Equating Scores from Adaptive to Linear Tests
ERIC Educational Resources Information Center
van der Linden, Wim J.
2006-01-01
Two local methods for observed-score equating are applied to the problem of equating an adaptive test to a linear test. In an empirical study, the methods were evaluated against a method based on the test characteristic function (TCF) of the linear test and traditional equipercentile equating applied to the ability estimates on the adaptive test…
Linearly-Constrained Adaptive Signal Processing Methods
NASA Astrophysics Data System (ADS)
Griffiths, Lloyd J.
1988-01-01
In adaptive least-squares estimation problems, a desired signal d(n) is estimated using a linear combination of L observation values samples xi (n), x2(n), . . . , xL-1(n) and denoted by the vector X(n). The estimate is formed as the inner product of this vector with a corresponding L-dimensional weight vector W. One particular weight vector of interest is Wopt which minimizes the mean-square between d(n) and the estimate. In this context, the term `mean-square difference' is a quadratic measure such as statistical expectation or time average. The specific value of W which achieves the minimum is given by the prod-uct of the inverse data covariance matrix and the cross-correlation between the data vector and the desired signal. The latter is often referred to as the P-vector. For those cases in which time samples of both the desired and data vector signals are available, a variety of adaptive methods have been proposed which will guarantee that an iterative weight vector Wa(n) converges (in some sense) to the op-timal solution. Two which have been extensively studied are the recursive least-squares (RLS) method and the LMS gradient approximation approach. There are several problems of interest in the communication and radar environment in which the optimal least-squares weight set is of interest and in which time samples of the desired signal are not available. Examples can be found in array processing in which only the direction of arrival of the desired signal is known and in single channel filtering where the spectrum of the desired response is known a priori. One approach to these problems which has been suggested is the P-vector algorithm which is an LMS-like approximate gradient method. Although it is easy to derive the mean and variance of the weights which result with this algorithm, there has never been an identification of the corresponding underlying error surface which the procedure searches. The purpose of this paper is to suggest an alternative
Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Boskovic, Jovan D.
2008-01-01
This paper presents a bounded linear stability analysis for a hybrid adaptive control that blends both direct and indirect adaptive control. Stability and convergence of nonlinear adaptive control are analyzed using an approximate linear equivalent system. A stability margin analysis shows that a large adaptive gain can lead to a reduced phase margin. This method can enable metrics-driven adaptive control whereby the adaptive gain is adjusted to meet stability margin requirements.
Synaptic dynamics: linear model and adaptation algorithm.
Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W
2014-08-01
In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and
A linear combination of modified Bessel functions
NASA Technical Reports Server (NTRS)
Shitzer, A.; Chato, J. C.
1971-01-01
A linear combination of modified Bessel functions is defined, discussed briefly, and tabulated. This combination was found to recur in the analysis of various heat transfer problems and in the analysis of the thermal behavior of living tissue when modeled by cylindrical shells.
Features in visual search combine linearly
Pramod, R. T.; Arun, S. P.
2014-01-01
Single features such as line orientation and length are known to guide visual search, but relatively little is known about how multiple features combine in search. To address this question, we investigated how search for targets differing in multiple features (intensity, length, orientation) from the distracters is related to searches for targets differing in each of the individual features. We tested race models (based on reaction times) and co-activation models (based on reciprocal of reaction times) for their ability to predict multiple feature searches. Multiple feature searches were best accounted for by a co-activation model in which feature information combined linearly (r = 0.95). This result agrees with the classic finding that these features are separable i.e., subjective dissimilarity ratings sum linearly. We then replicated the classical finding that the length and width of a rectangle are integral features—in other words, they combine nonlinearly in visual search. However, to our surprise, upon including aspect ratio as an additional feature, length and width combined linearly and this model outperformed all other models. Thus, length and width of a rectangle became separable when considered together with aspect ratio. This finding predicts that searches involving shapes with identical aspect ratio should be more difficult than searches where shapes differ in aspect ratio. We confirmed this prediction on a variety of shapes. We conclude that features in visual search co-activate linearly and demonstrate for the first time that aspect ratio is a novel feature that guides visual search. PMID:24715328
Inpainting with sparse linear combinations of exemplars
Wohlberg, Brendt
2008-01-01
We introduce a new exemplar-based inpainting algorithm based on representing the region to be inpainted as a sparse linear combination of blocks extracted from similar parts of the image being inpainted. This method is conceptually simple, being computed by functional minimization, and avoids the complexity of correctly ordering the filling in of missing regions of other exemplar-based methods. Initial performance comparisons on small inpainting regions indicate that this method provides similar or better performance than other recent methods.
Geometry-free linear combinations for Galileo
NASA Astrophysics Data System (ADS)
Henkel, Patrick
2009-11-01
Global navigation satellites of the European Galileo system transmit code signals on four carriers in the L1, E5a, E5b and E6 band. New geometry-free linear combinations are presented that eliminate the geometry terms (user to satellite ranges and orbital errors), the clock errors of the user and satellites and the tropospheric delay. The remaining parameters of these carrier phase combinations include integer ambiguities, ionospheric delays, carrier phase multipath and phase noise. The weighting coefficients are designed such that the integer nature of ambiguities is maintained. The use of four frequency combinations is highly recommended due to a noise reduction of up to 14.4 dB and an ionospheric reduction of up to 25.6 dB compared to two frequency geometry-free combinations. Moreover, a modified Least-squares Ambiguity Decorrelation Adjustment (LAMBDA) algorithm is suggested, which differs in two points from the traditional approach: the baseline is replaced by the ionospheric delay and the correlation is caused by linear combinations instead of double differences. For correct ambiguity resolution, the ionospheric delay can be determined with millimeter accuracy. This is quite beneficial as the ionosphere represents the largest source of error for absolute positioning.
Linear combination reading program for capture gamma rays
Tanner, Allan B.
1971-01-01
This program computes a weighting function, Qj, which gives a scalar output value of unity when applied to the spectrum of a desired element and a minimum value (considering statistics) when applied to spectra of materials not containing the desired element. Intermediate values are obtained for materials containing the desired element, in proportion to the amount of the element they contain. The program is written in the BASIC language in a format specific to the Hewlett-Packard 2000A Time-Sharing System, and is an adaptation of an earlier program for linear combination reading for X-ray fluorescence analysis (Tanner and Brinkerhoff, 1971). Following the program is a sample run from a study of the application of the linear combination technique to capture-gamma-ray analysis for calcium (report in preparation).
Indirect techniques for adaptive input-output linearization of non-linear systems
NASA Technical Reports Server (NTRS)
Teel, Andrew; Kadiyala, Raja; Kokotovic, Peter; Sastry, Shankar
1991-01-01
A technique of indirect adaptive control based on certainty equivalence for input output linearization of nonlinear systems is proven convergent. It does not suffer from the overparameterization drawbacks of the direct adaptive control techniques on the same plant. This paper also contains a semiindirect adaptive controller which has several attractive features of both the direct and indirect schemes.
SLICC: Spectral LInear Combination for Coronagraphy
NASA Astrophysics Data System (ADS)
Cox, Andrew W.; Grady, Carol A.
2015-01-01
The STIS corongraph is the only remaining working coronagraph on HST, but one, due to use of the unfiltered CCD, which has a bandpass spanning from 2000-10,000 A. This resulted in extreme sensitivity to the color of a source (Grady et al. 2005), and prompted use of adhoc linear combinations of point spread function template observations to reveal the circumstellar disks associated with T Tauri stars. A limited set of T Tauri stars have low resolution spectrophotometry spanning 1150-10,000 A, with sufficiently many epochs to permit us to fit both the imagery and the broadband optical spectral energy distribution. We present the results of this quantitative test of spectral deconvolution of STIS coronagraphy.
Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham K.; Krishnakumar, Kalmanje Srinlvas; Bakhtiari-Nejad, Maryam
2009-01-01
This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.
Development of a digital adaptive optimal linear regulator flight controller
NASA Technical Reports Server (NTRS)
Berry, P.; Kaufman, H.
1975-01-01
Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.
NASA Astrophysics Data System (ADS)
Sicuro, Gabriele; Bagchi, Debarshee; Tsallis, Constantino
2016-05-01
We analyze the distribution that extremizes a linear combination of the Boltzmann-Gibbs entropy and the nonadditive q-entropy. We show that this distribution can be expressed in terms of a Lambert function. Both the entropic functional and the extremizing distribution can be associated with a nonlinear Fokker-Planck equation obtained from a master equation with nonlinear transition rates. Also, we evaluate the entropy extremized by a linear combination of a Gaussian distribution (which extremizes the Boltzmann-Gibbs entropy) and a q-Gaussian distribution (which extremizes the q-entropy). We give its explicit expression for q = 0, and discuss the other cases numerically. The entropy that we obtain can be expressed, for q = 0, in terms of Lambert functions, and exhibits a discontinuity in the second derivative for all values of q < 1. The entire discussion is closely related to recent results for type-II superconductors and for the statistics of the standard map.
Self-characterization of linear and nonlinear adaptive optics systems.
Hampton, Peter J; Conan, Rodolphe; Keskin, Onur; Bradley, Colin; Agathoklis, Pan
2008-01-10
We present methods used to determine the linear or nonlinear static response and the linear dynamic response of an adaptive optics (AO) system. This AO system consists of a nonlinear microelectromechanical systems deformable mirror (DM), a linear tip-tilt mirror (TTM), a control computer, and a Shack-Hartmann wavefront sensor. The system is modeled using a single-input-single-output structure to determine the one-dimensional transfer function of the dynamic response of the chain of system hardware. An AO system has been shown to be able to characterize its own response without additional instrumentation. Experimentally determined models are given for a TTM and a DM. PMID:18188192
On the Linear Combination of Exponential and Gamma Random Variables
NASA Astrophysics Data System (ADS)
Nadarajah, Saralees; Kotz, Samuel
2005-06-01
The exact distribution of the linear combination α X + β Y is derived when X and Y are exponential and gamma random variables distributed independently of each other. A measure of entropy of the linear combination is investigated. We also provide computer programs for generating tabulations of the percentage points associated with the linear combination. The work is motivated by examples in automation, control, fuzzy sets, neurocomputing and other areas of computer science.
Shrinkage Estimation of Linear Combinations of True Scores.
ERIC Educational Resources Information Center
Longford, Nicholas T.
1997-01-01
It is demonstrated that, in the presence of population information, a linear combination of true scores can be estimated more efficiently than by the same linear combination of the observed scores. Three criteria for optimality are discussed, but they yield the same solution, described as a multivariate shrinkage estimator. (Author/SLD)
Unmasking the linear behaviour of slow motor adaptation to prolonged convergence.
Erkelens, Ian M; Thompson, Benjamin; Bobier, William R
2016-06-01
Adaptation to changing environmental demands is central to maintaining optimal motor system function. Current theories suggest that adaptation in both the skeletal-motor and oculomotor systems involves a combination of fast (reflexive) and slow (recalibration) mechanisms. Here we used the oculomotor vergence system as a model to investigate the mechanisms underlying slow motor adaptation. Unlike reaching with the upper limbs, vergence is less susceptible to changes in cognitive strategy that can affect the behaviour of motor adaptation. We tested the hypothesis that mechanisms of slow motor adaptation reflect early neural processing by assessing the linearity of adaptive responses over a large range of stimuli. Using varied disparity stimuli in conflict with accommodation, the slow adaptation of tonic vergence was found to exhibit a linear response whereby the rate (R(2) = 0.85, P < 0.0001) and amplitude (R(2) = 0.65, P < 0.0001) of the adaptive effects increased proportionally with stimulus amplitude. These results suggest that this slow adaptive mechanism is an early neural process, implying a fundamental physiological nature that is potentially dominated by subcortical and cerebellar substrates. PMID:26991129
Adaptive stochastic control for a class of linear systems.
NASA Technical Reports Server (NTRS)
Tse, E.; Athans, M.
1972-01-01
The problem considered in this paper deals with the control of linear discrete-time stochastic systems with unknown (possibly time-varying and random) gain parameters. The philosophy of control is based on the use of an open-loop feedback optimal (OLFO) control using a quadratic index of performance. It is shown that the OLFO system consists of (1) an identifier that estimates the system state variables and gain parameters and (2) a controller described by an 'adaptive' gain and correction term. Several qualitative properties and asymptotic properties of the OLFO adaptive system are discussed. Simulation results dealing with the control of stable and unstable third-order plants are presented. The key quantitative result is the precise variation of the control system adaptive gains as a function of the future expected uncertainty of the parameters; thus, in this problem the ordinary 'separation theorem' does not hold.
Linear and Order Statistics Combiners for Pattern Classification
NASA Technical Reports Server (NTRS)
Tumer, Kagan; Ghosh, Joydeep; Lau, Sonie (Technical Monitor)
2001-01-01
Several researchers have experimentally shown that substantial improvements can be obtained in difficult pattern recognition problems by combining or integrating the outputs of multiple classifiers. This chapter provides an analytical framework to quantify the improvements in classification results due to combining. The results apply to both linear combiners and order statistics combiners. We first show that to a first order approximation, the error rate obtained over and above the Bayes error rate, is directly proportional to the variance of the actual decision boundaries around the Bayes optimum boundary. Combining classifiers in output space reduces this variance, and hence reduces the 'added' error. If N unbiased classifiers are combined by simple averaging. the added error rate can be reduced by a factor of N if the individual errors in approximating the decision boundaries are uncorrelated. Expressions are then derived for linear combiners which are biased or correlated, and the effect of output correlations on ensemble performance is quantified. For order statistics based non-linear combiners, we derive expressions that indicate how much the median, the maximum and in general the i-th order statistic can improve classifier performance. The analysis presented here facilitates the understanding of the relationships among error rates, classifier boundary distributions, and combining in output space. Experimental results on several public domain data sets are provided to illustrate the benefits of combining and to support the analytical results.
Adaptive security systems -- Combining expert systems with adaptive technologies
Argo, P.; Loveland, R.; Anderson, K.
