The KIGP was also applied to four published microarray datasets, and the results showed that the KIGP performed better than or at least as well as any of the referred state-of-the-art methods did in all of these cases. Conclusion Mathematically built on the kernel-induced feature space concept under a Bayesian framework, the KIGP method presented in this paper provides a unified machine learning approach to explore both the linear and the possibly non-linear underlying relationship between the target features of a given binary disease classification problem and the related explanatory gene expression data. More importantly, it incorporates the model parameter tuning into the framework. The model selection problem is addressed in the form of selecting a proper kernel type. The KIGP method also gives Bayesian probabilistic predictions for disease classification. These properties and features are beneficial to most real-world applications. The algorithm is naturally robust in numerical computation. The simulation studies and the published data studies demonstrated that the proposed KIGP performs satisfactorily and consistently. PMID:17328811

Long-term memory, neurogenesis, and signal novelty.

PubMed

Sokolov, E N; Nezlina, N I

2004-10-01

According to our suggested hypothesis, long-term memory is a collection of "gnostic units," selectively tuned to past events. The formation of long-term memory occurs with the involvement of constantly appearing new neurons which differentiate from stem cells during the process of neurogenesis, in particular in adults. Conversion of precursor neurons into "gnostic units" selective in relation to ongoing events, supplemented by the involvement of hippocampal "novelty neurons," which increase the flow of information needing to be fixed in long-term memory. "Gnostic units" form before the informational processes occurring in the ventral ("what?") and dorsal ("where?") systems. Formation of new "gnostic units" selectively tuned to a particular event results from the combination of excitation of the detector for stimulus characteristics and the novelty signal generated by "novelty neurons" in the hippocampus.

Selective Tuning of Elastin-like Polypeptide Properties via Methionine Oxidation.

PubMed

Petitdemange, Rosine; Garanger, Elisabeth; Bataille, Laure; Dieryck, Wilfrid; Bathany, Katell; Garbay, Bertrand; Deming, Timothy J; Lecommandoux, Sébastien

2017-02-13

We have designed and prepared a recombinant elastin-like polypeptide (ELP) containing precisely positioned methionine residues, and performed the selective and complete oxidation of its methionine thioether groups to both sulfoxide and sulfone derivatives. Since these oxidation reactions substantially increase methionine residue polarity, they were found to be a useful means to precisely adjust the temperature responsive behavior of ELPs in aqueous solutions. In particular, lower critical solution temperatures were found to be elevated in oxidized sample solutions, but were not eliminated. These transition temperatures were found to be further tunable by the use of solvents containing different Hofmeister salts. Overall, the ability to selectively and fully oxidize methionine residues in ELPs proved to be a convenient postmodification strategy for tuning their transition temperatures in aqueous media.

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

PubMed

Eichner, Hubert; Borst, Alexander

2011-01-01

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

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

PubMed Central

Eichner, Hubert; Borst, Alexander

2011-01-01

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

Determine Neuronal Tuning Curves by Exploring Optimum Firing Rate Distribution for Information Efficiency

PubMed Central

Han, Fang; Wang, Zhijie; Fan, Hong

2017-01-01

This paper proposed a new method to determine the neuronal tuning curves for maximum information efficiency by computing the optimum firing rate distribution. Firstly, we proposed a general definition for the information efficiency, which is relevant to mutual information and neuronal energy consumption. The energy consumption is composed of two parts: neuronal basic energy consumption and neuronal spike emission energy consumption. A parameter to model the relative importance of energy consumption is introduced in the definition of the information efficiency. Then, we designed a combination of exponential functions to describe the optimum firing rate distribution based on the analysis of the dependency of the mutual information and the energy consumption on the shape of the functions of the firing rate distributions. Furthermore, we developed a rapid algorithm to search the parameter values of the optimum firing rate distribution function. Finally, we found with the rapid algorithm that a combination of two different exponential functions with two free parameters can describe the optimum firing rate distribution accurately. We also found that if the energy consumption is relatively unimportant (important) compared to the mutual information or the neuronal basic energy consumption is relatively large (small), the curve of the optimum firing rate distribution will be relatively flat (steep), and the corresponding optimum tuning curve exhibits a form of sigmoid if the stimuli distribution is normal. PMID:28270760

Self-tuning pressure-feedback control by pole placement for vibration reduction of excavator with independent metering fluid power system

NASA Astrophysics Data System (ADS)

Ding, Ruqi; Xu, Bing; Zhang, Junhui; Cheng, Min

2017-08-01

Independent metering control systems are promising fluid power technologies compared with traditional valve controlled systems. By breaking the mechanical coupling between the inlet and outlet, the meter-out valve can open as large as possible to reduce energy consumptions. However, the lack of damping in outlet causes stronger vibrations. To address the problem, the paper designs a hybrid control method combining dynamic pressure-feedback and active damping control. The innovation resides in the optimization of damping by introducing pressure feedback to make trade-offs between high stability and fast response. To achieve this goal, the dynamic response pertaining to the control parameters consisting of feedback gain and cut-off frequency, are analyzed via pole-zero locations. Accordingly, these parameters are tuned online in terms of guaranteed dominant pole placement such that the optimal damping can be accurately captured under a considerable variation of operating conditions. The experiment is deployed in a mini-excavator. The results pertaining to different control parameters confirm the theoretical expectations via pole-zero locations. By using proposed self-tuning controller, the vibrations are almost eliminated after only one overshoot for different operation conditions. The overshoots are also reduced with less decrease of the response time. In addition, the energy-saving capability of independent metering system is still not affected by the improvement of controllability.

Tuning a physically-based model of the air-sea gas transfer velocity

NASA Astrophysics Data System (ADS)

Jeffery, C. D.; Robinson, I. S.; Woolf, D. K.

Air-sea gas transfer velocities are estimated for one year using a 1-D upper-ocean model (GOTM) and a modified version of the NOAA-COARE transfer velocity parameterization. Tuning parameters are evaluated with the aim of bringing the physically based NOAA-COARE parameterization in line with current estimates, based on simple wind-speed dependent models derived from bomb-radiocarbon inventories and deliberate tracer release experiments. We suggest that A = 1.3 and B = 1.0, for the sub-layer scaling parameter and the bubble mediated exchange, respectively, are consistent with the global average CO 2 transfer velocity k. Using these parameters and a simple 2nd order polynomial approximation, with respect to wind speed, we estimate a global annual average k for CO 2 of 16.4 ± 5.6 cm h -1 when using global mean winds of 6.89 m s -1 from the NCEP/NCAR Reanalysis 1 1954-2000. The tuned model can be used to predict the transfer velocity of any gas, with appropriate treatment of the dependence on molecular properties including the strong solubility dependence of bubble-mediated transfer. For example, an initial estimate of the global average transfer velocity of DMS (a relatively soluble gas) is only 11.9 cm h -1 whilst for less soluble methane the estimate is 18.0 cm h -1.

Interface-based two-way tuning of the in-plane thermal transport in nanofilms

NASA Astrophysics Data System (ADS)

Hua, Yu-Chao; Cao, Bing-Yang

2018-03-01

Here, the two-way tuning of in-plane thermal transport is obtained in the bi-layer nanofilms with an interfacial effect by using the Boltzmann transport equation (BTE) and the phonon Monte Carlo (MC) technique. A thermal conductivity model was derived from the BTE and verified by the MC simulations. Both the model and the MC simulations indicate that the tuning of the thermal transport can be bidirectional (reduced or enhanced), depending on the interface conditions (i.e., roughness and adhesion energy) and the phonon property dissimilarity at the interface. For the identical-material interface, the emergence of thermal conductivity variation requires two conditions: (a) the interface is not completely specular and (b) the transmission specularity parameter differs from the reflection specularity parameter at the interface. When the transmission specularity parameter is larger than the reflection specularity parameter at the interface, the thermal conductivity improvement effect emerges, whereas the thermal conductivity reduction effect occurs. For the disparate-material interface, the phonon property perturbation near the interface causes the thermal conductivity variation, even when neither the above two conditions are satisfied. The mean free path ratio (γ) between the disparate materials was defined to characterize the phonon property dissimilarity. γ > 1 can lead to the thermal conductivity improvement effect, while γ < 1 corresponds to the thermal conductivity reduction effect. Our work provides a more in-depth understanding of the interfacial effect on the nanoscale thermal transport, with an applicable predictive model, which can be helpful for predicting and manipulating phonon transport in nanofilms.

Convolutional Dictionary Learning: Acceleration and Convergence

NASA Astrophysics Data System (ADS)

Chun, Il Yong; Fessler, Jeffrey A.

2018-04-01

Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in developing efficient algorithms for CDL, mostly relying on the augmented Lagrangian (AL) method or the variant alternating direction method of multipliers (ADMM). When their parameters are properly tuned, AL methods have shown fast convergence in CDL. However, the parameter tuning process is not trivial due to its data dependence and, in practice, the convergence of AL methods depends on the AL parameters for nonconvex CDL problems. To moderate these problems, this paper proposes a new practically feasible and convergent Block Proximal Gradient method using a Majorizer (BPG-M) for CDL. The BPG-M-based CDL is investigated with different block updating schemes and majorization matrix designs, and further accelerated by incorporating some momentum coefficient formulas and restarting techniques. All of the methods investigated incorporate a boundary artifacts removal (or, more generally, sampling) operator in the learning model. Numerical experiments show that, without needing any parameter tuning process, the proposed BPG-M approach converges more stably to desirable solutions of lower objective values than the existing state-of-the-art ADMM algorithm and its memory-efficient variant do. Compared to the ADMM approaches, the BPG-M method using a multi-block updating scheme is particularly useful in single-threaded CDL algorithm handling large datasets, due to its lower memory requirement and no polynomial computational complexity. Image denoising experiments show that, for relatively strong additive white Gaussian noise, the filters learned by BPG-M-based CDL outperform those trained by the ADMM approach.

V1 orientation plasticity is explained by broadly tuned feedforward inputs and intracortical sharpening.

PubMed

Teich, Andrew F; Qian, Ning

2010-03-01

Orientation adaptation and perceptual learning change orientation tuning curves of V1 cells. Adaptation shifts tuning curve peaks away from the adapted orientation, reduces tuning curve slopes near the adapted orientation, and increases the responses on the far flank of tuning curves. Learning an orientation discrimination task increases tuning curve slopes near the trained orientation. These changes have been explained previously in a recurrent model (RM) of orientation selectivity. However, the RM generates only complex cells when they are well tuned, so that there is currently no model of orientation plasticity for simple cells. In addition, some feedforward models, such as the modified feedforward model (MFM), also contain recurrent cortical excitation, and it is unknown whether they can explain plasticity. Here, we compare plasticity in the MFM, which simulates simple cells, and a recent modification of the RM (MRM), which displays a continuum of simple-to-complex characteristics. Both pre- and postsynaptic-based modifications of the recurrent and feedforward connections in the models are investigated. The MRM can account for all the learning- and adaptation-induced plasticity, for both simple and complex cells, while the MFM cannot. The key features from the MRM required for explaining plasticity are broadly tuned feedforward inputs and sharpening by a Mexican hat intracortical interaction profile. The mere presence of recurrent cortical interactions in feedforward models like the MFM is insufficient; such models have more rigid tuning curves. We predict that the plastic properties must be absent for cells whose orientation tuning arises from a feedforward mechanism.

Tuning the dielectric properties of polystyrene/poly(vinylidene fluoride) blends by selectively localizing carbon black nanoparticles.

PubMed

Zhao, Xiaodong; Zhao, Jun; Cao, Jian-Ping; Wang, Xiaoyan; Chen, Min; Dang, Zhi-Min

2013-02-28

In this work, the dielectric properties of immiscible polystyrene (PS)/poly(vinylidene fluoride) (PVDF) blends are tuned by selectively localizing carbon black (CB) nanoparticles in different phases. The PS/PVDF blends have a wide window of cocontinuity (ca. 30-80 vol % in terms of the volume fraction of PS component (v(PS))). The selective localization of CB nanoparticles is achieved by using the masterbatch process during melt mixing. For the volume ratio PS/PVDF 1/1 and the volume fraction of CB nanoparticles (v(CB)) below but close to the percolation threshold (v(c)(CB)), the selective localization of CB nanoparticles in PVDF phase produces higher dielectric constant (ε) than that in PS phase, whereas the ε of the ternary mixtures without selective localization of fillers is in the middle. For the volume ratios PS/PVDF 1/2 and 2/1, the selective location of CB nanoparticles in different phases can be used to easily tune the system from conductive to insulating or inverse, which might have potential applications in industry. The fillers are found to be "fixed" in the masterbatch of PS or PVDF component and there is no migration of the fillers to another phase occurring during the further mixing process for the mixing time up to 30 min. Furthermore, the addition of CB nanoparticles to the polymer matrix is found to induce the brittle-ductile transition in the system and increase the compatibility between the immiscible PS and PVDF components, which should benefit the mechanical properties.

Optimal Trajectories Generation in Robotic Fiber Placement Systems

NASA Astrophysics Data System (ADS)

Gao, Jiuchun; Pashkevich, Anatol; Caro, Stéphane

2017-06-01

The paper proposes a methodology for optimal trajectories generation in robotic fiber placement systems. A strategy to tune the parameters of the optimization algorithm at hand is also introduced. The presented technique transforms the original continuous problem into a discrete one where the time-optimal motions are generated by using dynamic programming. The developed strategy for the optimization algorithm tuning allows essentially reducing the computing time and obtaining trajectories satisfying industrial constraints. Feasibilities and advantages of the proposed methodology are confirmed by an application example.

Control of Crazyflie nano quadcopter using Simulink

NASA Astrophysics Data System (ADS)

Gopabhat Madhusudhan, Meghana

This thesis focuses on developing a mathematical model in Simulink to Crazyflie, an open source platform. Attitude, altitude and position controllers of a Crazyflie are designed in the mathematical model. The mathematical model is developed based on the quadcopter system dynamics using a non-linear approach. The parameters of translational and rotational dynamics of the quadcopter system are linearized and tuned individually. The tuned attitude and altitude controllers from the mathematical model are implemented on real time Crazyflie Simulink model to achieve autonomous and controlled flight.

ATLAS I/O performance optimization in as-deployed environments

NASA Astrophysics Data System (ADS)

Maier, T.; Benjamin, D.; Bhimji, W.; Elmsheuser, J.; van Gemmeren, P.; Malon, D.; Krumnack, N.

2015-12-01

This paper provides an overview of an integrated program of work underway within the ATLAS experiment to optimise I/O performance for large-scale physics data analysis in a range of deployment environments. It proceeds to examine in greater detail one component of that work, the tuning of job-level I/O parameters in response to changes to the ATLAS event data model, and considers the implications of such tuning for a number of measures of I/O performance.

Trade-off between curvature tuning and position invariance in visual area V4

PubMed Central

Sharpee, Tatyana O.; Kouh, Minjoon; Reynolds, John H.

2013-01-01

Humans can rapidly recognize a multitude of objects despite differences in their appearance. The neural mechanisms that endow high-level sensory neurons with both selectivity to complex stimulus features and “tolerance” or invariance to identity-preserving transformations, such as spatial translation, remain poorly understood. Previous studies have demonstrated that both tolerance and selectivity to conjunctions of features are increased at successive stages of the ventral visual stream that mediates visual recognition. Within a given area, such as visual area V4 or the inferotemporal cortex, tolerance has been found to be inversely related to the sparseness of neural responses, which in turn was positively correlated with conjunction selectivity. However, the direct relationship between tolerance and conjunction selectivity has been difficult to establish, with different studies reporting either an inverse or no significant relationship. To resolve this, we measured V4 responses to natural scenes, and using recently developed statistical techniques, we estimated both the relevant stimulus features and the range of translation invariance for each neuron. Focusing the analysis on tuning to curvature, a tractable example of conjunction selectivity, we found that neurons that were tuned to more curved contours had smaller ranges of position invariance and produced sparser responses to natural stimuli. These trade-offs provide empirical support for recent theories of how the visual system estimates 3D shapes from shading and texture flows, as well as the tiling hypothesis of the visual space for different curvature values. PMID:23798444

Orientation-Selective Retinal Circuits in Vertebrates.

PubMed

Antinucci, Paride; Hindges, Robert

2018-01-01

Visual information is already processed in the retina before it is transmitted to higher visual centers in the brain. This includes the extraction of salient features from visual scenes, such as motion directionality or contrast, through neurons belonging to distinct neural circuits. Some retinal neurons are tuned to the orientation of elongated visual stimuli. Such 'orientation-selective' neurons are present in the retinae of most, if not all, vertebrate species analyzed to date, with species-specific differences in frequency and degree of tuning. In some cases, orientation-selective neurons have very stereotyped functional and morphological properties suggesting that they represent distinct cell types. In this review, we describe the retinal cell types underlying orientation selectivity found in various vertebrate species, and highlight their commonalities and differences. In addition, we discuss recent studies that revealed the cellular, synaptic and circuit mechanisms at the basis of retinal orientation selectivity. Finally, we outline the significance of these findings in shaping our current understanding of how this fundamental neural computation is implemented in the visual systems of vertebrates.

An ℋ∞ full information approach for the feedforward controller design of a large blended wing body flexible aircraft

NASA Astrophysics Data System (ADS)

Westermayer, C.; Schirrer, A.; Hemedi, M.; Kozek, M.