1997-09-01
The Adaptive Multisensor Integrated Security System (AMISS) uses a variety of computational intelligence techniques to reason from raw sensor data through an array of processing layers to arrive at an assessment for alarm/alert conditions based on human behavior within a secure facility. In this paper, the authors give an overview of the system and briefly describe some of the major components of the system. This system is currently under development and testing in a realistic facility setting.
Rear-heavy car control by adaptive linear optimal preview
NASA Astrophysics Data System (ADS)
Thommyppillai, M.; Evangelou, S.; Sharp, R. S.
2010-05-01
Adaptive linear optimal preview control theory is applied to a simple but non-linear car model, with parameters chosen to make the rear axle saturate first in any quasi-steady manoeuvre. The tendency of such a car to spin above a critical speed, which is a function of its running state, causes control to be especially difficult when operating near to the limit of the rear-axle force system. As in previous work, trim states and optimal gains are computed off-line for a given speed and a full range of lateral accelerations. Gain-scheduling with interpolation over trims and gain sets is used to keep the control appropriate to the running conditions, as they change. Simulations of manoeuvres are used to test and demonstrate the system capability. It is shown that utilising the rear-axle lateral-slip ratio as the scheduling variable, in the case of this rear-heavy car, gives excellent tracking, even when the tyres are run close to full saturation. It is implied by this and previous work that the general case can be treated effectively by monitoring both front- and rear-axle slips and scheduling on a worst-case basis.
A new adaptive multiple modelling approach for non-linear and non-stationary systems
NASA Astrophysics Data System (ADS)
Chen, Hao; Gong, Yu; Hong, Xia
2016-07-01
This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.
NASA Astrophysics Data System (ADS)
De la sen, M.
2006-03-01
This paper deals with the pole-placement type robust adaptive control of continuous linear systems in the presence of bounded noise and a common class of unmodeled dynamics with the use of multiple estimation schemes working in parallel. The multiestimation scheme consisting of the above set of various single estimation schemes is a tool used to minimize the plant identification error by building an estimate which is a convex combination of the estimates at all time. The weighting functions of the individual estimates are provided at each time by a suboptimization scheme for a quadratic loss function of a possibly filtered tracking error and/or control input. The robust stability of the overall adaptive scheme is ensured by an adaptation relative dead zone which takes into account the contribution of the unmodeled dynamics and bounded noise. The basic results are derived for two different estimation strategies which have either a shared regressor with the plant or individual regressors for the input contribution and its relevant time-derivatives. In this second case, the plant input is obtained through a similar convex combination rule as the one used for the estimators in the first approach. An extension of the basic strategies is also pointed out including a combined use of the suboptimization scheme with a supervisor of past measures for the on-line calculation of the estimator weights in the convex combination.
Adaptive Error Estimation in Linearized Ocean General Circulation Models
NASA Technical Reports Server (NTRS)
Chechelnitsky, Michael Y.
1999-01-01
Data assimilation methods are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. This study addresses the problem of estimating model and measurement error statistics from observations. We start by testing innovation based methods of adaptive error estimation with low-dimensional models in the North Pacific (5-60 deg N, 132-252 deg E) to TOPEX/POSEIDON (TIP) sea level anomaly data, acoustic tomography data from the ATOC project, and the MIT General Circulation Model (GCM). A reduced state linear model that describes large scale internal (baroclinic) error dynamics is used. The methods are shown to be sensitive to the initial guess for the error statistics and the type of observations. A new off-line approach is developed, the covariance matching approach (CMA), where covariance matrices of model-data residuals are "matched" to their theoretical expectations using familiar least squares methods. This method uses observations directly instead of the innovations sequence and is shown to be related to the MT method and the method of Fu et al. (1993). Twin experiments using the same linearized MIT GCM suggest that altimetric data are ill-suited to the estimation of internal GCM errors, but that such estimates can in theory be obtained using acoustic data. The CMA is then applied to T/P sea level anomaly data and a linearization of a global GFDL GCM which uses two vertical modes. We show that the CMA method can be used with a global model and a global data set, and that the estimates of the error statistics are robust. We show that the fraction of the GCM-T/P residual variance explained by the model error is larger than that derived in Fukumori et al.(1999) with the method of Fu et al.(1993). Most of the model error is explained by the barotropic mode. However, we find that impact of the change in the error statistics on the data assimilation estimates is very small. This is explained by the large
NASA Astrophysics Data System (ADS)
Zhang, Ruikun; Hou, Zhongsheng; Ji, Honghai; Yin, Chenkun
2016-04-01
In this paper, an adaptive iterative learning control scheme is proposed for a class of non-linearly parameterised systems with unknown time-varying parameters and input saturations. By incorporating a saturation function, a new iterative learning control mechanism is presented which includes a feedback term and a parameter updating term. Through the use of parameter separation technique, the non-linear parameters are separated from the non-linear function and then a saturated difference updating law is designed in iteration domain by combining the unknown parametric term of the local Lipschitz continuous function and the unknown time-varying gain into an unknown time-varying function. The analysis of convergence is based on a time-weighted Lyapunov-Krasovskii-like composite energy function which consists of time-weighted input, state and parameter estimation information. The proposed learning control mechanism warrants a L2[0, T] convergence of the tracking error sequence along the iteration axis. Simulation results are provided to illustrate the effectiveness of the adaptive iterative learning control scheme.
Asymptotic Linearity of Optimal Control Modification Adaptive Law with Analytical Stability Margins
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
Optimal control modification has been developed to improve robustness to model-reference adaptive control. For systems with linear matched uncertainty, optimal control modification adaptive law can be shown by a singular perturbation argument to possess an outer solution that exhibits a linear asymptotic property. Analytical expressions of phase and time delay margins for the outer solution can be obtained. Using the gradient projection operator, a free design parameter of the adaptive law can be selected to satisfy stability margins.
Strand-invading linear probe combined with unmodified PNA.
Asanuma, Hiroyuki; Niwa, Rie; Akahane, Mariko; Murayama, Keiji; Kashida, Hiromu; Kamiya, Yukiko
2016-09-15
Efficient strand invasion by a linear probe to fluorescently label double-stranded DNA has been implemented by employing a probe and unmodified PNA. As a fluorophore, we utilized ethynylperylene. Multiple ethynylperylene residues were incorporated into the DNA probe via a d-threoninol scaffold. The ethynylperylene did not significantly disrupt hybridization with complementary DNA. The linear probe self-quenched in the absence of target DNA and did not hybridize with PNA. A gel-shift assay revealed that linear probe and PNA combination invaded the central region of double-stranded DNA upon heat-shock treatment to form a double duplex. To further suppress the background emission and increase the stability of the probe/DNA duplex, a probe containing anthraquinones as well as ethynylperylene was synthesized. This probe and PNA invader pair detected an internal sequence in a double-stranded DNA with high sensitivity when heat shock treatment was used. The probe and PNA pair was able to invade at the terminus of a long double-stranded DNA at 40°C at 100mM NaCl concentration. PMID:27394693
Combined real-time ultrasound plane wave compounding and linear array optoacoustics
NASA Astrophysics Data System (ADS)
Fournelle, Marc; Bost, Wolfgang; Tretbar, Steffen
2015-07-01
In optoacoustic imaging, the high optical contrast between different tissue types is combined with the high resolution and low scattering of ultrasound. Using adapted reconstruction algorithms, images of the distribution of light absorption in tissue can be obtained. Such as in any emerging modality, there is limited experience regarding the interpretation of optoacoustic images. For this reason, we developed a flexible hardware platform combining ultrasound imaging with optoacoustics. The system is based on the software processing of channel data and different types of reconstruction algorithms are implemented. It combines optoacoustic imaging based on linear arrays for detection with plane wave compounding ultrasound. Our system further includes a custom made probe based on a 7,5 MHz array, custom made fibre bundles for targeted light delivery and an acoustic coupling pad. The system was characterized on phantoms and first in-vivo datasets from subcutaneous vasculature were acquired.
Combining Step Gradients and Linear Gradients in Density.
Kumar, Ashok A; Walz, Jenna A; Gonidec, Mathieu; Mace, Charles R; Whitesides, George M
2015-06-16
Combining aqueous multiphase systems (AMPS) and magnetic levitation (MagLev) provides a method to produce hybrid gradients in apparent density. AMPS—solutions of different polymers, salts, or surfactants that spontaneously separate into immiscible but predominantly aqueous phases—offer thermodynamically stable steps in density that can be tuned by the concentration of solutes. MagLev—the levitation of diamagnetic objects in a paramagnetic fluid within a magnetic field gradient—can be arranged to provide a near-linear gradient in effective density where the height of a levitating object above the surface of the magnet corresponds to its density; the strength of the gradient in effective density can be tuned by the choice of paramagnetic salt and its concentrations and by the strength and gradient in the magnetic field. Including paramagnetic salts (e.g., MnSO4 or MnCl2) in AMPS, and placing them in a magnetic field gradient, enables their use as media for MagLev. The potential to create large steps in density with AMPS allows separations of objects across a range of densities. The gradients produced by MagLev provide resolution over a continuous range of densities. By combining these approaches, mixtures of objects with large differences in density can be separated and analyzed simultaneously. Using MagLev to add an effective gradient in density also enables tuning the range of densities captured at an interface of an AMPS by simply changing the position of the container in the magnetic field. Further, by creating AMPS in which phases have different concentrations of paramagnetic ions, the phases can provide different resolutions in density. These results suggest that combining steps in density with gradients in density can enable new classes of separations based on density. PMID:25978093
Deng, Hua; Li, Han-Xiong; Wu, Yi-Hu
2008-09-01
A new feedback-linearization-based neural network (NN) adaptive control is proposed for unknown nonaffine nonlinear discrete-time systems. An equivalent model in affine-like form is first derived for the original nonaffine discrete-time systems as feedback linearization methods cannot be implemented for such systems. Then, feedback linearization adaptive control is implemented based on the affine-like equivalent model identified with neural networks. Pretraining is not required and the weights of the neural networks used in adaptive control are directly updated online based on the input-output measurement. The dead-zone technique is used to remove the requirement of persistence excitation during the adaptation. With the proposed neural network adaptive control, stability and performance of the closed-loop system are rigorously established. Illustrated examples are provided to validate the theoretical findings. PMID:18779092
An adaptive over/under data combination method
NASA Astrophysics Data System (ADS)
He, Jian-Wei; Lu, Wen-Kai; Li, Zhong-Xiao
2013-12-01
The traditional "dephase and sum" algorithms for over/under data combination estimate the ghost operator by assuming a calm sea surface. However, the real sea surface is typically rough, which invalidates the calm sea surface assumption. Hence, the traditional "dephase and sum" algorithms might produce poor-quality results in rough sea conditions. We propose an adaptive over/under data combination method, which adaptively estimates the amplitude spectrum of the ghost operator from the over/under data, and then over/under data combinations are implemented using the estimated ghost operators. A synthetic single shot gather is used to verify the performance of the proposed method in rough sea surface conditions and a real triple over/under dataset demonstrates the method performance.
An Adaptive Cross-Architecture Combination Method for Graph Traversal
You, Yang; Song, Shuaiwen; Kerbyson, Darren J.
2014-06-18
Breadth-First Search (BFS) is widely used in many real-world applications including computational biology, social networks, and electronic design automation. The combination method, using both top-down and bottom-up techniques, is the most effective BFS approach. However, current combination methods rely on trial-and-error and exhaustive search to locate the optimal switching point, which may cause significant runtime overhead. To solve this problem, we design an adaptive method based on regression analysis to predict an optimal switching point for the combination method at runtime within less than 0.1% of the BFS execution time.
NASA Technical Reports Server (NTRS)
Clendaniel, Richard A.; Lasker, David M.; Minor, Lloyd B.; Shelhamer, M. J. (Principal Investigator)
2002-01-01
Previous work in squirrel monkeys has demonstrated the presence of linear and nonlinear components to the horizontal vestibuloocular reflex (VOR) evoked by high-acceleration rotations. The nonlinear component is seen as a rise in gain with increasing velocity of rotation at frequencies more than 2 Hz (a velocity-dependent gain enhancement). We have shown that there are greater changes in the nonlinear than linear component of the response after spectacle-induced adaptation. The present study was conducted to determine if the two components of the response share a common adaptive process. The gain of the VOR, in the dark, to sinusoidal stimuli at 4 Hz (peak velocities: 20-150 degrees /s) and 10 Hz (peak velocities: 20 and 100 degrees /s) was measured pre- and postadaptation. Adaptation was induced over 4 h with x0.45 minimizing spectacles. Sum-of-sines stimuli were used to induce adaptation, and the parameters of the stimuli were adjusted to invoke only the linear or both linear and nonlinear components of the response. Preadaptation, there was a velocity-dependent gain enhancement at 4 and 10 Hz. In postadaptation with the paradigms that only recruited the linear component, there was a decrease in gain and a persistent velocity-dependent gain enhancement (indicating adaptation of only the linear component). After adaptation with the paradigm designed to recruit both the linear and nonlinear components, there was a decrease in gain and no velocity-dependent gain enhancement (indicating adaptation of both components). There were comparable changes in the response to steps of acceleration. We interpret these results to indicate that separate processes drive the adaptation of the linear and nonlinear components of the response.
Linear magnetic spring and spring/motor combination
NASA Technical Reports Server (NTRS)
Patt, Paul J. (Inventor); Stolfi, Fred R. (Inventor)
1991-01-01
A magnetic spring, or a spring and motor combination, providing a linear spring force characteristic in each direction from a neutral position, in which the spring action may occur for any desired coordinate of a typical orthogonal coordinate system. A set of magnets are disposed, preferably symmetrically about a coordinate axis, poled orthogonally to the desired force direction. A second set of magnets, respectively poled opposite the first set, are arranged on the sprung article. The magnets of one of the sets are spaced a greater distance apart than those of the other, such that an end magnet from each set forms a pair having preferably planar faces parallel to the direction of spring force, the faces being offset so that in a neutral position the outer edge of the closer spaced magnet set is aligned with the inner edge of the greater spaced magnet set. For use as a motor, a coil can be arranged with conductors orthogonal to both the magnet pole directions and the direction of desired spring force, located across from the magnets of one set and fixed with respect to the magnets of the other set. In a cylindrical coordinate system having axial spring force, the magnets are radially poled and motor coils are concentric with the cylinder axis.