2013-12-01

An ℋ∞ full information feedforward design approach for longitudinal motion prefilter design of a large flexible blended wing body (BWB) aircraft is presented. An existing onset is extended such that specifications concerning command tracking, limited control energy, and manoeuvre load reduction can be addressed simultaneously. Therefore, the utilized design architecture is provided and manual tuning aspects are considered. In order to increase controller tuning efficiency, an automated tuning process based on several optimization criteria is proposed. Moreover, two design methodologies for the parameter-varying design case are investigated. The obtained controller is validated on a high-order nonlinear model, indicating the high potential of the presented approach for flexible aircraft control.

On the Possibility of Using Nonlinear Elements for Landau Damping in High-Intensity Beams

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

Alexahin, Y.; Gianfelice-Wendt, E.; Lebedev, V.

2016-09-30

Direct space-charge force shifts incoherent tunes downwards from the coherent ones breaking the Landau mechanism of coherent oscillations damping at high beam intensity. To restore it nonlinear elements can be employed which move back tunes of large amplitude particles. In the present report we consider the possibility of creating a “nonlinear integrable optics” insertion in the Fermilab Recycler to host either octupoles or hollow electron lens for this purpose. For comparison we also consider the classic scheme with distributed octupole families. It is shown that for the Proton Improvement Plan II (PIP II) parameters the required nonlinear tune shift canmore » be created without destroying the dynamic aperture.« less

Wavelength adjustability of frequency conversion light of Yb-doped fiber laser based on FBGs

NASA Astrophysics Data System (ADS)

Dobashi, Kazuma; Tomihari, Yasuhiro; Imai, Koichi; Hirohashi, Junji; Makio, Satoshi

2018-02-01

We focused on wavelength conversion of simple and compact CW Yb-Doped fiber laser based on FBGs with wavelength adjustable function. By controlling temperatures of FBGs in fiber laser, it was possible to tune oscillated wavelength from 1064.101 nm to 1064.414 nm with more than 20 W in CW operation mode. Based on this fundamental light, frequency converted light (SHG and THG) were generated by utilizing two PP:Mg-SLT devises. We obtained more than 3 W of SHG light with tuning range of 150 pm and more than 35 mW of THG with tuning range of 100 pm. By selecting FBG grating and QPM grating properly, we can realize adjustable wavelength laser with the same scheme from 1040 nm to 1090 nm and their SHG/THG. With this combination of FBG based fiber laser and QPM devices, it is possible to tune the wavelength just by temperature tuning without any changes of beam shape and beam pointing.

Rapid optimization of MRM-MS instrument parameters by subtle alteration of precursor and product m/z targets.

PubMed

Sherwood, Carly A; Eastham, Ashley; Lee, Lik Wee; Risler, Jenni; Mirzaei, Hamid; Falkner, Jayson A; Martin, Daniel B

2009-07-01

Multiple reaction monitoring (MRM) is a highly sensitive method of targeted mass spectrometry (MS) that can be used to selectively detect and quantify peptides based on the screening of specified precursor peptide-to-fragment ion transitions. MRM-MS sensitivity depends critically on the tuning of instrument parameters, such as collision energy and cone voltage, for the generation of maximal product ion signal. Although generalized equations and values exist for such instrument parameters, there is no clear indication that optimal signal can be reliably produced for all types of MRM transitions using such an algorithmic approach. To address this issue, we have devised a workflow functional on both Waters Quattro Premier and ABI 4000 QTRAP triple quadrupole instruments that allows rapid determination of the optimal value of any programmable instrument parameter for each MRM transition. Here, we demonstrate the strategy for the optimizations of collision energy and cone voltage, but the method could be applied to other instrument parameters, such as declustering potential, as well. The workflow makes use of the incremental adjustment of the precursor and product m/z values at the hundredth decimal place to create a series of MRM targets at different collision energies that can be cycled through in rapid succession within a single run, avoiding any run-to-run variability in execution or comparison. Results are easily visualized and quantified using the MRM software package Mr. M to determine the optimal instrument parameters for each transition.

Rapid Optimization of MRM-MS Instrument Parameters by Subtle Alteration of Precursor and Product m/z Targets

PubMed Central

Sherwood, Carly A.; Eastham, Ashley; Lee, Lik Wee; Risler, Jenni; Mirzaei, Hamid; Falkner, Jayson A.; Martin, Daniel B.

2009-01-01

Multiple reaction monitoring (MRM) is a highly sensitive method of targeted mass spectrometry (MS) that can be used to selectively detect and quantify peptides based on the screening of specified precursor peptide-to-fragment ion transitions. MRM-MS sensitivity depends critically on the tuning of instrument parameters, such as collision energy and cone voltage, for the generation of maximal product ion signal. Although generalized equations and values exist for such instrument parameters, there is no clear indication that optimal signal can be reliably produced for all types of MRM transitions using such an algorithmic approach. To address this issue, we have devised a workflow functional on both Waters Quattro Premier and ABI 4000 QTRAP triple quadrupole instruments that allows rapid determination of the optimal value of any programmable instrument parameter for each MRM transition. Here, we demonstrate the strategy for the optimizations of collision energy and cone voltage, but the method could be applied to other instrument parameters, such as declustering potential, as well. The workflow makes use of the incremental adjustment of the precursor and product m/z values at the hundredth decimal place to create a series of MRM targets at different collision energies that can be cycled through in rapid succession within a single run, avoiding any run-to-run variability in execution or comparison. Results are easily visualized and quantified using the MRM software package Mr. M to determine the optimal instrument parameters for each transition. PMID:19405522

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

NASA Astrophysics Data System (ADS)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters.

Spectral embedding finds meaningful (relevant) structure in image and microarray data

PubMed Central

Higgs, Brandon W; Weller, Jennifer; Solka, Jeffrey L

2006-01-01

Background Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing measurements across thousands of variables. Principal components analysis (PCA) is a linear dimensionality reduction (DR) method that is unsupervised in that it relies only on the data; projections are calculated in Euclidean or a similar linear space and do not use tuning parameters for optimizing the fit to the data. However, relationships within sets of nonlinear data types, such as biological networks or images, are frequently mis-rendered into a low dimensional space by linear methods. Nonlinear methods, in contrast, attempt to model important aspects of the underlying data structure, often requiring parameter(s) fitting to the data type of interest. In many cases, the optimal parameter values vary when different classification algorithms are applied on the same rendered subspace, making the results of such methods highly dependent upon the type of classifier implemented. Results We present the results of applying the spectral method of Lafon, a nonlinear DR method based on the weighted graph Laplacian, that minimizes the requirements for such parameter optimization for two biological data types. We demonstrate that it is successful in determining implicit ordering of brain slice image data and in classifying separate species in microarray data, as compared to two conventional linear methods and three nonlinear methods (one of which is an alternative spectral method). This spectral implementation is shown to provide more meaningful information, by preserving important relationships, than the methods of DR presented for comparison. Tuning parameter fitting is simple and is a general, rather than data type or experiment specific approach, for the two datasets analyzed here. Tuning parameter optimization is minimized in the DR step to each subsequent classification method, enabling the possibility of valid cross-experiment comparisons. Conclusion Results from the spectral method presented here exhibit the desirable properties of preserving meaningful nonlinear relationships in lower dimensional space and requiring minimal parameter fitting, providing a useful algorithm for purposes of visualization and classification across diverse datasets, a common challenge in systems biology. PMID:16483359

Internally resonating lattices for bandgap generation and low-frequency vibration control

NASA Astrophysics Data System (ADS)

Baravelli, Emanuele; Ruzzene, Massimo

2013-12-01

The paper reports on a structural concept for high stiffness and high damping performance. A stiff external frame and an internal resonating lattice are combined in a beam-like assembly which is characterized by high frequency bandgaps and tuned vibration attenuation at low frequencies. The resonating lattice consists of an elastomeric material arranged according to a chiral topology which is designed to resonate at selected frequencies. The concept achieves high damping performance by combining the frequency-selective properties of internally resonating structures, with the energy dissipation characteristics of their constituent material. The flexible ligaments, the circular nodes and the non-central interactions of the chiral topology lead to dynamic deformation patterns which are beneficial to energy dissipation. Furthermore, tuning and grading of the elements of the lattice allows for tailoring of the resonating properties so that vibration attenuation is obtained over desired frequency ranges. Numerical and experimental results demonstrate the tuning flexibility of this concept and suggest its potential application for load-carrying structural members parts of vibration and shock prone systems.

In Situ Generation of Plasmonic Nanoparticles for Manipulating Photon-Plasmon Coupling in Microtube Cavities.