A fundamental aeroservoelastic study combining unsteady CFD with adaptive control
NASA Technical Reports Server (NTRS)
Friedmann, P.; Guillot, Damien M.
1994-01-01
This paper describes a two-dimensional aeroservoelastic study in the time domain. The model, which is based on exact inviscid aerodynamics, correctly represents the large amplitude motions and the associated strong shock dynamics in the transonic regime. The aeroservoelastic system consists of a two degree-of-freedom airfoil with a trailing edge control surface. Using first-order actuator dynamics, a digital adaptive controller is applied to provide active flutter suppression. Comparisons between time-responses of the open-loop and closed loop systems show the ability of the trailing edge control surface to suppress non-linear transonic aeroelastic phenomena. A relation between actuator dynamics, sampling time-step and limits on the flap deflection angle to guarantee the effectiveness of the adaptive controller was demonstrated by the results generated.
Language Model Combination and Adaptation Using Weighted Finite State Transducers
NASA Technical Reports Server (NTRS)
Liu, X.; Gales, M. J. F.; Hieronymus, J. L.; Woodland, P. C.
2010-01-01
In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaption may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences
Solitons in combined linear and nonlinear lattice potentials
Sakaguchi, Hidetsugu; Malomed, Boris A.
2010-01-15
We study ordinary solitons and gap solitons (GS's) in the framework of the one-dimensional Gross-Pitaevskii equation (GPE) with a combination of both linear and nonlinear lattice potentials. The main points of the analysis are the effects of (in)commensurability between the lattices, the development of analytical methods, viz., the variational approximation (VA) for narrow ordinary solitons and various forms of the averaging method for broad solitons of both types, and also the study of the mobility of the solitons. Under the direct commensurability (equal periods of the lattices, L{sub lin}=L{sub nonlin}), the family of ordinary solitons is similar to its counterpart in the GPE without external potentials. In the case of the subharmonic commensurability with L{sub lin}=(1/2)L{sub nonlin}, or incommensurability, there is an existence threshold for the ordinary solitons and the scaling relation between their amplitude and width is different from that in the absence of the potentials. GS families demonstrate a bistability unless the direct commensurability takes place. Specific scaling relations are found for them as well. Ordinary solitons can be readily set in motion by kicking. GS's are also mobile and feature inelastic collisions. The analytical approximations are shown to be quite accurate, predicting correct scaling relations for the soliton families in different cases. The stability of the ordinary solitons is fully determined by the Vakhitov-Kolokolov (VK) criterion (i.e., a negative slope in the dependence between the solitons's chemical potential mu and norm N). The stability of GS families obeys an inverted ('anti-VK') criterion dmu/dN>0, which is explained by the approximation based on the averaging method. The present system provides for the unique possibility to check the anti-VK criterion, as mu(N) dependencies for GS's feature turning points except in the case of direct commensurability.
Atrial electrical activity detection using linear combination of 12-lead ECG signals.
Perlman, Or; Katz, Amos; Weissman, Noam; Amit, Guy; Zigel, Yaniv
2014-04-01
ECG analysis is the method for cardiac arrhythmia diagnosis. During the diagnostic process many features should be taken into consideration, such as regularity and atrial activity. Since in some arrhythmias, the atrial electrical activity (AEA) waves are hidden in other waves, and a precise classification from surface ECG is inapplicable, a confirmation diagnosis is usually performed during an invasive procedure. In this paper, we study a "semiautomatic" method for AEA-waves detection using a linear combination of 12-lead ECG signals. This method's objective is to be applicable to a variety of arrhythmias with emphasis given to detect concealed AEA waves. It includes two variations--using maximum energy ratio and a synthetic AEA signal. In the former variation, an energy ratio-based cost function is created and maximized using the gradient ascent method. The latter variation adapted the linear combiner method, when applied on a synthetic signal, combined with surface ECG leads. A study was performed evaluating the AEA-waves detection from 63 patients (nine training, 54 validation) presenting eight arrhythmia types. Averaged sensitivity of 92.21% and averaged precision of 92.08% were achieved compared to the definite diagnosis. In conclusion, the presented method may lead to early and accurate detection of arrhythmias, which will result in a better oriented treatment. PMID:24658228
NASA Technical Reports Server (NTRS)
Balas, M. J.
1985-01-01
Distributed Parameter Systems (DPS), such as systems described by partial differential equations, require infinite-dimensional state space descriptions to correctly model their dynamical behavior. However, any adaptive control algorithm must be finite-dimensional in order to be implemented via on-line digital computers. Finite-dimensional adaptive control of linear DPS requires stability analysis of nonlinear, time-varying, infinite-dimensional systems. The structure of nonadaptive finite-dimensional control of linear DPS is summarized as it relates to the existence of limiting systems for adaptive control. Two candidate schemes for finite-dimensional adaptive control of DPS are described and critical issues in infinite-dimensional stability analysis are discussed, in particular, the invariance principle, center manifold theory, and relationships between input-output and internal stability.
An adaptive observer for single-input single-output linear systems
NASA Technical Reports Server (NTRS)
Carroll, R. L.; Lindorff, D. P.
1972-01-01
It is shown that the full order adaptive observer for single input, single output, observable, continuous, stable, linear differential systems in the absence of a deterministic or random disturbance vector guarantees the vanishing of observation error, regardless of the size of the constant or slowly varying parameter ignorance. The observer parameters are directly changed in a Liapunov adaptive way so as to eventually yield the unknown full order Luenberger observer. The observer poles throughout may be placed freely in the stable region and no derivatives are required in the adaptive law.
STAR adaptation of QR algorithm. [program for solving over-determined systems of linear equations
NASA Technical Reports Server (NTRS)
Shah, S. N.
1981-01-01
The QR algorithm used on a serial computer and executed on the Control Data Corporation 6000 Computer was adapted to execute efficiently on the Control Data STAR-100 computer. How the scalar program was adapted for the STAR-100 and why these adaptations yielded an efficient STAR program is described. Program listings of the old scalar version and the vectorized SL/1 version are presented in the appendices. Execution times for the two versions applied to the same system of linear equations, are compared.
Intelligent control of non-linear dynamical system based on the adaptive neurocontroller
NASA Astrophysics Data System (ADS)
Engel, E.; Kovalev, I. V.; Kobezhicov, V.
2015-10-01
This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.
NASA Technical Reports Server (NTRS)
Nguyen, Nhan
2013-01-01
This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.
On a combined adaptive tetrahedral tracing and edge diffraction model
NASA Astrophysics Data System (ADS)
Hart, Carl R.
A major challenge in architectural acoustics is the unification of diffraction models and geometric acoustics. For example, geometric acoustics is insufficient to quantify the scattering characteristics of acoustic diffusors. Typically the time-independent boundary element method (BEM) is the method of choice. In contrast, time-domain computations are of interest for characterizing both the spatial and temporal scattering characteristics of acoustic diffusors. Hence, a method is sought that predicts acoustic scattering in the time-domain. A prediction method, which combines an advanced image source method and an edge diffraction model, is investigated for the prediction of time-domain scattering. Adaptive tetrahedral tracing is an advanced image source method that generates image sources through an adaptive process. Propagating tetrahedral beams adapt to ensonified geometry mapping the geometric sound field in space and along boundaries. The edge diffraction model interfaces with the adaptive tetrahedral tracing process by the transfer of edge geometry and visibility information. Scattering is quantified as the contribution of secondary sources along a single or multiple interacting edges. Accounting for a finite number of diffraction permutations approximates the scattered sound field. Superposition of the geometric and scattered sound fields results in a synthesized impulse response between a source and a receiver. Evaluation of the prediction technique involves numerical verification and numerical validation. Numerical verification is based upon a comparison with analytic and numerical (BEM) solutions for scattering geometries. Good agreement is shown for the selected scattering geometries. Numerical validation is based upon experimentally determined scattered impulse responses of acoustic diffusors. Experimental data suggests that the predictive model is appropriate for high-frequency predictions. For the experimental determination of the scattered impulse
Adaptive convex combination approach for the identification of improper quaternion processes.
Ujang, Bukhari Che; Jahanchahi, Cyrus; Took, Clive Cheong; Mandic, Danilo P
2014-01-01
Data-adaptive optimal modeling and identification of real-world vector sensor data is provided by combining the fractional tap-length (FT) approach with model order selection in the quaternion domain. To account rigorously for the generality of such processes, both second-order circular (proper) and noncircular (improper), the proposed approach in this paper combines the FT length optimization with both the strictly linear quaternion least mean square (QLMS) and widely linear QLMS (WL-QLMS). A collaborative approach based on QLMS and WL-QLMS is shown to both identify the type of processes (proper or improper) and to track their optimal parameters in real time. Analysis shows that monitoring the evolution of the convex mixing parameter within the collaborative approach allows us to track the improperness in real time. Further insight into the properties of those algorithms is provided by establishing a relationship between the steady-state error and optimal model order. The approach is supported by simulations on model order selection and identification of both strictly linear and widely linear quaternion-valued systems, such as those routinely used in renewable energy (wind) and human-centered computing (biomechanics). PMID:24806652
Fast solution of elliptic partial differential equations using linear combinations of plane waves.
Pérez-Jordá, José M
2016-02-01
Given an arbitrary elliptic partial differential equation (PDE), a procedure for obtaining its solution is proposed based on the method of Ritz: the solution is written as a linear combination of plane waves and the coefficients are obtained by variational minimization. The PDE to be solved is cast as a system of linear equations Ax=b, where the matrix A is not sparse, which prevents the straightforward application of standard iterative methods in order to solve it. This sparseness problem can be circumvented by means of a recursive bisection approach based on the fast Fourier transform, which makes it possible to implement fast versions of some stationary iterative methods (such as Gauss-Seidel) consuming O(NlogN) memory and executing an iteration in O(Nlog(2)N) time, N being the number of plane waves used. In a similar way, fast versions of Krylov subspace methods and multigrid methods can also be implemented. These procedures are tested on Poisson's equation expressed in adaptive coordinates. It is found that the best results are obtained with the GMRES method using a multigrid preconditioner with Gauss-Seidel relaxation steps. PMID:26986436
Fast solution of elliptic partial differential equations using linear combinations of plane waves
NASA Astrophysics Data System (ADS)
Pérez-Jordá, José M.
2016-02-01
Given an arbitrary elliptic partial differential equation (PDE), a procedure for obtaining its solution is proposed based on the method of Ritz: the solution is written as a linear combination of plane waves and the coefficients are obtained by variational minimization. The PDE to be solved is cast as a system of linear equations A x =b , where the matrix A is not sparse, which prevents the straightforward application of standard iterative methods in order to solve it. This sparseness problem can be circumvented by means of a recursive bisection approach based on the fast Fourier transform, which makes it possible to implement fast versions of some stationary iterative methods (such as Gauss-Seidel) consuming O (N logN ) memory and executing an iteration in O (N log2N ) time, N being the number of plane waves used. In a similar way, fast versions of Krylov subspace methods and multigrid methods can also be implemented. These procedures are tested on Poisson's equation expressed in adaptive coordinates. It is found that the best results are obtained with the GMRES method using a multigrid preconditioner with Gauss-Seidel relaxation steps.
NASA Astrophysics Data System (ADS)
Kun, David William
Unmanned aircraft systems (UASs) are gaining popularity in civil and commercial applications as their lightweight on-board computers become more powerful and affordable, their power storage devices improve, and the Federal Aviation Administration addresses the legal and safety concerns of integrating UASs in the national airspace. Consequently, many researchers are pursuing novel methods to control UASs in order to improve their capabilities, dependability, and safety assurance. The nonlinear control approach is a common choice as it offers several benefits for these highly nonlinear aerospace systems (e.g., the quadrotor). First, the controller design is physically intuitive and is derived from well known dynamic equations. Second, the final control law is valid in a larger region of operation, including far from the equilibrium states. And third, the procedure is largely methodical, requiring less expertise with gain tuning, which can be arduous for a novice engineer. Considering these facts, this thesis proposes a nonlinear controller design method that combines the advantages of adaptive robust control (ARC) with the powerful design tools of linear matrix inequalities (LMI). The ARC-LMI controller is designed with a discontinuous projection-based adaptation law, and guarantees a prescribed transient and steady state tracking performance for uncertain systems in the presence of matched disturbances. The norm of the tracking error is bounded by a known function that depends on the controller design parameters in a known form. Furthermore, the LMI-based part of the controller ensures the stability of the system while overcoming polytopic uncertainties, and minimizes the control effort. This can reduce the number of parameters that require adaptation, and helps to avoid control input saturation. These desirable characteristics make the ARC-LMI control algorithm well suited for the quadrotor UAS, which may have unknown parameters and may encounter external
Combining text clustering and retrieval for corpus adaptation
NASA Astrophysics Data System (ADS)
He, Feng; Ding, Xiaoqing
2007-01-01
The application-relevant text data are very useful in various natural language applications. Using them can achieve significantly better performance for vocabulary selection, language modeling, which are widely employed in automatic speech recognition, intelligent input method etc. In some situations, however, the relevant data is hard to collect. Thus, the scarcity of application-relevant training text brings difficulty upon these natural language processing. In this paper, only using a small set of application specific text, by combining unsupervised text clustering and text retrieval techniques, the proposed approach can find the relevant text from unorganized large scale corpus, thereby, adapt training corpus towards the application area of interest. We use the performance of n-gram statistical language model, which is trained from the text retrieved and test on the application-specific text, to evaluate the relevance of the text acquired, accordingly, to validate the effectiveness of our corpus adaptation approach. The language models trained from the ranked text bundles present well discriminated perplexities on the application-specific text. The preliminary experiments on short message text and unorganized large corpus demonstrate the performance of the proposed methods.