PubMed

Yin, Yin; Wang, Jiawei; Lu, Xueyi; Hao, Qi; Saei Ghareh Naz, Ehsan; Cheng, Chuanfu; Ma, Libo; Schmidt, Oliver G

2018-04-24

In situ generation of silver nanoparticles for selective coupling between localized plasmonic resonances and whispering-gallery modes (WGMs) is investigated by spatially resolved laser dewetting on microtube cavities. The size and morphology of the silver nanoparticles are changed by adjusting the laser power and irradiation time, which in turn effectively tune the photon-plasmon coupling strength. Depending on the relative position of the plasmonic nanoparticles spot and resonant field distribution of WGMs, selective coupling between the localized surface plasmon resonances (LSPRs) and WGMs is experimentally demonstrated. Moreover, by creating multiple plasmonic-nanoparticle spots on the microtube cavity, the field distribution of optical axial modes is freely tuned due to multicoupling between LSPRs and WGMs. The multicoupling mechanism is theoretically investigated by a modified quasipotential model based on perturbation theory. This work provides an in situ fabrication of plasmonic nanoparticles on three-dimensional microtube cavities for manipulating photon-plasmon coupling which is of interest for optical tuning abilities and enhanced light-matter interactions.

Non-Uniform Bias Enhancement of a Varactor-Tuned FSS used with a Low Profile 2.4 GHz Dipole Antenna

NASA Technical Reports Server (NTRS)

Cure, David; Weller, Thomas M.; Miranda, Felix A.

2012-01-01

In this paper a low profile antenna using a nonuniformly biased varactor-tuned frequency selective surface (FSS) is presented. The tunable FSS avoids the use of vias and has a simplified DC bias network. The voltages to the DC bias ports can be varied independently allowing adjustment in the frequency response and enhanced radiation properties. The measured data demonstrate tunability from 2.15 GHz to 2.63 GHz with peak efficiencies that range from 50% to 90% and instantaneous bandwidths of 50 MHz to 280 MHz within the tuning range. The total antenna thickness is approximately lambda/45.

Real-Time Ozone Detection Based on a Microfabricated Quartz Crystal Tuning Fork Sensor

PubMed Central

Wang, Rui; Tsow, Francis; Zhang, Xuezhi; Peng, Jhih-Hong; Forzani, Erica S.; Chen, Yongsheng; Crittenden, John C.; Destaillats, Hugo; Tao, Nongjian

2009-01-01

A chemical sensor for ozone based on an array of microfabricated tuning forks is described. The tuning forks are highly sensitive and stable, with low power consumption and cost. The selective detection is based on the specific reaction of the polymer with ozone. With a mass detection limit of ∼2 pg/mm2 and response time of 1 second, the sensor coated with a polymer sensing material can detect ppb-level ozone in air. The sensor is integrated into a miniaturized wearable device containing a detection circuit, filtration, battery and wireless communication chip, which is ideal for personal and microenvironmental chemical exposure monitoring. PMID:22346720

Highly tunable birefringent microstructured optical fiber.

PubMed

Kerbage, C; Steinvurzel, P; Reyes, P; Westbrook, P S; Windeler, R S; Hale, A; Eggleton, B J

2002-05-15

We demonstrate a method for introducing and dynamically tuning birefringence in a microstructured optical fiber. Waveguide asymmetry in the fiber is obtained by selective filling of air holes with polymer, and tunability is achieved by temperature tuning of the polymer's index. The fiber is tapered such that the mode field expands into the cladding and efficiently overlaps the polymer that has been infused into the air holes, ensuring enhanced tunability and low splice loss. Experimental results are compared with numerical simulations made with the beam propagation method and confirm birefringence tuning that corresponds to a phase change of 6pi for a 1-cm length of fiber.

Intelligent Machine Learning Approaches for Aerospace Applications

NASA Astrophysics Data System (ADS)

Sathyan, Anoop

Machine Learning is a type of artificial intelligence that provides machines or networks the ability to learn from data without the need to explicitly program them. There are different kinds of machine learning techniques. This thesis discusses the applications of two of these approaches: Genetic Fuzzy Logic and Convolutional Neural Networks (CNN). Fuzzy Logic System (FLS) is a powerful tool that can be used for a wide variety of applications. FLS is a universal approximator that reduces the need for complex mathematics and replaces it with expert knowledge of the system to produce an input-output mapping using If-Then rules. The expert knowledge of a system can help in obtaining the parameters for small-scale FLSs, but for larger networks we will need to use sophisticated approaches that can automatically train the network to meet the design requirements. This is where Genetic Algorithms (GA) and EVE come into the picture. Both GA and EVE can tune the FLS parameters to minimize a cost function that is designed to meet the requirements of the specific problem. EVE is an artificial intelligence developed by Psibernetix that is trained to tune large scale FLSs. The parameters of an FLS can include the membership functions and rulebase of the inherent Fuzzy Inference Systems (FISs). The main issue with using the GFS is that the number of parameters in a FIS increase exponentially with the number of inputs thus making it increasingly harder to tune them. To reduce this issue, the FLSs discussed in this thesis consist of 2-input-1-output FISs in cascade (Chapter 4) or as a layer of parallel FISs (Chapter 7). We have obtained extremely good results using GFS for different applications at a reduced computational cost compared to other algorithms that are commonly used to solve the corresponding problems. In this thesis, GFSs have been designed for controlling an inverted double pendulum, a task allocation problem of clustering targets amongst a set of UAVs, a fire detection problem and the aircraft conflict resolution problem. During the last decade, CNNs have become increasingly popular in the domain of image and speech processing. CNNs have a lot more parameters compared to GFSs that are tuned using the back-propagation algorithm. CNNs typically have hundreds of thousands or maybe millions of parameters that are tuned using common cost functions such as integral squared error, softmax loss etc. Chapter 5 discusses a classification problem to classify images as humans or not and Chapter 6 discusses a regression task using CNN for producing an approximate near-optimal route for the Traveling Salesman Problem (TSP) which is regarded as one of the most complicated decision making problem. Both the GFS and CNN are used to develop intelligent systems specific to the application providing them computational efficiency, robustness in the face of uncertainties and scalability.

Tuning the Solid Electrolyte Interphase for Selective Li- and Na-Ion Storage in Hard Carbon

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

Soto, Fernando A.; Yan, Pengfei; Engelhard, Mark H.

Solid-electrolyte interphase (SEI) with controllable properties are highly desirable to improve battery performance. In this paper, we use a combined experimental and simulation approach to study the SEI formation on hard carbon in Li and Na-ion batteries. We show that with proper additives, stable SEI can be formed on hard carbon by pre-cycling the electrode materials in Li or Na-ion electrolyte. Detailed mechanistic studies suggest that the ion transport in the SEI layer is kinetically controlled and can be tuned by the applied voltage. Selective Na and Li-ion SEI membranes are produced using the Na or Li-ion based electrolytes respectively.more » The large Na ion SEI allows easy transport of Li ions, while the small Li ion SEI shuts off the Na-ion transport. Na-ion storage can be manipulated by tuning the SEI with film-forming electrolyte additives or preforming a SEI on the electrodes’ surface. The Na specific capacity can be controlled to <25 mAh/g, ~1/10 of the normal capacity (250 mAh/g). Unusual selective/preferential transport of Li-ion is demonstrated by preforming a SEI on the electrode’s surface and corroborated with a mixed electrolyte. This work may provide new guidance for preparing good ion selective conductors using electrochemical approaches in the future.« less

Model predictive control of attitude maneuver of a geostationary flexible satellite based on genetic algorithm

NASA Astrophysics Data System (ADS)

TayyebTaher, M.; Esmaeilzadeh, S. Majid

2017-07-01

This article presents an application of Model Predictive Controller (MPC) to the attitude control of a geostationary flexible satellite. SIMO model has been used for the geostationary satellite, using the Lagrange equations. Flexibility is also included in the modelling equations. The state space equations are expressed in order to simplify the controller. Naturally there is no specific tuning rule to find the best parameters of an MPC controller which fits the desired controller. Being an intelligence method for optimizing problem, Genetic Algorithm has been used for optimizing the performance of MPC controller by tuning the controller parameter due to minimum rise time, settling time, overshoot of the target point of the flexible structure and its mode shape amplitudes to make large attitude maneuvers possible. The model included geosynchronous orbit environment and geostationary satellite parameters. The simulation results of the flexible satellite with attitude maneuver shows the efficiency of proposed optimization method in comparison with LQR optimal controller.

Tunable non-interacting free-energy functionals: development and applications to low-density aluminum

NASA Astrophysics Data System (ADS)

Trickey, Samuel; Karasiev, Valentin

We introduce the concept of tunable orbital-free non-interacting free-energy density functionals and present a generalized gradient approximation (GGA) with a subset of parameters defined from constraints and a few free parameters. Those free parameters are tuned to reproduce reference Kohn-Sham (KS) static-lattice pressures for Al at T=8 kK for bulk densities between 0.6 and 2 g/cm3. The tuned functional then is used in OF molecular dynamics (MD) simulations for Al with densities between 0.1 and 2 g/cm3 and T between 6 and 50 kK to calculate the equation of state and generate configurations for electrical conductivity calculations. The tunable functional produces accurate results. Computationally it is very effective especially at elevated temperature. Kohn-Shiam calculations for such low densities are affordable only up to T=10 kK, while other OF approximations, including two-point functionals, fail badly in that regime. Work supported by US DoE Grant DE-SC0002139.