Digital redesign of the decentralised adaptive tracker for linear large-scale systems
NASA Astrophysics Data System (ADS)
Lin, Ming-Hong; Sheng-Hong Tsai, Jason; Chen, Chia-Wei; Guo, Shu-Mei; Chu, Che-An
2010-02-01
A novel digital redesign of the analogue model-reference-based decentralized adaptive tracker is proposed for the sampled-data large scale system consisting of N interconnected linear subsystems, so that the system output will follow any trajectory specified at sampling instant which may not be presented by the analytic reference initially, and shows that the proposed decentralized controller induces a good robustness on the decoupling of the closed-loop controlled system. The adaptation of the analogue controller gain is derived by using the model-reference adaptive control theory based on Lyapunov's method. In this article, it is shown that using the sampled-data decentralized adaptive control system it is theoretically possible to asymptotically track the desired output with a desired performance. It is assumed that all the controllers share their prior information and the principal result is derived when they cooperate implicitly. Based on the prediction-based digital redesign methodology, the optimal digital redesigned tracker for the sampled-data decentralised adaptive control systems is newly proposed. An illustrative example of interconnected linear system is presented to demonstrate the effectiveness of the proposed design methodology.
Learning of Action Through Adaptive Combination of Motor Primitives
Thoroughman, Kurt A.; Shadmehr, Reza
2008-01-01
Understanding how the brain constructs movements remains a fundamental challenge in neuroscience. The brain may control complex movements through flexible combination of motor primitives1, where each primitive is an element of computation in the sensorimotor map that transforms desired limb trajectories into motor commands. Theoretical studies have shown that a system’s ability to learn actions depends on the shape of its primitives2. Using a time-series analysis of error patterns, here we find evidence that humans learn dynamics of reaching movements through flexible combination of primitives that have Gaussian-like tuning functions encoding hand velocity. The wide tuning of the inferred primitives predicts limitations on the brain’s ability to represent viscous dynamics. We find close agreement between the predicted limitations and subjects’ adaptation to novel force fields. The mathematical properties of the derived primitives resemble the tuning curves of Purkinje cells in the cerebellum. Activity of these cells may encode primitives that underlie learning of dynamics. PMID:11048720
Accuracy requirements of optical linear algebra processors in adaptive optics imaging systems
NASA Technical Reports Server (NTRS)
Downie, John D.; Goodman, Joseph W.
1989-01-01
The accuracy requirements of optical processors in adaptive optics systems are determined by estimating the required accuracy in a general optical linear algebra processor (OLAP) that results in a smaller average residual aberration than that achieved with a conventional electronic digital processor with some specific computation speed. Special attention is given to an error analysis of a general OLAP with regard to the residual aberration that is created in an adaptive mirror system by the inaccuracies of the processor, and to the effect of computational speed of an electronic processor on the correction. Results are presented on the ability of an OLAP to compete with a digital processor in various situations.
NASA Astrophysics Data System (ADS)
Fujii, Kensaku; Aoki, Ryo; Muneyasu, Mitsuji
This paper proposes an adaptive algorithm for identifying unknown systems containing nonlinear amplitude characteristics. Usually, the nonlinearity is so small as to be negligible. However, in low cost systems, such as acoustic echo canceller using a small loudspeaker, the nonlinearity deteriorates the performance of the identification. Several methods preventing the deterioration, polynomial or Volterra series approximations, have been hence proposed and studied. However, the conventional methods require high processing cost. In this paper, we propose a method approximating the nonlinear characteristics with a piecewise linear curve and show using computer simulations that the performance can be extremely improved. The proposed method can also reduce the processing cost to only about twice that of the linear adaptive filter system.
Non-linear adaptive sliding mode switching control with average dwell-time
NASA Astrophysics Data System (ADS)
Yu, Lei; Zhang, Maoqing; Fei, Shumin
2013-03-01
In this article, an adaptive integral sliding mode control scheme is addressed for switched non-linear systems in the presence of model uncertainties and external disturbances. The control law includes two parts: a slide mode controller for the reduced model of the plant and a compensation controller to deal with the non-linear systems with parameter uncertainties. The adaptive updated laws have been derived from the switched multiple Lyapunov function method, also an admissible switching signal with average dwell-time technique is given. The simplicity of the proposed control scheme facilitates its implementation and the overall control scheme guarantees the global asymptotic stability in the Lyapunov sense such that the sliding surface of the control system is well reached. Simulation results are presented to demonstrate the effectiveness and the feasibility of the proposed approach.
A novel adaptive multi-resolution combined watermarking algorithm
NASA Astrophysics Data System (ADS)
Feng, Gui; Lin, QiWei
2008-04-01
The rapid development of IT and WWW technique, causing person frequently confronts with various kinds of authorized identification problem, especially the copyright problem of digital products. The digital watermarking technique was emerged as one kind of solutions. The balance between robustness and imperceptibility is always the object sought by related researchers. In order to settle the problem of robustness and imperceptibility, a novel adaptive multi-resolution combined digital image watermarking algorithm was proposed in this paper. In the proposed algorithm, we first decompose the watermark into several sub-bands, and according to its significance to embed the sub-band to different DWT coefficient of the carrier image. While embedding, the HVS was considered. So under the precondition of keeping the quality of image, the larger capacity of watermark can be embedding. The experimental results have shown that the proposed algorithm has better performance in the aspects of robustness and security. And with the same visual quality, the technique has larger capacity. So the unification of robustness and imperceptibility was achieved.
Combining biomarkers linearly and nonlinearly for classification using the area under the ROC curve.
Fong, Youyi; Yin, Shuxin; Huang, Ying
2016-09-20
In biomedical studies, it is often of interest to classify/predict a subject's disease status based on a variety of biomarker measurements. A commonly used classification criterion is based on area under the receiver operating characteristic curve (AUC). Many methods have been proposed to optimize approximated empirical AUC criteria, but there are two limitations to the existing methods. First, most methods are only designed to find the best linear combination of biomarkers, which may not perform well when there is strong nonlinearity in the data. Second, many existing linear combination methods use gradient-based algorithms to find the best marker combination, which often result in suboptimal local solutions. In this paper, we address these two problems by proposing a new kernel-based AUC optimization method called ramp AUC (RAUC). This method approximates the empirical AUC loss function with a ramp function and finds the best combination by a difference of convex functions algorithm. We show that as a linear combination method, RAUC leads to a consistent and asymptotically normal estimator of the linear marker combination when the data are generated from a semiparametric generalized linear model, just as the smoothed AUC method. Through simulation studies and real data examples, we demonstrate that RAUC outperforms smooth AUC in finding the best linear marker combinations, and can successfully capture nonlinear pattern in the data to achieve better classification performance. We illustrate our method with a dataset from a recent HIV vaccine trial. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27058981
An analytical study on the carrier-phase linear combinations for triple-frequency GNSS
NASA Astrophysics Data System (ADS)
Li, Jinlong; Yang, Yuanxi; He, Haibo; Guo, Hairong
2016-08-01
The linear combinations of multi-frequency carrier-phase measurements for Global Navigation Satellite System (GNSS) are greatly beneficial to improving the performance of ambiguity resolution (AR), cycle slip correction as well as precise positioning. In this contribution, the existing definitions of the carrier-phase linear combination are reviewed and the integer property of the resulting ambiguity of the phase linear combinations is examined. The general analytical method for solving the optimal integer linear combinations for all triple-frequency GNSS is presented. Three refined triple-frequency integer combinations solely determined by the frequency values are introduced, which are the ionosphere-free (IF) combination that the Sum of its integer coefficients equal to 0 (IFS0), the geometry-free (GF) combination that the Sum of its integer coefficients equal to 0 (GFS0) and the geometry-free and ionosphere-free (GFIF) combination. Besides, the optimal GF, IF, extra-wide lane and ionosphere-reduced integer combinations for GPS and BDS are solved exhaustively by the presented method. Their potential applications in cycle slip detection, AR as well as precise positioning are discussed. At last, a more straightforward GF and IF AR scheme than the existing method is presented based on the GFIF integer combination.
Speaker adaptation of HMMs using evolutionary strategy-based linear regression
NASA Astrophysics Data System (ADS)
Selouani, Sid-Ahmed; O'Shaughnessy, Douglas
2002-05-01
A new framework for speaker adaptation of continuous-density hidden Markov models (HMMs) is introduced. It aims to improve the robustness of speech recognizers by adapting HMM parameters to new conditions (e.g., from new speakers). It describes an optimization technique using an evolutionary strategy for linear regression-based spectral transformation. In classical iterative maximum likelihood linear regression (MLLR), a global transform matrix is estimated to make a general model better match particular target conditions. To permit adaptation on a small amount of data, a regression tree classification is performed. However, an important drawback of MLLR is that the number of regression classes is fixed. The new approach allows the degree of freedom of the global transform to be implicitly variable, as the evolutionary optimization permits the survival of only active classes. The fitness function is evaluated by the phoneme correctness through the evolution steps. The implementation requirements such as chromosome representation, selection function, genetic operators, and evaluation function have been chosen in order to lend more reliability to the global transformation matrix. Triphone experiments used the TIMIT and ARPA-RM1 databases. For new speakers, the new technique achieves 8 percent fewer word errors than the basic MLLR method.
Optimal linear combinations of multiple diagnostic biomarkers based on Youden index.
Yin, Jingjing; Tian, Lili
2014-04-15
In practice, usually multiple biomarkers are measured on the same subject for disease diagnosis. Combining these biomarkers into a single score could improve diagnostic accuracy. Many researchers have addressed the problem of finding the optimal linear combination based on maximizing the area under ROC curve (AUC). Actually, such combined score might have less than optimal property at the diagnostic threshold. In this paper, we propose the idea of using Youden index as an objective function for searching the optimal linear combination. The combined score directly achieves the maximum overall correct classification rate at the diagnostic threshold corresponding to Youden index; in other words, it is the optimal linear combination score for making the disease diagnosis. We present both empirical and numerical searching methods for the optimal linear combination. We carry out extensive simulation study to investigate the performance of the proposed methods. Additionally, we empirically compare the optimal overall classification rates between the proposed combination based on Youden index and the traditional one based on AUC and demonstrate a significant gain in diagnostic accuracy for the proposed combination. In the end, we apply the proposed methods to a real data set. PMID:24311111
An adaptive noise cancelling system used for beam control at the Stanford Linear Accelerator Center
Himel, T.; Allison, S.; Grossberg, P.; Hendrickson, L.; Sass, R.; Shoaee, H.
1993-06-01
The SLAC Linear Collider now has a total of twenty-four beam-steering feedback loops used to keep the electron and positron beams on their desired trajectories. Seven of these loops measure and control the same beam as it proceeds down the linac through the arcs to the final focus. Ideally by each loop should correct only for disturbances that occur between it and the immediate upstream loop. In fact, in the original system each loop corrected for all upstream disturbances. This resulted in undesirable over-correction and ringing. We added MIMO (Multiple Input Multiple Output) adaptive noise cancellers to separate the signal we wish to correct from disturbances further upstream. This adaptive control improved performance in the 1992 run.
Ayati, Moosa; Alwan, Mohamad; Liu Xinzhi; Khaloozadeh, Hamid
2011-11-30
State observation (estimation) is a very important issue in system analysis and control. This paper develops a new observer called Stochastic Adaptive Impulsive Observer (SAIO) for the state estimation of impulsive systems. The proposed observer is applicable to linear and nonlinear stochastic impulsive systems. In addition, the effect of parametric uncertainty is considered and unknown parameters of the system are estimated by suitable adaptation laws. Impulsive system theory, particularly stochastic Lyapunov-like function, is used to analyze the stability and convergence of the state estimations. The main advantages of the proposed observer are: 1) it gives continuous estimation from discrete time measurements of the system output, and 2) it is useful for state estimation when continuous measurements are impossible or expensive. Simulation results show the effectiveness of the proposed observer and we believe that it has many applications in control and estimation theories.
Adaptive H∞ nonlinear velocity tracking using RBFNN for linear DC brushless motor
NASA Astrophysics Data System (ADS)
Tsai, Ching-Chih; Chan, Cheng-Kain; Li, Yi Yu
2012-01-01
This article presents an adaptive H ∞ nonlinear velocity control for a linear DC brushless motor. A simplified model of this motor with friction is briefly recalled. The friction dynamics is described by the Lu Gre model and the online tuning radial basis function neural network (RBFNN) is used to parameterise the nonlinear friction function and un-modelled errors. An adaptive nonlinear H ∞ control method is then proposed to achieve velocity tracking, by assuming that the upper bounds of the ripple force, the changeable load and the nonlinear friction can be learned by the RBFNN. The closed-loop system is proven to be uniformly bounded using the Lyapunov stability theory. The feasibility and the efficacy of the proposed control are exemplified by conducting two velocity tracking experiments.
Combining and connecting linear, multi-input, multi-output subsystem models
NASA Technical Reports Server (NTRS)
Duke, E. L.
1986-01-01
The mathematical background for combining and connecting linear, multi-input, multi-output subsystem models into an overall system model is provided. Several examples of subsystem configurations are examined in detail. A description of a MATRIX (sub x) command file to aid in the process of combining and connecting these subsystem models is contained.
NASA Technical Reports Server (NTRS)
Balas, M. J.; Kaufman, H.; Wen, J.
1985-01-01
A command generator tracker approach to model following contol of linear distributed parameter systems (DPS) whose dynamics are described on infinite dimensional Hilbert spaces is presented. This method generates finite dimensional controllers capable of exponentially stable tracking of the reference trajectories when certain ideal trajectories are known to exist for the open loop DPS; we present conditions for the existence of these ideal trajectories. An adaptive version of this type of controller is also presented and shown to achieve (in some cases, asymptotically) stable finite dimensional control of the infinite dimensional DPS.