Exploring performance and energy tradeoffs for irregular applications: A case study on the Tilera many-core architecture

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

Panyala, Ajay; Chavarría-Miranda, Daniel; Manzano, Joseph B.

High performance, parallel applications with irregular data accesses are becoming a critical workload class for modern systems. In particular, the execution of such workloads on emerging many-core systems is expected to be a significant component of applications in data mining, machine learning, scientific computing and graph analytics. However, power and energy constraints limit the capabilities of individual cores, memory hierarchy and on-chip interconnect of such systems, thus leading to architectural and software trade-os that must be understood in the context of the intended application’s behavior. Irregular applications are notoriously hard to optimize given their data-dependent access patterns, lack of structuredmore » locality and complex data structures and code patterns. We have ported two irregular applications, graph community detection using the Louvain method (Grappolo) and high-performance conjugate gradient (HPCCG), to the Tilera many-core system and have conducted a detailed study of platform-independent and platform-specific optimizations that improve their performance as well as reduce their overall energy consumption. To conduct this study, we employ an auto-tuning based approach that explores the optimization design space along three dimensions - memory layout schemes, GCC compiler flag choices and OpenMP loop scheduling options. We leverage MIT’s OpenTuner auto-tuning framework to explore and recommend energy optimal choices for different combinations of parameters. We then conduct an in-depth architectural characterization to understand the memory behavior of the selected workloads. Finally, we perform a correlation study to demonstrate the interplay between the hardware behavior and application characteristics. Using auto-tuning, we demonstrate whole-node energy savings and performance improvements of up to 49:6% and 60% relative to a baseline instantiation, and up to 31% and 45:4% relative to manually optimized variants.« less

Antenna Linear-Quadratic-Gaussian (LQG) Controllers: Properties, Limits of Performance, and Tuning Procedure

NASA Technical Reports Server (NTRS)

Gawronski, W.

2004-01-01

Wind gusts are the main disturbances that depreciate tracking precision of microwave antennas and radiotelescopes. The linear-quadratic-Gaussian (LQG) controllers - as compared with the proportional-and-integral (PI) controllers significantly improve the tracking precision in wind disturbances. However, their properties have not been satisfactorily understood; consequently, their tuning is a trial-and-error process. A control engineer has two tools to tune an LQG controller: the choice of coordinate system of the controller model and the selection of weights of the LQG performance index. This article analyzes properties of an open- and closed-loop antenna. It shows that the proper choice of coordinates of the open-loop model simplifies the shaping of the closed-loop performance. The closed-loop properties are influenced by the LQG weights. The article shows the impact of the weights on the antenna closed-loop bandwidth, disturbance rejection properties, and antenna acceleration. The bandwidth and the disturbance rejection characterize the antenna performance, while the acceleration represents the performance limit set by the antenna hardware (motors). The article presents the controller tuning procedure, based on the coordinate selection and the weight properties. The procedure rationally shapes the closed-loop performance, as an alternative to the trial-and-error approach.

Consensus Classification Using Non-Optimized Classifiers.

PubMed

Brownfield, Brett; Lemos, Tony; Kalivas, John H

2018-04-03

Classifying samples into categories is a common problem in analytical chemistry and other fields. Classification is usually based on only one method, but numerous classifiers are available with some being complex, such as neural networks, and others are simple, such as k nearest neighbors. Regardless, most classification schemes require optimization of one or more tuning parameters for best classification accuracy, sensitivity, and specificity. A process not requiring exact selection of tuning parameter values would be useful. To improve classification, several ensemble approaches have been used in past work to combine classification results from multiple optimized single classifiers. The collection of classifications for a particular sample are then combined by a fusion process such as majority vote to form the final classification. Presented in this Article is a method to classify a sample by combining multiple classification methods without specifically classifying the sample by each method, that is, the classification methods are not optimized. The approach is demonstrated on three analytical data sets. The first is a beer authentication set with samples measured on five instruments, allowing fusion of multiple instruments by three ways. The second data set is composed of textile samples from three classes based on Raman spectra. This data set is used to demonstrate the ability to classify simultaneously with different data preprocessing strategies, thereby reducing the need to determine the ideal preprocessing method, a common prerequisite for accurate classification. The third data set contains three wine cultivars for three classes measured at 13 unique chemical and physical variables. In all cases, fusion of nonoptimized classifiers improves classification. Also presented are atypical uses of Procrustes analysis and extended inverted signal correction (EISC) for distinguishing sample similarities to respective classes.

Transient Volcano Deformation Event Detection over Variable Spatial Scales in Alaska

NASA Astrophysics Data System (ADS)

Li, J. D.; Rude, C. M.; Gowanlock, M.; Herring, T.; Pankratius, V.

2016-12-01

Transient deformation events driven by volcanic activity can be monitored using increasingly dense networks of continuous Global Positioning System (GPS) ground stations. The wide spatial extent of GPS networks, the large number of GPS stations, and the spatially and temporally varying scale of deformation events result in the mixing of signals from multiple sources. Typical analysis then necessitates manual identification of times and regions of volcanic activity for further study and the careful tuning of algorithmic parameters to extract possible transient events. Here we present a computer-aided discovery system that facilitates the discovery of potential transient deformation events at volcanoes by providing a framework for selecting varying spatial regions of interest and for tuning the analysis parameters. This site specification step in the framework reduces the spatial mixing of signals from different volcanic sources before applying filters to remove interfering signals originating from other geophysical processes. We analyze GPS data recorded by the Plate Boundary Observatory network and volcanic activity logs from the Alaska Volcano Observatory to search for and characterize transient inflation events in Alaska. We find 3 transient inflation events between 2008 and 2015 at the Akutan, Westdahl, and Shishaldin volcanoes in the Aleutian Islands. The inflation event detected in the first half of 2008 at Akutan is validated other studies, while the inflation events observed in early 2011 at Westdahl and in early 2013 at Shishaldin are previously unreported. Our analysis framework also incorporates modelling of the transient inflation events and enables a comparison of different magma chamber inversion models. Here, we also estimate the magma sources that best describe the deformation observed by the GPS stations at Akutan, Westdahl, and Shishaldin. We acknowledge support from NASA AIST-NNX15AG84G (PI: V. Pankratius).

Exploring possibilities of band gap measurement with off-axis EELS in TEM.

PubMed

Korneychuk, Svetlana; Partoens, Bart; Guzzinati, Giulio; Ramaneti, Rajesh; Derluyn, Joff; Haenen, Ken; Verbeeck, Jo

2018-06-01

A technique to measure the band gap of dielectric materials with high refractive index by means of energy electron loss spectroscopy (EELS) is presented. The technique relies on the use of a circular (Bessel) aperture and suppresses Cherenkov losses and surface-guided light modes by enforcing a momentum transfer selection. The technique also strongly suppresses the elastic zero loss peak, making the acquisition, interpretation and signal to noise ratio of low loss spectra considerably better, especially for excitations in the first few eV of the EELS spectrum. Simulations of the low loss inelastic electron scattering probabilities demonstrate the beneficial influence of the Bessel aperture in this setup even for high accelerating voltages. The importance of selecting the optimal experimental convergence and collection angles is highlighted. The effect of the created off-axis acquisition conditions on the selection of the transitions from valence to conduction bands is discussed in detail on a simplified isotropic two band model. This opens the opportunity for deliberately selecting certain transitions by carefully tuning the microscope parameters. The suggested approach is experimentally demonstrated and provides good signal to noise ratio and interpretable band gap signals on reference samples of diamond, GaN and AlN while offering spatial resolution in the nm range. Copyright © 2018 Elsevier B.V. All rights reserved.

Mean-field and linear regime approach to magnetic hyperthermia of core-shell nanoparticles: can tiny nanostructures fight cancer?

NASA Astrophysics Data System (ADS)

Carrião, Marcus S.; Bakuzis, Andris F.

2016-04-01

The phenomenon of heat dissipation by magnetic materials interacting with an alternating magnetic field, known as magnetic hyperthermia, is an emergent and promising therapy for many diseases, mainly cancer. Here, a magnetic hyperthermia model for core-shell nanoparticles is developed. The theoretical calculation, different from previous models, highlights the importance of heterogeneity by identifying the role of surface and core spins on nanoparticle heat generation. We found that the most efficient nanoparticles should be obtained by selecting materials to reduce the surface to core damping factor ratio, increasing the interface exchange parameter and tuning the surface to core anisotropy ratio for each material combination. From our results we propose a novel heat-based hyperthermia strategy with the focus on improving the heating efficiency of small sized nanoparticles instead of larger ones. This approach might have important implications for cancer treatment and could help improving clinical efficacy.The phenomenon of heat dissipation by magnetic materials interacting with an alternating magnetic field, known as magnetic hyperthermia, is an emergent and promising therapy for many diseases, mainly cancer. Here, a magnetic hyperthermia model for core-shell nanoparticles is developed. The theoretical calculation, different from previous models, highlights the importance of heterogeneity by identifying the role of surface and core spins on nanoparticle heat generation. We found that the most efficient nanoparticles should be obtained by selecting materials to reduce the surface to core damping factor ratio, increasing the interface exchange parameter and tuning the surface to core anisotropy ratio for each material combination. From our results we propose a novel heat-based hyperthermia strategy with the focus on improving the heating efficiency of small sized nanoparticles instead of larger ones. This approach might have important implications for cancer treatment and could help improving clinical efficacy. Electronic supplementary information (ESI) available: Unit cells per region calculation; core-shell Hamiltonian; magnetisation description functions; energy argument of Brillouin function; polydisperse models; details of experimental procedure; LRT versus core-shell model; model calculation software; and shell thickness study. See DOI: 10.1039/C5NR09093H

Optical tuning of electronic valleys (Conference Presentation)

NASA Astrophysics Data System (ADS)

Sie, Edbert J.; Gedik, Nuh

2017-02-01

Monolayer transition-metal dichalcogenides such as MoS2 and WS2 are prime examples of atomically thin semiconducting crystals that exhibit remarkable electronic and optical properties. They have a pair of valleys that can serve as a new electronic degree of freedom, and these valleys obey optical selection rules with circularly polarized light. Here, we discuss how ultrafast laser pulses can be used to tune their energy levels in a controllable valley-selective manner. The energy tunability is extremely large, comparable to what would be obtained using a hundred Tesla of magnetic field. We will also show that such valley tunability can be performed while we effectively manipulate the valley selection rules. Finally, we will explore the prospect of using this technique through photoemission spectroscopy to create a new phase of matter called a valley Floquet topological insulator.

Robot tracking system improvements and visual calibration of orbiter position for radiator inspection

NASA Technical Reports Server (NTRS)

Tonkay, Gregory

1990-01-01

The following separate topics are addressed: (1) improving a robotic tracking system; and (2) providing insights into orbiter position calibration for radiator inspection. The objective of the tracking system project was to provide the capability to track moving targets more accurately by adjusting parameters in the control system and implementing a predictive algorithm. A computer model was developed to emulate the tracking system. Using this model as a test bed, a self-tuning algorithm was developed to tune the system gains. The model yielded important findings concerning factors that affect the gains. The self-tuning algorithms will provide the concepts to write a program to automatically tune the gains in the real system. The section concerning orbiter position calibration provides a comparison to previous work that had been performed for plant growth. It provided the conceptualized routines required to visually determine the orbiter position and orientation. Furthermore, it identified the types of information which are required to flow between the robot controller and the vision system.

Dynamically controlled electromagnetically induced transparency in terahertz graphene metamaterial for modulation and slow light applications

NASA Astrophysics Data System (ADS)

He, Xunjun; Yao, Yuan; Yang, Xingyu; Lu, Guangjun; Yang, Wenlong; Yang, Yuqiang; Wu, Fengmin; Yu, Zhigang; Jiang, Jiuxing

2018-03-01

By patterning two graphene resonators on a SiO2/Si substrate, a dynamically controlled electromagnetically induced transparency (EIT) in the terahertz graphene metamaterial was numerically studied through tuning the structural parameter and Fermi energy of graphene. The calculated surface current distributions demonstrate that the distinct EIT window in the graphene metamaterial results from the near-field coupling of two graphene resonators. Moreover, the EIT window can be actively controlled by tuning Fermi energy combined states of two resonators. When the Fermi energy combined state of two resonators changes from (0.21 and 0.16 eV) to (0.4 and 0.11 eV), the amplitude modulation depth of the EIT peak is 97.8% at 0.45 THz, and the corresponding enhanced factor of group delay with 6 times is obtained. This study offers an alternative tuning method to existing optical, thermal, and relative distance tuning, delivering a promising potential for designing active and miniaturized THz devices.

Model-independent particle accelerator tuning

DOE PAGES

Scheinker, Alexander; Pang, Xiaoying; Rybarcyk, Larry

2013-10-21

We present a new model-independent dynamic feedback technique, rotation rate tuning, for automatically and simultaneously tuning coupled components of uncertain, complex systems. The main advantages of the method are: 1) It has the ability to handle unknown, time-varying systems, 2) It gives known bounds on parameter update rates, 3) We give an analytic proof of its convergence and its stability, and 4) It has a simple digital implementation through a control system such as the Experimental Physics and Industrial Control System (EPICS). Because this technique is model independent it may be useful as a real-time, in-hardware, feedback-based optimization scheme formore » uncertain and time-varying systems. In particular, it is robust enough to handle uncertainty due to coupling, thermal cycling, misalignments, and manufacturing imperfections. As a result, it may be used as a fine-tuning supplement for existing accelerator tuning/control schemes. We present multi-particle simulation results demonstrating the scheme’s ability to simultaneously adaptively adjust the set points of twenty two quadrupole magnets and two RF buncher cavities in the Los Alamos Neutron Science Center Linear Accelerator’s transport region, while the beam properties and RF phase shift are continuously varying. The tuning is based only on beam current readings, without knowledge of particle dynamics. We also present an outline of how to implement this general scheme in software for optimization, and in hardware for feedback-based control/tuning, for a wide range of systems.« less

The effect of laser focus and process parameters on microstructure and mechanical properties of SLM Inconel 718

NASA Astrophysics Data System (ADS)

Bean, Glenn E.; Witkin, David B.; McLouth, Tait D.; Zaldivar, Rafael J.

2018-02-01

Research on the selective laser melting (SLM) method of laser powder bed fusion additive manufacturing (AM) has shown that surface and internal quality of AM parts is directly related to machine settings such as laser energy density, scanning strategies, and atmosphere. To optimize laser parameters for improved component quality, the energy density is typically controlled via laser power, scanning rate, and scanning strategy, but can also be controlled by changing the spot size via laser focal plane shift. Present work being conducted by The Aerospace Corporation was initiated after observing inconsistent build quality of parts printed using OEM-installed settings. Initial builds of Inconel 718 witness geometries using OEM laser parameters were evaluated for surface roughness, density, and porosity while varying energy density via laser focus shift. Based on these results, hardware and laser parameter adjustments were conducted in order to improve build quality and consistency. Tensile testing was also conducted to investigate the effect of build plate location and laser settings on SLM 718. This work has provided insight into the limitations of OEM parameters compared with optimized parameters towards the goal of manufacturing aerospace-grade parts, and has led to the development of a methodology for laser parameter tuning that can be applied to other alloy systems. Additionally, evidence was found that for 718, which derives its strength from post-manufacturing heat treatment, there is a possibility that tensile testing may not be perceptive to defects which would reduce component performance. Ongoing research is being conducted towards identifying appropriate testing and analysis methods for screening and quality assurance.

Fine tuning of transmission features in nanoporous anodic alumina distributed Bragg reflectors

NASA Astrophysics Data System (ADS)

Lim, Siew Yee; Law, Cheryl Suwen; Santos, Abel

2018-01-01

This study introduces an innovative apodisation strategy to tune the filtering features of distributed Bragg reflectors based on nanoporous anodic alumina (NAA-DBRs). The effective medium of NAA-DBRs, which is modulated in a stepwise fashion by a pulse-like anodisation approach, is apodised following a logarithmic negative function to engineer the transmission features of NAA-DBRs. We investigate the effect of various apodisation parameters such as apodisation amplitude difference, anodisation period, current density offset and pore widening time, to tune and optimise the optical properties of NAA-DBRs in terms of central wavelength position, full width at half maximum and quality of photonic stop band. The transmission features of NAA-DBRs are shown to be fully controllable with precision across the spectral regions by means of the apodisation parameters. Our study demonstrates that an apodisation strategy can significantly narrow the width and enhance the quality of the characteristic photonic stop band of NAA-DBRs. This rationally designed anodisation approach based on the combination of apodisation and stepwise pulse anodisation enables the development of optical filters with tuneable filtering features to be integrated into optical technologies acting as essential photonic elements in devices such as optical sensors and biosensors.

Tuning the dielectric properties of metallic-nanoparticle/elastomer composites by strain.

PubMed

Gaiser, Patrick; Binz, Jonas; Gompf, Bruno; Berrier, Audrey; Dressel, Martin

2015-03-14

Tunable metal/dielectric composites are promising candidates for a large number of potential applications in electronics, sensor technologies and optical devices. Here we systematically investigate the dielectric properties of Ag-nanoparticles embedded in the highly flexible elastomer poly-dimethylsiloxane (PDMS). As tuning parameter we use uniaxial and biaxial strain applied to the composite. We demonstrate that both static variations of the filling factor and applied strain lead to the same behavior, i.e., the filling factor of the composite can be tuned by application of strain. In this way the effective static permittivity εeff of the composite can be varied over a very large range. Once the Poisson's ratio of the composite is known, the strain dependent dielectric constant can be accurately described by effective medium theory without any additional free fit parameter up to metal filling factors close to the percolation threshold. It is demonstrated that, starting above the percolation threshold in the metallic phase, applying strain provides the possibility to cross the percolation threshold into the insulating region. The change of regime from conductive phase down to insulating follows the description given by percolation theory and can be actively controlled.