Combining Adaptive Hypermedia with Project and Case-Based Learning
ERIC Educational Resources Information Center
Papanikolaou, Kyparisia; Grigoriadou, Maria
2009-01-01
In this article we investigate the design of educational hypermedia based on constructivist learning theories. According to the principles of project and case-based learning we present the design rational of an Adaptive Educational Hypermedia system prototype named MyProject; learners working with MyProject undertake a project and the system…
A covariance-adaptive approach for regularized inversion in linear models
NASA Astrophysics Data System (ADS)
Kotsakis, Christopher
2007-11-01
The optimal inversion of a linear model under the presence of additive random noise in the input data is a typical problem in many geodetic and geophysical applications. Various methods have been developed and applied for the solution of this problem, ranging from the classic principle of least-squares (LS) estimation to other more complex inversion techniques such as the Tikhonov-Philips regularization, truncated singular value decomposition, generalized ridge regression, numerical iterative methods (Landweber, conjugate gradient) and others. In this paper, a new type of optimal parameter estimator for the inversion of a linear model is presented. The proposed methodology is based on a linear transformation of the classic LS estimator and it satisfies two basic criteria. First, it provides a solution for the model parameters that is optimally fitted (in an average quadratic sense) to the classic LS parameter solution. Second, it complies with an external user-dependent constraint that specifies a priori the error covariance (CV) matrix of the estimated model parameters. The formulation of this constrained estimator offers a unified framework for the description of many regularization techniques that are systematically used in geodetic inverse problems, particularly for those methods that correspond to an eigenvalue filtering of the ill-conditioned normal matrix in the underlying linear model. Our study lies on the fact that it adds an alternative perspective on the statistical properties and the regularization mechanism of many inversion techniques commonly used in geodesy and geophysics, by interpreting them as a family of `CV-adaptive' parameter estimators that obey a common optimal criterion and differ only on the pre-selected form of their error CV matrix under a fixed model design.
Linear-scaling symmetry-adapted perturbation theory with scaled dispersion
Maurer, Simon A.; Beer, Matthias; Lambrecht, Daniel S.; Ochsenfeld, Christian
2013-11-14
We present a linear-scaling symmetry-adapted perturbation theory (SAPT) method that is based on an atomic orbital (AO) formulation of zeroth-order SAPT (SAPT0). The non-dispersive terms are realized with linear-scaling cost using both the continuous fast multipole method (CFMM) and the linear exchange (LinK) approach for integral contractions as well as our efficient Laplace-based coupled-perturbed self-consistent field method (DL-CPSCF) for evaluating response densities. The reformulation of the dispersion term is based on our linear-scaling AO Møller-Plesset second-order perturbation theory (AO-MP2) method, that uses our recently introduced QQR-type screening [S. A. Maurer, D. S. Lambrecht, J. Kussmann, and C. Ochsenfeld, J. Chem. Phys. 138, 014101 (2013)] for preselecting numerically significant energy contributions. Similar to scaled opposite-spin MP2, we neglect the exchange-dispersion term in SAPT and introduce a scaling factor for the dispersion term, which compensates for the error and at the same time accounts for basis set incompleteness effects and intramonomer correlation. We show in extensive benchmark calculations that the new scaled-dispersion (sd-)SAPT0 approach provides reliable results for small and large interacting systems where the results with a small 6-31G** basis are roughly comparable to supermolecular MP2 calculations in a triple-zeta basis. The performance of our method is demonstrated with timings on cellulose fragments, DNA systems, and cutouts of a protein-ligand complex with up to 1100 atoms on a single computer core.
Radiative-neutron-capture gamma-ray analysis by a linear combination technique
Tanner, A.B.; Bhargava, R.C.; Senftle, F.E.; Brinkerhoff, J.M.
1972-01-01
The linear combination technique, when applied to a gamma-ray spectrum, gives a single number indicative of the extent to which the spectral lines of a sought element are present in a complex spectrum. Spectra are taken of the sought element and of various other substances whose spectra interfere with that of the sought element. A weighting function is then computed for application to spectra of unknown materials. The technique was used to determine calcium by radiative-neutron-capture gamma-ray analysis in the presence of interfering elements, notably titanium, and the results were compared with those for two popular methods of peak area integration. Although linearity of response was similar for the methods, the linear combination technique was much better at rejecting interferences. For analyses involving mixtures of unknown composition the technique consequently offers improved sensitivity. ?? 1972.
Rehault, Julien; Helbing, Jan; Zanirato, Vinicio; Olivucci, Massimo
2011-03-28
We demonstrate strong amplification of polarization-sensitive transient IR signals using a pseudo-null crossed polarizer technique first proposed by Keston and Lospalluto [Fed. Proc. 10, 207 (1951)] and applied for nanosecond flash photolysis in the visible by Che et al. [Chem. Phys. Lett. 224, 145 (1994)]. We adapted the technique to ultrafast pulsed laser spectroscopy in the infrared using photoelastic modulators, which allow us to measure amplified linear dichroism at kilohertz repetition rates. The method was applied to a photoswitch of the N-alkylated Schiff base family in order to demonstrate its potential of strongly enhancing sensitivity and signal to noise in ultrafast transient IR experiments, to simplify spectra and to determine intramolecular transition dipole orientations.
NASA Astrophysics Data System (ADS)
Réhault, Julien; Zanirato, Vinicio; Olivucci, Massimo; Helbing, Jan
2011-03-01
We demonstrate strong amplification of polarization-sensitive transient IR signals using a pseudo-null crossed polarizer technique first proposed by Keston and Lospalluto [Fed. Proc. 10, 207 (1951)] and applied for nanosecond flash photolysis in the visible by Che et al. [Chem. Phys. Lett. 224, 145 (1994)]. We adapted the technique to ultrafast pulsed laser spectroscopy in the infrared using photoelastic modulators, which allow us to measure amplified linear dichroism at kilohertz repetition rates. The method was applied to a photoswitch of the N-alkylated Schiff base family in order to demonstrate its potential of strongly enhancing sensitivity and signal to noise in ultrafast transient IR experiments, to simplify spectra and to determine intramolecular transition dipole orientations.
Exploring two-spin internal linear combinations for the recovery of the CMB polarization
NASA Astrophysics Data System (ADS)
Fernández-Cobos, R.; Marcos-Caballero, A.; Vielva, P.; Martínez-González, E.; Barreiro, R. B.
2016-06-01
We present a methodology to recover cosmic microwave background (CMB) polarization in which the quantity P = Q + iU is linearly combined at different frequencies using complex coefficients. This is the most general linear combination of the Q and U Stokes parameters which preserves the physical coherence of the residual contribution on the CMB estimation. The approach is applied to the internal linear combination (ILC) and the internal template fitting (ITF) methodologies. The variance of P of the resulting map is minimized to compute the coefficients of the linear combination. One of the key aspects of this procedure is that it serves to account for a global frequency-dependent shift of the polarization phase. Although in the standard case, in which no global E-B transference depending on frequency is expected in the foreground components, minimizing <|P|2> is similar to minimizing
Optimization of an adaptive SPECT system with the scanning linear estimator
NASA Astrophysics Data System (ADS)
Ghanbari, Nasrin; Clarkson, Eric; Kupinski, Matthew A.; Li, Xin
2015-08-01
The adaptive single-photon emission computed tomography (SPECT) system studied here acquires an initial scout image to obtain preliminary information about the object. Then the configuration is adjusted by selecting the size of the pinhole and the magnification that optimize system performance on an ensemble of virtual objects generated to be consistent with the scout data. In this study the object is a lumpy background that contains a Gaussian signal with a variable width and amplitude. The virtual objects in the ensemble are imaged by all of the available configurations and the subsequent images are evaluated with the scanning linear estimator to obtain an estimate of the signal width and amplitude. The ensemble mean squared error (EMSE) on the virtual ensemble between the estimated and the true parameters serves as the performance figure of merit for selecting the optimum configuration. The results indicate that variability in the original object background, noise and signal parameters leads to a specific optimum configuration in each case. A statistical study carried out for a number of objects show that the adaptive system on average performs better than its nonadaptive counterpart.
Linearity enhancement of TVGA based on adaptive sweep optimisation in monostatic radar receiver
NASA Astrophysics Data System (ADS)
Almslmany, Amir; Wang, Caiyun; Cao, Qunsheng
2016-08-01
The limited input dynamic power range of the radar receiver and the power loss due to the targets' ranges are two potential problems in the radar receivers. This paper proposes a model based on the time-varying gain amplifier (TVGA) to compensate the power loss from the targets' ranges, and using the negative impedance compensation technique to enhance the TVGA linearity based on Volterra series. The simulation has been done based on adaptive sweep optimisation (ASO) using advanced design system (ADS) and Matlab. It shows that the suppression of the third-order intermodulation products (IMR3) was carried out for two-tone test, the high-gain accuracy improved by 3 dB, and the high linearity IMR3 improved by 14 dB. The monostatic radar system was tested to detect three targets at different ranges and to compare its probability of detection with the prior models; the results show that the probability of detection has been increased for ASO/TVGA.
NASA Astrophysics Data System (ADS)
Meng, Fanwei; Liu, Chengying; Li, Zhijun; Wang, Liping
2013-01-01
Due to low damping ratio, flat permanent magnet linear synchronous motor's vibration is difficult to be damped and the accuracy is limited. The vibration suppressing results are not good enough in the existing research because only the longitudinal direction vibration is considered while the normal direction vibration is neglected. The parameters of the direct-axis current controller are set to be the same as those of the quadrature-axis current controller commonly. This causes contradiction between signal noise and response. To suppress the vibration, the electromagnetic force model of the flat permanent magnet synchronous linear motor is formulated first. Through the analysis of the effect that direct-axis current noise and quadrature-axis current noise have on both direction vibration, it can be declared that the conclusion that longitudinal direction vibration is only related to the quadrature-axis current noise while the normal direction vibration is related to both the quadrature-axis current noise and direct-axis current noise. Then, the simulation test on current loop with a low-pass filter is conducted and the results show that the low-pass filter can not suppress the vibration but makes the vibration more severe. So a vibration suppressing strategy that the proportional gain of direct-axis current controller adapted according to quadrature-axis reference current is proposed. This control strategy can suppress motor vibration by suppressing direct-axis current noise. The experiments results about the effect of K p and T i on normal direction vibration, longitudinal vibration and the position step response show that this strategy suppresses vibration effectively while the motor's motion performance is not affected. The maximum reduction of vibration can be up to 40%. In addition, current test under rated load condition is also conducted and the results show that the control strategy can avoid the conflict between the direct-axis current and the quadrature
Combined conjugate and pupil adaptive optics in widefield microscopy
NASA Astrophysics Data System (ADS)
Beaulieu, Devin R.
Traditionally, adaptive optics (AO) systems for microscopy have focused on AO at the pupil plane, however this produces poor performance in samples with both spatially-variant aberrations, such as non-flat sample interfaces, and spatially-invariant aberrations, such as spherical aberration due to a difference between the sample index of refraction and the sample for which the objective was designed. Here, we demonstrate well-corrected, wide field-of-view (FOV) microscopy by simultaneously correcting the two types of aberrations using two AO loops. Such an approach is necessary in wide-field applications where both types of aberration may be present, as each AO loop can only fully correct one type of aberration. Wide FOV corrections are demonstrated in a trans-illumination microscope equipped with two deformable mirrors (DMs), using a partitioned aperture wavefront (PAW) sensor to directly control the DM conjugated to the sample interface and a sensor-less genetic algorithm to control the DM conjugated to the objective's pupil.
Adaptive spatial combining for passive time-reversed communications.
Gomes, João; Silva, António; Jesus, Sérgio
2008-08-01
Passive time reversal has aroused considerable interest in underwater communications as a computationally inexpensive means of mitigating the intersymbol interference introduced by the channel using a receiver array. In this paper the basic technique is extended by adaptively weighting sensor contributions to partially compensate for degraded focusing due to mismatch between the assumed and actual medium impulse responses. Two algorithms are proposed, one of which restores constructive interference between sensors, and the other one minimizes the output residual as in widely used equalization schemes. These are compared with plain time reversal and variants that employ postequalization and channel tracking. They are shown to improve the residual error and temporal stability of basic time reversal with very little added complexity. Results are presented for data collected in a passive time-reversal experiment that was conducted during the MREA'04 sea trial. In that experiment a single acoustic projector generated a 24-PSK (phase-shift keyed) stream at 200400 baud, modulated at 3.6 kHz, and received at a range of about 2 km on a sparse vertical array with eight hydrophones. The data were found to exhibit significant Doppler scaling, and a resampling-based preprocessing method is also proposed here to compensate for that scaling. PMID:18681595
A new adaptation of linear reservoir models in parallel sets to assess actual hydrological events
NASA Astrophysics Data System (ADS)
Mateo Lázaro, Jesús; Sánchez Navarro, José Ángel; García Gil, Alejandro; Edo Romero, Vanesa
2015-05-01
A methodology based on Parallel Linear Reservoir (PLR) models is presented. To carry it out has been implemented within the software SHEE (Simulation of Hydrological Extreme Events), which is a tool for the analysis of hydrological processes in catchments with the management and display of DEM and datasets. The algorithms of the models pass throughout the cells and drainage network, by means of the Watershed Traversal Algorithm (WTA) that runs the entire drainage network of a basin in both directions, upwards and downwards, which is ideal for incorporating the models of the hydrological processes of the basins into its structure. The WTA methodology is combined with another one based on models of Parallel Linear Reservoirs (PLR) whose main qualities include: (1) the models are defined by observing the recession curves of actual hydrographs, i.e., the watershed actual responses; (2) the models serve as a way to simulate the routing through the watershed and its different reservoirs; and (3) the models allow calculating the water balance, which is essential to the study of actual events in the watershed. A complete hydrometeorological event needs the combination of several models, each one of which represents a hydrological process. The PLR model is a routing model, but it also contributes to the adjustment of other models (e.g., the rainfall-runoff model) and allows establishing a distributed model of effective rainfall for an actual event occurred in a basin. On the other hand, the proposed formulation solves the rainfall distribution problem for each deposit in the reservoir combination models.