Optical properties and magnetic flux-induced electronic band tuning of a T-graphene sheet and nanoribbon.

PubMed

Bandyopadhyay, Arka; Nandy, Atanu; Chakrabarti, Arunava; Jana, Debnarayan

2017-08-16

Tetragonal graphene (T-graphene) is a theoretically proposed dynamically stable, metallic allotrope of graphene. In this theoretical investigation, a tight binding (TB) model is used to unravel the metal to semiconductor transition of this 2D sheet under the influence of an external magnetic flux. In addition, the environment under which the sheet exposes an appreciable direct band gap of 1.41 ± 0.01 eV is examined. Similarly, the electronic band structure of the narrowest armchair T-graphene nanoribbon (NATGNR) also gets modified with different combinations of magnetic fluxes through the elementary rings. The band tuning parameters are critically identified for both systems. It is observed that the induced band gaps vary remarkably with the tuning parameters. We have also introduced an exact analytical approach to address the band structure of the NATGNR in the absence of any magnetic flux. Finally, the optical properties of the sheet and NATGNR are also critically analysed for both parallel and perpendicular polarizations with the help of density functional theory (DFT). Our study predicts that this material and its nanoribbons can be used in optoelectronic devices.

Modeling Enclosure Design in Above-Grade Walls

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

Lstiburek, J.; Ueno, K.; Musunuru, S.

2016-03-01

This report describes the modeling of typical wall assemblies that have performed well historically in various climate zones. The WUFI (Warme und Feuchte instationar) software (Version 5.3) model was used. A library of input data and results are provided. The provided information can be generalized for application to a broad population of houses, within the limits of existing experience. The WUFI software model was calibrated or tuned using wall assemblies with historically successful performance. The primary performance criteria or failure criteria establishing historic performance was moisture content of the exterior sheathing. The primary tuning parameters (simulation inputs) were airflow andmore » specifying appropriate material properties. Rational hygric loads were established based on experience - specifically rain wetting and interior moisture (RH levels). The tuning parameters were limited or bounded by published data or experience. The WUFI templates provided with this report supply useful information resources to new or less-experienced users. The files present various custom settings that will help avoid results that will require overly conservative enclosure assemblies. Overall, better material data, consistent initial assumptions, and consistent inputs among practitioners will improve the quality of WUFI modeling, and improve the level of sophistication in the field.« less

Photochemical isotope separation

DOEpatents

Robinson, C. Paul; Jensen, Reed J.; Cotter, Theodore P.; Greiner, Norman R.; Boyer, Keith

1987-01-01

A process for separating isotopes by selective excitation of isotopic species of a volatile compound by tuned laser light. A highly cooled gas of the volatile compound is produced in which the isotopic shift is sharpened and defined. Before substantial condensation occurs, the cooled gas is irradiated with laser light precisely tuned to a desired wavelength to selectively excite a particular isotopic species in the cooled gas. The laser light may impart sufficient energy to the excited species to cause it to undergo photochemical reaction or even to photoionize. Alternatively, a two-photon irradiation may be applied to the cooled gas to induce photochemical reaction or photoionization. The process is particularly applicable to the separation of isotopes of uranium and plutonium.

Laser isotope separation

DOEpatents

Robinson, C. Paul; Jensen, Reed J.; Cotter, Theodore P.; Boyer, Keith; Greiner, Norman R.

1988-01-01

A process and apparatus for separating isotopes by selective excitation of isotopic species of a volatile compound by tuned laser light. A highly cooled gas of the volatile compound is produced in which the isotopic shift is sharpened and defined. Before substantial condensation occurs, the cooled gas is irradiated with laser light precisely tuned to a desired wavelength to selectively excite a particular isotopic species in the cooled gas. The laser light may impart sufficient energy to the excited species to cause it to undergo photolysis, photochemical reaction or even to photoionize. Alternatively, a two-photon irradiation may be applied to the cooled gas to induce photolysis, photochemical reaction or photoionization. The process is particularly applicable to the separation of isotopes of uranium.

Isotope separation by laser means

DOEpatents

Robinson, C. Paul; Jensen, Reed J.; Cotter, Theodore P.; Greiner, Norman R.; Boyer, Keith

1982-06-15

A process for separating isotopes by selective excitation of isotopic species of a volatile compound by tuned laser light. A highly cooled gas of the volatile compound is produced in which the isotopic shift is sharpened and defined. Before substantial condensation occurs, the cooled gas is irradiated with laser light precisely tuned to a desired wavelength to selectively excite a particular isotopic species in the cooled gas. The laser light may impart sufficient energy to the excited species to cause it to undergo photochemical reaction or even to photoionize. Alternatively, a two-photon irradiation may be applied to the cooled gas to induce photochemical reaction or photoionization. The process is particularly applicable to the separation of isotopes of uranium and plutonium.

Clustering by soft-constraint affinity propagation: applications to gene-expression data.

PubMed

Leone, Michele; Sumedha; Weigt, Martin

2007-10-15

Similarity-measure-based clustering is a crucial problem appearing throughout scientific data analysis. Recently, a powerful new algorithm called Affinity Propagation (AP) based on message-passing techniques was proposed by Frey and Dueck (2007a). In AP, each cluster is identified by a common exemplar all other data points of the same cluster refer to, and exemplars have to refer to themselves. Albeit its proved power, AP in its present form suffers from a number of drawbacks. The hard constraint of having exactly one exemplar per cluster restricts AP to classes of regularly shaped clusters, and leads to suboptimal performance, e.g. in analyzing gene expression data. This limitation can be overcome by relaxing the AP hard constraints. A new parameter controls the importance of the constraints compared to the aim of maximizing the overall similarity, and allows to interpolate between the simple case where each data point selects its closest neighbor as an exemplar and the original AP. The resulting soft-constraint affinity propagation (SCAP) becomes more informative, accurate and leads to more stable clustering. Even though a new a priori free parameter is introduced, the overall dependence of the algorithm on external tuning is reduced, as robustness is increased and an optimal strategy for parameter selection emerges more naturally. SCAP is tested on biological benchmark data, including in particular microarray data related to various cancer types. We show that the algorithm efficiently unveils the hierarchical cluster structure present in the data sets. Further on, it allows to extract sparse gene expression signatures for each cluster.

Regularization Parameter Selection for Nonlinear Iterative Image Restoration and MRI Reconstruction Using GCV and SURE-Based Methods

PubMed Central

Ramani, Sathish; Liu, Zhihao; Rosen, Jeffrey; Nielsen, Jon-Fredrik; Fessler, Jeffrey A.

2012-01-01

Regularized iterative reconstruction algorithms for imaging inverse problems require selection of appropriate regularization parameter values. We focus on the challenging problem of tuning regularization parameters for nonlinear algorithms for the case of additive (possibly complex) Gaussian noise. Generalized cross-validation (GCV) and (weighted) mean-squared error (MSE) approaches (based on Stein's Unbiased Risk Estimate— SURE) need the Jacobian matrix of the nonlinear reconstruction operator (representative of the iterative algorithm) with respect to the data. We derive the desired Jacobian matrix for two types of nonlinear iterative algorithms: a fast variant of the standard iterative reweighted least-squares method and the contemporary split-Bregman algorithm, both of which can accommodate a wide variety of analysis- and synthesis-type regularizers. The proposed approach iteratively computes two weighted SURE-type measures: Predicted-SURE and Projected-SURE (that require knowledge of noise variance σ2), and GCV (that does not need σ2) for these algorithms. We apply the methods to image restoration and to magnetic resonance image (MRI) reconstruction using total variation (TV) and an analysis-type ℓ1-regularization. We demonstrate through simulations and experiments with real data that minimizing Predicted-SURE and Projected-SURE consistently lead to near-MSE-optimal reconstructions. We also observed that minimizing GCV yields reconstruction results that are near-MSE-optimal for image restoration and slightly sub-optimal for MRI. Theoretical derivations in this work related to Jacobian matrix evaluations can be extended, in principle, to other types of regularizers and reconstruction algorithms. PMID:22531764

A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package

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

Genser, Krzysztof; Hatcher, Robert; Kelsey, Michael

The Geant4 simulation toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. These models rely on measured cross-sections and phenomenological models with the physically motivated parameters that are tuned to cover many application domains. To study what uncertainties are associated with the Geant4 physics models we have designed and implemented a comprehensive, modular, user-friendly software toolkit that allows the variation of one or more parameters of one or more Geant4 physics models involved in simulation studies. It also enables analysis of multiple variantsmore » of the resulting physics observables of interest in order to estimate the uncertainties associated with the simulation model choices. Based on modern event-processing infrastructure software, the toolkit offers a variety of attractive features, e.g. exible run-time con gurable work ow, comprehensive bookkeeping, easy to expand collection of analytical components. Design, implementation technology, and key functionalities of the toolkit are presented in this paper and illustrated with selected results.« less

Dynamics of entanglement of a three-level atom in motion interacting with two coupled modes including parametric down conversion

NASA Astrophysics Data System (ADS)

Faghihi, M. J.; Tavassoly, M. K.; Hatami, M.