Lei, Yuming; Bao, Shancheng; Wang, Jinsung
2016-09-01
Sensorimotor adaptation can be induced by action observation, and also by passive training. Here, we investigated the effect of a protocol that combined action observation and passive training on visuomotor adaptation, by comparing it with the effect of action observation or passive training alone. Subjects were divided into five conditions during the training session: (1) action observation, in which the subjects watched a video of a model who adapted to a novel visuomotor rotation; (2) proprioceptive training, in which the subject's arm was moved passively to target locations that were associated with desired trajectories; (3) combined training, in which the subjects watched the video of a model during a half of the session and experienced passive movements during the other half; (4) active training, in which the subjects adapted actively to the rotation; and (5) a control condition, in which the subjects did not perform any task. Following that session, all subjects adapted to the same visuomotor rotation. Results showed that the subjects in the combined training condition adapted to the rotation significantly better than those in the observation or proprioceptive training condition, although their performance was not as good as that of those who adapted actively. These findings suggest that although a protocol that combines action observation and passive training consists of all the processes involved in active training (error detection and correction, effector-specific and proprioceptively based reaching movements), these processes in that protocol may work differently as compared to a protocol in which the same processes are engaged actively. PMID:27298007
Kang, Le; Xiong, Chengjie; Crane, Paul; Tian, Lili
2015-01-01
Many researchers have addressed the problem of finding the optimal linear combination of biomarkers to maximize the area under receiver operating characteristic (ROC) curves for scenarios with binary disease status. In practice, many disease processes such as Alzheimer can be naturally classified into three diagnostic categories such as normal, mild cognitive impairment and Alzheimer’s disease (AD), and for such diseases the volume under the ROC surface (VUS) is the most commonly used index of diagnostic accuracy. In this article, we propose a few parametric and nonparametric approaches to address the problem of finding the optimal linear combination to maximize the VUS. We carried out simulation studies to investigate the performance of the proposed methods. We apply all of the investigated approaches to a real data set from a cohort study in early stage AD. PMID:22865796
Orthogonality, Lommel integrals and cross product zeros of linear combinations of Bessel functions.
Ziener, Christian H; Kurz, Felix T; Buschle, Lukas R; Kampf, Thomas
2015-01-01
The cylindrical Bessel differential equation and the spherical Bessel differential equation in the interval [Formula: see text] with Neumann boundary conditions are considered. The eigenfunctions are linear combinations of the Bessel function [Formula: see text] or linear combinations of the spherical Bessel functions [Formula: see text]. The orthogonality relations with analytical expressions for the normalization constant are given. Explicit expressions for the Lommel integrals in terms of Lommel functions are derived. The cross product zeros [Formula: see text] and [Formula: see text] are considered in the complex plane for real as well as complex values of the index [Formula: see text] and approximations for the exceptional zero [Formula: see text] are obtained. A numerical scheme based on the discretization of the two-dimensional and three-dimensional Laplace operator with Neumann boundary conditions is presented. Explicit representations of the radial part of the Laplace operator in form of a tridiagonal matrix allow the simple computation of the cross product zeros. PMID:26251774
Shang, Shang; Bai, Jing; Song, Xiaolei; Wang, Hongkai; Lau, Jaclyn
2007-01-01
Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based on a restart strategy, in order to take advantage of the two kinds of conjugate gradient methods and compensate for the disadvantages. A quadratic penalty method is adopted to gain a nonnegative constraint and reduce the illposedness of the problem. Simulation studies show that the presented algorithm is accurate, stable, and fast. It has a better performance than the conventional conjugate gradient-based reconstruction algorithms. It offers an effective approach to reconstruct fluorochrome information for FMT. PMID:18354740
High-power spectral beam combining of linearly polarized Tm:fiber lasers.
Shah, Lawrence; Sims, R Andrew; Kadwani, Pankaj; Willis, Christina C C; Bradford, Joshua B; Sincore, Alex; Richardson, Martin
2015-02-01
To date, high-power scaling of Tm:fiber lasers has been accomplished by maximizing the power from a single fiber aperture. In this work, we investigate power scaling by spectral beam combination of three linearly polarized Tm:fiber MOPA lasers using dielectric mirrors with a steep transition from highly reflective to highly transmissive that enable a minimum wavelength separation of 6 nm between individual laser channels within the wavelength range from 2030 to 2050 nm. Maximum output power is 253 W with M(2)<2, ultimately limited by thermal lensing in the beam combining elements. PMID:25967785
A combined lift and propulsion system of a steel plate by transverse flux linear induction motors
Hayashiya, H.; Ohsaki, H.; Masada, E.
1999-09-01
To realize a non-contacting conveyance of a steel plate, a combined lift and propulsion system of a steel plate by transverse flux linear induction motors (LIMs) is proposed. By introducing the DC biased AC feeding to the LIM< a steel plate is supported stably and efficiently. In this paper, after showing the advantages of the system, the magnetic levitation experiments are carried out to investigate the feasibility of the system.
On-chip power-combining techniques for watt-level linear power amplifiers in 0.18 μm CMOS
NASA Astrophysics Data System (ADS)
Zhixiong, Ren; Kefeng, Zhang; Lanqi, Liu; Cong, Li; Xiaofei, Chen; Dongsheng, Liu; Zhenglin, Liu; Xuecheng, Zou
2015-09-01
Three linear CMOS power amplifiers (PAs) with high output power (more than watt-level output power) for high data-rate mobile applications are introduced. To realize watt-level output power, there are two 2.4 GHz PAs using an on-chip parallel combining transformer (PCT) and one 1.95 GHz PA using an on-chip series combining transformer (SCT) to combine output signals of multiple power stages. Furthermore, some linearization techniques including adaptive bias, diode linearizer, multi-gated transistors (MGTR) and the second harmonic control are applied in these PAs. Using the proposed power combiner, these three PAs are designed and fabricated in TSMC 0.18 μm RFCMOS process. According to the measurement results, the proposed two linear 2.4 GHz PAs achieve a gain of 33.2 dB and 34.3 dB, a maximum output power of 30.7 dBm and 29.4 dBm, with 29% and 31.3% of peak PAE, respectively. According to the simulation results, the presented linear 1.95 GHz PA achieves a gain of 37.5 dB, a maximum output power of 34.3 dBm with 36.3% of peak PAE. Project supported by the National Natural Science Foundation of China (No. 61076030).
Mixed linear model approach adapted for genome-wide association studies
Zhang, Zhiwu; Ersoz, Elhan; Lai, Chao-Qiang; Todhunter, Rory J; Tiwari, Hemant K; Gore, Michael A; Bradbury, Peter J; Yu, Jianming; Arnett, Donna K; Ordovas, Jose M; Buckler, Edward S
2010-01-01
Mixed linear model (MLM) methods have proven useful in controlling for population structure and relatedness within genome-wide association studies. However, MLM-based methods can be computationally challenging for large datasets. We report a compression approach, called ‘compressed MLM’, that decreases the effective sample size of such datasets by clustering individuals into groups. We also present a complementary approach, ‘population parameters previously determined’ (P3D), that eliminates the need to re-compute variance components. We applied these two methods both independently and combined in selected genetic association datasets from human, dog and maize. The joint implementation of these two methods markedly reduced computing time and either maintained or improved statistical power. We used simulations to demonstrate the usefulness in controlling for substructure in genetic association datasets for a range of species and genetic architectures. We have made these methods available within an implementation of the software program TASSEL. PMID:20208535
NASA Technical Reports Server (NTRS)
Kincaid, D. R.; Young, D. M.
1984-01-01
Adapting and designing mathematical software to achieve optimum performance on the CYBER 205 is discussed. Comments and observations are made in light of recent work done on modifying the ITPACK software package and on writing new software for vector supercomputers. The goal was to develop very efficient vector algorithms and software for solving large sparse linear systems using iterative methods.
Kneissler, Jan; Drugowitsch, Jan; Friston, Karl; Butz, Martin V
2015-01-01
Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF). PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than 10-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares. PMID:25983690
MULTIPASS MUON RLA RETURN ARCS BASED ON LINEAR COMBINED-FUNCTION MAGNETS
Vasiliy Morozov, Alex Bogacz, Yves Roblin, Kevin Beard
2011-09-01
Recirculating Linear Accelerators (RLA) are an efficient way of accelerating short-lived muons to the multi-GeV energies required for Neutrino Factories and TeV energies required for Muon Colliders. In this paper we present a design of a two-pass RLA return arc based on linear combined function magnets, in which both charge muons with momenta different by a factor of two are transported through the same string of magnets. The arc is composed of 60{sup o}-bending symmetric super cells allowing for a simple arc geometry closing. By adjusting the dipole and quadrupole components of the combined-function magnets, each super cell is designed to be achromatic and to have zero initial and final periodic orbit offsets for both muon momenta. Such a design provides a greater compactness than, for instance, an FFAG lattice with its regular alternating bends and is expected to possess a large dynamic aperture characteristic of linear-field lattices.
NASA Technical Reports Server (NTRS)
Hegemann, S.; Shelhamer, M.; Kramer, P. D.; Zee, D. S.
2000-01-01
The phase of the translational linear VOR (LVOR) can be adaptively modified by exposure to a visual-vestibular mismatch. We extend here our earlier work on LVOR phase adaptation, and discuss the role of the oculomotor neural integrator. Ten subjects were oscillated laterally at 0.5 Hz, 0.3 g peak acceleration, while sitting upright on a linear sled. LVOR was assessed before and after adaptation with subjects tracking the remembered location of a target at 1 m in the dark. Phase and gain were measured by fitting sine waves to the desaccaded eye movements, and comparing sled and eye position. To adapt LVOR phase, the subject viewed a computer-generated stereoscopic visual display, at a virtual distance of 1 m, that moved so as to require either a phase lead or a phase lag of 53 deg. Adaptation lasted 20 min, during which subjects were oscillated at 0.5 Hz/0.3 g. Four of five subjects produced an adaptive change in the lag condition (range 4-45 deg), and each of five produced a change in the lead condition (range 19-56 deg), as requested. Changes in drift on eccentric gaze suggest that the oculomotor velocity-to-position integrator may be involved in the phase changes.
SILC: a new Planck internal linear combination CMB temperature map using directional wavelets
NASA Astrophysics Data System (ADS)
Rogers, Keir K.; Peiris, Hiranya V.; Leistedt, Boris; McEwen, Jason D.; Pontzen, Andrew
2016-08-01
We present new clean maps of the cosmic microwave background (CMB) temperature anisotropies (as measured by Planck) constructed with a novel internal linear combination (ILC) algorithm using directional, scale-discretized wavelets - scale-discretized, directional wavelet ILC or Scale-discretised, directional wavelet Internal Linear Combination (SILC). Directional wavelets, when convolved with signals on the sphere, can separate the anisotropic filamentary structures which are characteristic of both the CMB and foregrounds. Extending previous component separation methods, which use the frequency, spatial and harmonic signatures of foregrounds to separate them from the cosmological background signal, SILC can additionally use morphological information in the foregrounds and CMB to better localize the cleaning algorithm. We test the method on Planck data and simulations, demonstrating consistency with existing component separation algorithms, and discuss how to optimize the use of morphological information by varying the number of directional wavelets as a function of spatial scale. We find that combining the use of directional and axisymmetric wavelets depending on scale could yield higher quality CMB temperature maps. Our results set the stage for the application of SILC to polarization anisotropies through an extension to spin wavelets.
Mode-field adapter for tapered-fiber-bundle signal and pump combiners.
Koška, Pavel; Baravets, Yauhen; Peterka, Pavel; Bohata, Jan; Písařík, Michael
2015-02-01
We report on a novel mode-field adapter that is proposed to be incorporated inside tapered fused-fiber-bundle pump and signal combiners for high-power double-clad fiber lasers. Such an adapter allows optimization of signal-mode-field matching on the input and output fibers. Correspondingly, losses of the combiner signal branch are significantly reduced. The mode-field adapter optimization procedure is demonstrated on a combiner based on commercially available fibers. Signal wavelengths of 1.55 and 2 μm are considered. The losses can be further improved by using specially designed intermediate fiber and by dopant diffusion during splicing as confirmed by preliminary experimental results. PMID:25967784
Rowson, Steven; Duma, Stefan M
2013-05-01
Recent research has suggested possible long term effects due to repetitive concussions, highlighting the importance of developing methods to accurately quantify concussion risk. This study introduces a new injury metric, the combined probability of concussion, which computes the overall risk of concussion based on the peak linear and rotational accelerations experienced by the head during impact. The combined probability of concussion is unique in that it determines the likelihood of sustaining a concussion for a given impact, regardless of whether the injury would be reported or not. The risk curve was derived from data collected from instrumented football players (63,011 impacts including 37 concussions), which was adjusted to account for the underreporting of concussion. The predictive capability of this new metric is compared to that of single biomechanical parameters. The capabilities of these parameters to accurately predict concussion incidence were evaluated using two separate datasets: the Head Impact Telemetry System (HITS) data and National Football League (NFL) data collected from impact reconstructions using dummies (58 impacts including 25 concussions). Receiver operating characteristic curves were generated, and all parameters were significantly better at predicting injury than random guessing. The combined probability of concussion had the greatest area under the curve for all datasets. In the HITS dataset, the combined probability of concussion and linear acceleration were significantly better predictors of concussion than rotational acceleration alone, but not different from each other. In the NFL dataset, there were no significant differences between parameters. The combined probability of concussion is a valuable method to assess concussion risk in a laboratory setting for evaluating product safety. PMID:23299827
Elhaj, Fatin A; Salim, Naomie; Harris, Arief R; Swee, Tan Tian; Ahmed, Taqwa
2016-04-01
Arrhythmia is a cardiac condition caused by abnormal electrical activity of the heart, and an electrocardiogram (ECG) is the non-invasive method used to detect arrhythmias or heart abnormalities. Due to the presence of noise, the non-stationary nature of the ECG signal (i.e. the changing morphology of the ECG signal with respect to time) and the irregularity of the heartbeat, physicians face difficulties in the diagnosis of arrhythmias. The computer-aided analysis of ECG results assists physicians to detect cardiovascular diseases. The development of many existing arrhythmia systems has depended on the findings from linear experiments on ECG data which achieve high performance on noise-free data. However, nonlinear experiments characterize the ECG signal more effectively sense, extract hidden information in the ECG signal, and achieve good performance under noisy conditions. This paper investigates the representation ability of linear and nonlinear features and proposes a combination of such features in order to improve the classification of ECG data. In this study, five types of beat classes of arrhythmia as recommended by the Association for Advancement of Medical Instrumentation are analyzed: non-ectopic beats (N), supra-ventricular ectopic beats (S), ventricular ectopic beats (V), fusion beats (F) and unclassifiable and paced beats (U). The characterization ability of nonlinear features such as high order statistics and cumulants and nonlinear feature reduction methods such as independent component analysis are combined with linear features, namely, the principal component analysis of discrete wavelet transform coefficients. The features are tested for their ability to differentiate different classes of data using different classifiers, namely, the support vector machine and neural network methods with tenfold cross-validation. Our proposed method is able to classify the N, S, V, F and U arrhythmia classes with high accuracy (98.91%) using a combined support
NASA Astrophysics Data System (ADS)
Murakami, Yutaka; Matsuoka, Takashi; Takahashi, Kazuaki; Orihashi, Masayuki
In this paper, we evaluate BER (bit error rate) performance and diversity gain when employing a transmission technique utilizing LC (Linear Combination) diversity using 2 time slots with QPSK channels in 2×2 MIMO (Multiple-Input Multiple-Output) spatial multiplexing systems by comparing it with the upper and lower bound on BER. This evaluation shows that this transmission technique realizes high diversity gain and high transmission rate in LOS (line-of-sight) and NLOS (non line-of-sight) environments.
NASA Astrophysics Data System (ADS)
Kajiwara, Yoshiyuki; Shiraishi, Junya; Kobayashi, Shoei; Yamagami, Tamotsu
2009-03-01
A digital phase-locked loop (PLL) with a linearly constrained adaptive filter (LCAF) has been studied for higher-linear-density optical discs. LCAF has been implemented before an interpolated timing recovery (ITR) PLL unit in order to improve the quality of phase error calculation by using an adaptively equalized partial response (PR) signal. Coefficient update of an asynchronous sampled adaptive FIR filter with a least-mean-square (LMS) algorithm has been constrained by a projection matrix in order to suppress the phase shift of the tap coefficients of the adaptive filter. We have developed projection matrices that are suitable for Blu-ray disc (BD) drive systems by numerical simulation. Results have shown the properties of the projection matrices. Then, we have designed the read channel system of the ITR PLL with an LCAF model on the FPGA board for experiments. Results have shown that the LCAF improves the tilt margins of 30 gigabytes (GB) recordable BD (BD-R) and 33 GB BD read-only memory (BD-ROM) with a sufficient LMS adaptation stability.
NASA Astrophysics Data System (ADS)
Segl, Karl; Roessner, Sigrid
1999-10-01
Urban areas are characterized by a high frequency of small sized changes in surface cover types whose spatial patterns strongly influence the environmental conditions in cities. Airborne hyperspectral data yield a new potential for their spectrally-based identification, but also raise new challenges in image analysis caused by high spatial and spectral variability of the data. In this context we present a new linear unmixing approach including a pixel-oriented selection of endmember combinations. This approach was especially developed for analyzing urban conditions using data of airborne DAIS 7915 scanner for the city of Dresden, Germany. Because of the big number of spectrally similar endmembers in the urban environment, application of standard unmixing techniques lead to strong local variations of different endmembers and confusion of surface cover types. In comparison to these standard techniques a new extended mathematical model is used which includes stochastic models for each endmember. Additionally, a procedure for pixel oriented selection of likely endmember candidates is developed based on the assumption that the number of endmembers is limited within a pixel. For this purpose, all possible combinations of different endmembers are defined and stored in a list which forms the basis for spatially and thematically constrained endmember selection. These combinations of endmembers are tested during the linear unmixing process. In the result, sensible endmember combinations could be identified during the unmixing process for the 10 km by 4.5 km study area in Dresden. In comparison with standard image classification techniques our approach shows advantages especially in areas dominated by mixed pixels. Thus, a spatially and thematically precise identification of urban surface cover types could be achieved.
Rajvanshi, Meghna; Gayen, Kalyan; Venkatesh, K V
2013-06-01
A homoserine auxotroph strain of Corynebacterium glutamicum accumulates storage compound trehalose with lysine when limited by growth. Industrially lysine is produced from C. glutamicum through aspartate biosynthetic pathway, where enzymatic activity of aspartate kinase is allosterically controlled by the concerted feedback inhibition of threonine plus lysine. Ample threonine in the medium supports growth and inhibits lysine production (phenotype-I) and its complete absence leads to inhibition of growth in addition to accumulating lysine and trehalose (phenotype-II). In this work, we demonstrate that as threonine concentration becomes limiting, metabolic state of the cell shifts from maximizing growth (phenotype-I) to maximizing trehalose phenotype (phenotype-II) in a highly sensitive manner (with a Hill coefficient of 4). Trehalose formation was linked to lysine production through stoichiometry of the network. The study demonstrated that the net flux of the population was a linear combination of the two optimal phenotypic states, requiring only two experimental measurements to evaluate the flux distribution. The property of linear combination of two extreme phenotypes was robust for various medium conditions including varying batch time, initial glucose concentrations and medium osmolality. PMID:24432142
Can a linear combination of gait principal component vectors identify hip OA stages?
Ardestani, Marzieh M; Wimmer, Markus A
2016-07-01
Hip osteoarthritis (OA) has been shown to affect gait patterns of lower extremities. However, until now, no specific identifying gait characteristics for the various disease stages of hip OA have emerged. The present study addresses the following questions: (1) does a vector-based principal component analysis (PCA) discriminate between various disease stages? And, is this analysis more robust than using discrete gait variables? (2) Does the elimination of differences in walking speed affect the discriminatory robustness of a vector-based PCA? De-identified data sets of forty-five unilateral hip OA patients with varying disease stages and twenty-three age-matched, healthy control subjects were obtained from an available repository. PCA was performed on trial matrices consisting of all external joint moments and sagittal joint angles of one full gait cycle. Group differences in sagittal angles, external moments and the linear combination of PC vectors were investigated using spatial parameter mapping (SPM), a statistical vector field test. Several individual gait variables (i.e. joint moments or angles) demonstrated differences between healthy and moderately and/or severely affected subjects. Only the hip adduction moment could discriminate between the healthy and the early-stage OA group. There was no variable that could distinguish between all OA disease stages. In contrast, the linear combination of PC vectors demonstrated significant group differences between all stages of osteoarthritis; furthermore, these group differences stayed significant when matched speeds were input to the model. PMID:27255606
Radiation dose reduction with application of non-linear adaptive filters for abdominal CT
Singh, Sarabjeet; Kalra, Mannudeep K; Sung, Mi Kim; Back, Anni; Blake, Michael A
2012-01-01
AIM: To evaluate the effect of non-linear adaptive filters (NLAF) on abdominal computed tomography (CT) images acquired at different radiation dose levels. METHODS: Nineteen patients (mean age 61.6 ± 7.9 years, M:F = 8:11) gave informed consent for an Institutional Review Board approved prospective study involving acquisition of 4 additional image series (200, 150, 100, 50 mAs and 120 kVp) on a 64 slice multidetector row CT scanner over an identical 10 cm length in the abdomen. The CT images acquired at 150, 100 and 50 mAs were processed with the NLAF. Two radiologists reviewed unprocessed and processed images for image quality in a blinded randomized manner. CT dose index volume, dose length product, patient weight, transverse diameters, objective noise and CT numbers were recorded. Data were analyzed using Analysis of Variance and Wilcoxon signed rank test. RESULTS: Of the 31 lesions detected in abdominal CT images, 28 lesions were less than 1 cm in size. Subjective image noise was graded as unacceptable in unprocessed images at 50 and 100 mAs, and in NLAF processed images at 50 mAs only. In NLAF processed images, objective image noise was decreased by 21% (14.4 ± 4/18.2 ± 4.9) at 150 mAs, 28.3% (15.7 ± 5.6/21.9 ± 4) at 100 mAs and by 39.4% (18.8 ± 9/30.4 ± 9.2) at 50 mAs compared to unprocessed images acquired at respective radiation dose levels. At 100 mAs the visibility of smaller structures improved from suboptimal in unprocessed images to excellent in NLAF processed images, whereas diagnostic confidence was respectively improved from probably confident to fully confident. CONCLUSION: NLAF lowers image noise, improves the visibility of small structures and maintains lesion conspicuity at down to 100 mAs for abdominal CT. PMID:22328968
NASA Astrophysics Data System (ADS)
Wang, Shi-bing; Wang, Xing-yuan; Wang, Xiu-you; Zhou, Yu-fei
2016-04-01
With comprehensive consideration of generalized synchronization, combination synchronization and adaptive control, this paper investigates a novel adaptive generalized combination complex synchronization (AGCCS) scheme for different real and complex nonlinear systems with unknown parameters. On the basis of Lyapunov stability theory and adaptive control, an AGCCS controller and parameter update laws are derived to achieve synchronization and parameter identification of two real drive systems and a complex response system, as well as two complex drive systems and a real response system. Two simulation examples, namely, ACGCS for chaotic real Lorenz and Chen systems driving a hyperchaotic complex Lü system, and hyperchaotic complex Lorenz and Chen systems driving a real chaotic Lü system, are presented to verify the feasibility and effectiveness of the proposed scheme.
Sensory, motor, and combined contexts for context-specific adaptation of saccade gain in humans
NASA Technical Reports Server (NTRS)
Shelhamer, Mark; Clendaniel, Richard
2002-01-01
Saccadic eye movements can be adapted in a context-specific manner such that their gain can be made to depend on the state of a prevailing context cue. We asked whether context cues are more effective if their nature is primarily sensory, motor, or a combination of sensory and motor. Subjects underwent context-specific adaptation using one of three different context cues: a pure sensory context (head roll-tilt right or left); a pure motor context (changes in saccade direction); or a combined sensory-motor context (head roll-tilt and changes in saccade direction). We observed context-specific adaptation in each condition; the greatest degree of context-specificity occurred in paradigms that used the motor cue, alone or in conjunction with the sensory cue. Copyright 2002 Elsevier Science Ireland Ltd.
NASA Technical Reports Server (NTRS)
Balas, Mark; Frost, Susan
2012-01-01
Flexible structures containing a large number of modes can benefit from adaptive control techniques which are well suited to applications that have unknown modeling parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend our adaptive control theory to accommodate troublesome modal subsystems of a plant that might inhibit the adaptive controller. In some cases the plant does not satisfy the requirements of Almost Strict Positive Realness. Instead, there maybe be a modal subsystem that inhibits this property. This section will present new results for our adaptive control theory. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for the troublesome modal subsystem, or the Q modes. Here we present the theory for adaptive controllers modified by RMFs, with attention to the issue of disturbances propagating through the Q modes. We apply the theoretical results to a flexible structure example to illustrate the behavior with and without the residual mode filter.
Cavusoglu, Tarik; Yazici, Ilker; Vargel, Ibrahim; Karakaya, Esen Ibrahim
2011-01-01
In this clinical report, we are presenting the combination of demineralized bone matrix combined with bilateral galea frontalis flaps. Based on our 6-month results, this seems to be a reasonable combination to accomplish long-lasting restoration of forehead defects related to en coup de sabre linear localized scleroderma. PMID:21233742
No Evidence for a Low Linear Energy Transfer Adaptive Response in Irradiated RKO Cells
Sowa, Marianne B.; Goetz, Wilfried; Baulch, Janet E.; Lewis, Adam J.; Morgan, William F.
2011-01-06
It has become increasingly evident from reports in the literature that there are many confounding factors that are capable of modulating radiation induced non-targeted responses such as the bystander effect and the adaptive response. In this paper we examine recent data that suggest that the observation of non-targeted responses may not be universally observable for differing radiation qualities. We have conducted a study of the adaptive response following low LET exposures for human colon carcinoma cells and failed to observe adaption for the endpoints of clonogenic survival or micronucleus formation.
Wu, Mixia; Shu, Yu; Li, Zhaohai; Liu, Aiyi
2016-08-30
A sequential design is proposed to test whether the accuracy of a binary diagnostic biomarker meets the minimal level of acceptance. The accuracy of a binary diagnostic biomarker is a linear combination of the marker's sensitivity and specificity. The objective of the sequential method is to minimize the maximum expected sample size under the null hypothesis that the marker's accuracy is below the minimal level of acceptance. The exact results of two-stage designs based on Youden's index and efficiency indicate that the maximum expected sample sizes are smaller than the sample sizes of the fixed designs. Exact methods are also developed for estimation, confidence interval and p-value concerning the proposed accuracy index upon termination of the sequential testing. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. PMID:26947768
NASA Astrophysics Data System (ADS)
Ziemann, Amanda K.; Messinger, David W.
2014-06-01
Hyperspectral images comprise, by design, high dimensional image data. However, research has shown that for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of non-linear manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data. With graph theory and manifold learning based models, the only assumption is that the data reside on an underlying manifold. In previous publications, we have shown that manifold coordinate approximation using locally linear embedding (LLE) is a viable pre-processing step for target detection with the Adaptive Cosine/Coherence Estimator (ACE) algorithm. Here, we improve upon that methodology using a more rigorous, data-driven implementation of LLE that incorporates the injection of a cloud" of target pixels and the Spectral Angle Mapper (SAM) detector. The LLE algorithm, which holds that the data is locally linear, is typically governed by a user defined parameter k, indicating the number of nearest neighbors to use in the initial graph model. We use an adaptive approach to building the graph that is governed by the data itself and does not rely upon user input. This implementation of LLE can yield greater separation between the target pixels and the background pixels in the manifold space. We present an analysis of target detection performance in the manifold coordinates using scene-derived target spectra and laboratory-measured target spectra across two different data sets.
Tommasi, C.; May, C.