In this paper, a model by which we study the interaction between a motional three-level atom and two-mode field injected simultaneously in a bichromatic cavity is considered; the three-level atom is assumed to be in a Λ-type configuration. As a result, the atom-field and the field-field interaction (parametric down conversion) will be appeared. It is shown that, by applying a canonical transformation, the introduced model can be reduced to a well-known form of the generalized Jaynes-Cummings model. Under particular initial conditions, which may be prepared for the atom and the field, the time evolution of state vector of the entire system is analytically evaluated. Then, the dynamics of atom by considering ‘atomic population inversion’ and two different measures of entanglement, i.e., ‘von Neumann entropy’ and ‘idempotency defect’ is discussed, in detail. It is deduced from the numerical results that, the duration and the maximum amount of the considered physical quantities can be suitably tuned by selecting the proper field-mode structure parameter p and the detuning parameters.

Patient-specific parameter estimation in single-ventricle lumped circulation models under uncertainty

PubMed Central

Schiavazzi, Daniele E.; Baretta, Alessia; Pennati, Giancarlo; Hsia, Tain-Yen; Marsden, Alison L.

2017-01-01

Summary Computational models of cardiovascular physiology can inform clinical decision-making, providing a physically consistent framework to assess vascular pressures and flow distributions, and aiding in treatment planning. In particular, lumped parameter network (LPN) models that make an analogy to electrical circuits offer a fast and surprisingly realistic method to reproduce the circulatory physiology. The complexity of LPN models can vary significantly to account, for example, for cardiac and valve function, respiration, autoregulation, and time-dependent hemodynamics. More complex models provide insight into detailed physiological mechanisms, but their utility is maximized if one can quickly identify patient specific parameters. The clinical utility of LPN models with many parameters will be greatly enhanced by automated parameter identification, particularly if parameter tuning can match non-invasively obtained clinical data. We present a framework for automated tuning of 0D lumped model parameters to match clinical data. We demonstrate the utility of this framework through application to single ventricle pediatric patients with Norwood physiology. Through a combination of local identifiability, Bayesian estimation and maximum a posteriori simplex optimization, we show the ability to automatically determine physiologically consistent point estimates of the parameters and to quantify uncertainty induced by errors and assumptions in the collected clinical data. We show that multi-level estimation, that is, updating the parameter prior information through sub-model analysis, can lead to a significant reduction in the parameter marginal posterior variance. We first consider virtual patient conditions, with clinical targets generated through model solutions, and second application to a cohort of four single-ventricle patients with Norwood physiology. PMID:27155892

Simultaneous feature selection and parameter optimisation using an artificial ant colony: case study of melting point prediction

PubMed Central

O'Boyle, Noel M; Palmer, David S; Nigsch, Florian; Mitchell, John BO

2008-01-01

Background We present a novel feature selection algorithm, Winnowing Artificial Ant Colony (WAAC), that performs simultaneous feature selection and model parameter optimisation for the development of predictive quantitative structure-property relationship (QSPR) models. The WAAC algorithm is an extension of the modified ant colony algorithm of Shen et al. (J Chem Inf Model 2005, 45: 1024–1029). We test the ability of the algorithm to develop a predictive partial least squares model for the Karthikeyan dataset (J Chem Inf Model 2005, 45: 581–590) of melting point values. We also test its ability to perform feature selection on a support vector machine model for the same dataset. Results Starting from an initial set of 203 descriptors, the WAAC algorithm selected a PLS model with 68 descriptors which has an RMSE on an external test set of 46.6°C and R2 of 0.51. The number of components chosen for the model was 49, which was close to optimal for this feature selection. The selected SVM model has 28 descriptors (cost of 5, ε of 0.21) and an RMSE of 45.1°C and R2 of 0.54. This model outperforms a kNN model (RMSE of 48.3°C, R2 of 0.47) for the same data and has similar performance to a Random Forest model (RMSE of 44.5°C, R2 of 0.55). However it is much less prone to bias at the extremes of the range of melting points as shown by the slope of the line through the residuals: -0.43 for WAAC/SVM, -0.53 for Random Forest. Conclusion With a careful choice of objective function, the WAAC algorithm can be used to optimise machine learning and regression models that suffer from overfitting. Where model parameters also need to be tuned, as is the case with support vector machine and partial least squares models, it can optimise these simultaneously. The moving probabilities used by the algorithm are easily interpreted in terms of the best and current models of the ants, and the winnowing procedure promotes the removal of irrelevant descriptors. PMID:18959785

Hierarchical Gene Selection and Genetic Fuzzy System for Cancer Microarray Data Classification

PubMed Central

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice. PMID:25823003

Hierarchical gene selection and genetic fuzzy system for cancer microarray data classification.

PubMed

Nguyen, Thanh; Khosravi, Abbas; Creighton, Douglas; Nahavandi, Saeid

2015-01-01

This paper introduces a novel approach to gene selection based on a substantial modification of analytic hierarchy process (AHP). The modified AHP systematically integrates outcomes of individual filter methods to select the most informative genes for microarray classification. Five individual ranking methods including t-test, entropy, receiver operating characteristic (ROC) curve, Wilcoxon and signal to noise ratio are employed to rank genes. These ranked genes are then considered as inputs for the modified AHP. Additionally, a method that uses fuzzy standard additive model (FSAM) for cancer classification based on genes selected by AHP is also proposed in this paper. Traditional FSAM learning is a hybrid process comprising unsupervised structure learning and supervised parameter tuning. Genetic algorithm (GA) is incorporated in-between unsupervised and supervised training to optimize the number of fuzzy rules. The integration of GA enables FSAM to deal with the high-dimensional-low-sample nature of microarray data and thus enhance the efficiency of the classification. Experiments are carried out on numerous microarray datasets. Results demonstrate the performance dominance of the AHP-based gene selection against the single ranking methods. Furthermore, the combination of AHP-FSAM shows a great accuracy in microarray data classification compared to various competing classifiers. The proposed approach therefore is useful for medical practitioners and clinicians as a decision support system that can be implemented in the real medical practice.

Highly adaptive tests for group differences in brain functional connectivity.

PubMed

Kim, Junghi; Pan, Wei

2015-01-01

Resting-state functional magnetic resonance imaging (rs-fMRI) and other technologies have been offering evidence and insights showing that altered brain functional networks are associated with neurological illnesses such as Alzheimer's disease. Exploring brain networks of clinical populations compared to those of controls would be a key inquiry to reveal underlying neurological processes related to such illnesses. For such a purpose, group-level inference is a necessary first step in order to establish whether there are any genuinely disrupted brain subnetworks. Such an analysis is also challenging due to the high dimensionality of the parameters in a network model and high noise levels in neuroimaging data. We are still in the early stage of method development as highlighted by Varoquaux and Craddock (2013) that "there is currently no unique solution, but a spectrum of related methods and analytical strategies" to learn and compare brain connectivity. In practice the important issue of how to choose several critical parameters in estimating a network, such as what association measure to use and what is the sparsity of the estimated network, has not been carefully addressed, largely because the answers are unknown yet. For example, even though the choice of tuning parameters in model estimation has been extensively discussed in the literature, as to be shown here, an optimal choice of a parameter for network estimation may not be optimal in the current context of hypothesis testing. Arbitrarily choosing or mis-specifying such parameters may lead to extremely low-powered tests. Here we develop highly adaptive tests to detect group differences in brain connectivity while accounting for unknown optimal choices of some tuning parameters. The proposed tests combine statistical evidence against a null hypothesis from multiple sources across a range of plausible tuning parameter values reflecting uncertainty with the unknown truth. These highly adaptive tests are not only easy to use, but also high-powered robustly across various scenarios. The usage and advantages of these novel tests are demonstrated on an Alzheimer's disease dataset and simulated data.

The dynamics and tuning of orchestral crotales

NASA Astrophysics Data System (ADS)

Deutsch, Bradley M.; Ramirez, Cherie L.; Moore, Thomas R.

2004-10-01

An experimental and theoretical investigation of the acoustic and vibrational properties of orchestral crotales within the range C6 to C8 is reported. Interferograms of the acoustically important modes of vibration are presented and the frequencies are reported. It is shown that the acoustic spectra of crotales are not predicted by assuming that they are either thin circular plates or annular plates clamped at the center, despite the physical resemblance to these objects. Results from finite element analysis are presented that demonstrate how changing the size of the central mass affects the tuning of the instruments, and it is concluded that crotales are not currently designed to ensure optimal tuning. The possibility of using annular plates as crotales is also investigated and the physical parameters for such a set of instruments are presented. .