2010-09-30
The DKL-optimality criterion has been recently proposed for the dual problem of model discrimination and parameter estimation, for the case of two rival models. A sequential version of the DKL-optimality criterion is herein proposed in order to discriminate and efficiently estimate more than two nested non-linear models. Our sequential method is inspired by the procedure of Biswas and Chaudhuri (2002), which is however useful only in the set up of nested linear models.
Biohybrid Control of General Linear Systems Using the Adaptive Filter Model of Cerebellum
Wilson, Emma D.; Assaf, Tareq; Pearson, Martin J.; Rossiter, Jonathan M.; Dean, Paul; Anderson, Sean R.; Porrill, John
2015-01-01
The adaptive filter model of the cerebellar microcircuit has been successfully applied to biological motor control problems, such as the vestibulo-ocular reflex (VOR), and to sensory processing problems, such as the adaptive cancelation of reafferent noise. It has also been successfully applied to problems in robotics, such as adaptive camera stabilization and sensor noise cancelation. In previous applications to inverse control problems, the algorithm was applied to the velocity control of a plant dominated by viscous and elastic elements. Naive application of the adaptive filter model to the displacement (as opposed to velocity) control of this plant results in unstable learning and control. To be more generally useful in engineering problems, it is essential to remove this restriction to enable the stable control of plants of any order. We address this problem here by developing a biohybrid model reference adaptive control (MRAC) scheme, which stabilizes the control algorithm for strictly proper plants. We evaluate the performance of this novel cerebellar-inspired algorithm with MRAC scheme in the experimental control of a dielectric electroactive polymer, a class of artificial muscle. The results show that the augmented cerebellar algorithm is able to accurately control the displacement response of the artificial muscle. The proposed solution not only greatly extends the practical applicability of the cerebellar-inspired algorithm, but may also shed light on cerebellar involvement in a wider range of biological control tasks. PMID:26257638
NASA Astrophysics Data System (ADS)
Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.
2015-03-01
Maintaining or even improving image quality while lowering patient dose is always the desire in clinical CT imaging. Iterative reconstruction (IR) algorithms have been designed to help reduce dose and/or provide better image quality. In this work, the channelized scanning linear observer (CSLO) is applied to study the combination of detection and estimation task performance using CT image data. The purpose of this work is to design a task--based approach to quantitatively evaluate image--quality for different reconstruction algorithms. Low--contrast objects embedded in head--size and body--size phantoms are imaged multiple times and reconstructed by FBP and an IR algorithm for this study. Independent signal present and absent ROIs cropped from images are channelized by Difference of Gauss channels for CSLO training and testing. Estimation receiver operating characteristic (EROC) curves and the area under EROC curve (EAUC) are calculated by CSLO as the figure of merit. The One-- Shot method is used to compute the variance of the EAUC values. Results suggest that the IR algorithm studied in this work could efficiently reduce the dose approximately 54% to achieve an image quality comparable to conventional FBP reconstruction for the combined detection and estimation tasks.
Accuracy requirements of optical linear algebra processors in adaptive optics imaging systems
NASA Technical Reports Server (NTRS)
Downie, John D.
1990-01-01
A ground-based adaptive optics imaging telescope system attempts to improve image quality by detecting and correcting for atmospherically induced wavefront aberrations. The required control computations during each cycle will take a finite amount of time. Longer time delays result in larger values of residual wavefront error variance since the atmosphere continues to change during that time. Thus an optical processor may be well-suited for this task. This paper presents a study of the accuracy requirements in a general optical processor that will make it competitive with, or superior to, a conventional digital computer for the adaptive optics application. An optimization of the adaptive optics correction algorithm with respect to an optical processor's degree of accuracy is also briefly discussed.
NASA Astrophysics Data System (ADS)
Bentaallah, Abderrahim; Massoum, Ahmed; Benhamida, Farid; Meroufel, Abdelkader
2012-03-01
This paper studies the nonlinear adaptive control of an induction motor with natural dynamic complete nonlinear observer. The aim of this work is to develop a nonlinear control law and adaptive performance for an asynchronous motor with two main objectives: to improve the continuation of trajectories and the stability, robustness to parametric variations and disturbances rejection. This control law will independently control the speed and flux into the machine by restricting supply. A complete nonlinear observer for dynamic nature ensuring closed loop stability of the entire control and observer has been developed. Several simulations have also been carried out to demonstrate system performance.
NASA Technical Reports Server (NTRS)
Bautista, Abigail B.
1994-01-01
Twenty-four observers looked through a pair of 20 diopter wedge prisms and pointed to an image of a target which was displaced vertically from eye level by 6 cm at a distance of 30 cm. Observers pointed 40 times, using only their right hand, and received error-corrective feedback upon termination of each pointing response (terminal visual feedback). At three testing distances, 20, 30, and 40 cm, ten pre-exposure and ten post-exposure pointing responses were recorded for each hand as observers reached to a mirror-viewed target located at eye level. The difference between pre- and post-exposure pointing response (adaptive shift) was compared for both Exposed and Unexposed hands across all three testing distances. The data were assessed according to the results predicted by two alternative models for processing spatial-information: one using angular displacement information and another using linear displacement information. The angular model of spatial mapping best predicted the observer's pointing response for the Exposed hand. Although the angular adaptive shift did not change significantly as a function of distance (F(2,44) = 1.12, n.s.), the linear adaptive shift increased significantly over the three testing distances 02 44) = 4.90 p less than 0.01).
Assembling a Computerized Adaptive Testing Item Pool as a Set of Linear Tests
ERIC Educational Resources Information Center
van der Linden, Wim J.; Ariel, Adelaide; Veldkamp, Bernard P.
2006-01-01
Test-item writing efforts typically results in item pools with an undesirable correlational structure between the content attributes of the items and their statistical information. If such pools are used in computerized adaptive testing (CAT), the algorithm may be forced to select items with less than optimal information, that violate the content…
Weighted Structural Regression: A Broad Class of Adaptive Methods for Improving Linear Prediction.
ERIC Educational Resources Information Center
Pruzek, Robert M.; Lepak, Greg M.
1992-01-01
Adaptive forms of weighted structural regression are developed and discussed. Bootstrapping studies indicate that the new methods have potential to recover known population regression weights and predict criterion score values routinely better than do ordinary least squares methods. The new methods are scale free and simple to compute. (SLD)
A weighted adjoint-source for weight-window generation by means of a linear tally combination
Sood, Avneet; Booth, Thomas E; Solomon, Clell J
2009-01-01
A new importance estimation technique has been developed that allows weight-window optimization for a linear combination of tallies. This technique has been implemented in a local version of MCNP and effectively weights the adjoint source term for each tally in the combination. Optimizing weight window parameters for the linear tally combination allows the user to optimize weight windows for multiple regions at once. In this work, we present our results of solutions to an analytic three-tally-region test problem and a flux calculation on a 100,000 voxel oil-well logging tool problem.
Mixed linear model approach adapted for genome-wide association studies
Technology Transfer Automated Retrieval System (TEKTRAN)
Mixed linear model (MLM) methods have proven useful in controlling for population structure and relatedness within genome-wide association studies. However, MLM-based methods can be computationally challenging for large datasets. We report a compression approach, called ‘compressed MLM,’ that decrea...
[Non-linear real-time adaptive filtration of ultrasound TI628A echotomoscope images].
Barannik, E A; Volokhov, Iu V; Marusenko, A I
1997-01-01
The statistical uncertainty caused by speckle noise artifacts is the reason for the great importance of the problem which is the optimum choice between the medical diagnostic systems resolution and the statistical accuracy of histological tissue identification. The way of speckle noise suppression, which is closely associated with the well-known idea of adaptive filtration and based on the physical analysis of the origin of true and false signals, is very promising. The testing results of the nonlinear real-time adaptive filter which has been designed for a TI628A echotomoscope are presented. The filter has been shown to have a rather high contrast and space resolution and reduces the speckle noise and other artifacts of the images. PMID:9445983
NASA Astrophysics Data System (ADS)
Cicchi, Riccardo; Matthäus, Christian; Meyer, Tobias; Lattermann, Annika; Dietzek, Benjamin; Brehm, Bernhard R.; Popp, Jürgen; Pavone, Francesco S.
2015-03-01
Atherosclerosis is among the most widespread cardiovascular diseases and one of the leading cause of death in the Western World. Characterization of arterial tissue in atherosclerotic condition is extremely interesting from the diagnostic point of view, especially for what is concerning collagen content and organization because collagen plays a crucial role in plaque vulnerability. Routinely used diagnostic methods, such as histopathological examination, are limited to morphological analysis of the examined tissues, whereas an exhaustive characterization requires immune-histochemical examination and a morpho-functional approach. Non-linear microscopy techniques offer the potential for providing morpho-functional information on the examined tissues in a label-free way. In this study, we employed combined SHG and FLIM microscopy for characterizing collagen organization in both normal arterial wall and within atherosclerotic plaques. Image pattern analysis of SHG images allowed characterizing collagen organization in different tissue regions. In addition, the analysis of collagen fluorescence decay contributed to the characterization of the samples on the basis of collagen fluorescence lifetime. Different values of collagen fiber mean size, collagen distribution, collagen anisotropy and collagen fluorescence lifetime were found in normal arterial wall and within plaque depositions, prospectively allowing for automated classification of atherosclerotic lesions and plaque vulnerability. The presented method represents a promising diagnostic tool for evaluating atherosclerotic tissue and has the potential to find a stable place in clinical setting as well as to be applied in vivo in the near future.
Extracting H I cosmological signal with generalized needlet internal linear combination
NASA Astrophysics Data System (ADS)
Olivari, L. C.; Remazeilles, M.; Dickinson, C.
2016-03-01
H I intensity mapping is a new observational technique to map fluctuations in the large-scale structure of matter using the 21 cm emission line of atomic hydrogen (H I). Sensitive H I intensity mapping experiments have the potential to detect Baryon Acoustic Oscillations at low redshifts (z ≲ 1) in order to constrain the properties of dark energy. Observations of the H I signal will be contaminated by instrumental noise and, more significantly, by astrophysical foregrounds, such as Galactic synchrotron emission, which is at least four orders of magnitude brighter than the H I signal. Foreground cleaning is recognized as one of the key challenges for future radio astronomy surveys. We study the ability of the Generalized Needlet Internal Linear Combination (GNILC) method to subtract radio foregrounds and to recover the cosmological H I signal for a general H I intensity mapping experiment. The GNILC method is a new technique that uses both frequency and spatial information to separate the components of the observed data. Our results show that the method is robust to the complexity of the foregrounds. For simulated radio observations including H I emission, Galactic synchrotron, Galactic free-free, radio sources, and 0.05 mK thermal noise, we find that the GNILC method can reconstruct the H I power spectrum for multipoles 30 < ℓ < 150 with 6 per cent accuracy on 50 per cent of the sky for a redshift z ˜ 0.25.
Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei
2015-01-01
Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928
Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei
2015-01-01
Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928
Sun, W Y
1993-04-01
This thesis solves the problem of finding the optimal linear noise-reduction filter for linear tomographic image reconstruction. The optimization is data dependent and results in minimizing the mean-square error of the reconstructed image. The error is defined as the difference between the result and the best possible reconstruction. Applications for the optimal filter include reconstructions of positron emission tomographic (PET), X-ray computed tomographic, single-photon emission tomographic, and nuclear magnetic resonance imaging. Using high resolution PET as an example, the optimal filter is derived and presented for the convolution backprojection, Moore-Penrose pseudoinverse, and the natural-pixel basis set reconstruction methods. Simulations and experimental results are presented for the convolution backprojection method.
Connolly, Amanda J; Rinehart, Nicole J; Fielding, Joanne
2016-10-01
Growing evidence suggests Attention Deficit Hyperactivity Disorder (ADHD) often co-occurs with Autism Spectrum Disorder (ASD), and a better understanding of the nature of their overlap, including at a neurobiological level, is needed. Research has implicated cerebellar-networks as part of the neural-circuitry disrupted in ASD, but little research has been carried out to investigate this in ADHD. We investigated cerebellar integrity using a double-step saccade adaptation paradigm in a group of male children age 8-15 (n=12) diagnosed with ADHD-Combined Type (-CT). Their performance was compared to a group of age and IQ-matched typically developing (TD) controls (n=12). Parent reported symptoms of ADHD-CT and ASD were measured, along with motor proficiency (Movement ABC-2). We found, on average, the adaptation of saccade gain was reduced for the ADHD-CT group compared to the TD group. Greater saccadic gain change (adaptation) was also positively correlated with higher Movement ABC-2 total and balance scores among the ADHD-CT participants. These differences suggest cerebellar networks underlying saccade adaptation may be disrupted in young people with ADHD-CT. Though our findings require further replication with larger samples, they suggest further research into cerebellar dysfunction in ADHD-CT, and as a point of neurobiological overlap with ASD, may be warranted. PMID:27393248
Reed, M.S.; Podesta, G.; Fazey, I.; Geeson, N.; Hessel, R.; Hubacek, K.; Letson, D.; Nainggolan, D.; Prell, C.; Rickenbach, M.G.; Ritsema, C.; Schwilch, G.; Stringer, L.C.; Thomas, A.D.
2013-01-01
Experts working on behalf of international development organisations need better tools to assist land managers in developing countries maintain their livelihoods, as climate change puts pressure on the ecosystem services that they depend upon. However, current understanding of livelihood vulnerability to climate change is based on a fractured and disparate set of theories and methods. This review therefore combines theoretical insights from sustainable livelihoods analysis with other analytical frameworks (including the ecosystem services framework, diffusion theory, social learning, adaptive management and transitions management) to assess the vulnerability of rural livelihoods to climate change. This integrated analytical framework helps diagnose vulnerability to climate change, whilst identifying and comparing adaptation options that could reduce vulnerability, following four broad steps: i) determine likely level of exposure to climate change, and how climate change might interact with existing stresses and other future drivers of change; ii) determine the sensitivity of stocks of capital assets and flows of ecosystem services to climate change; iii) identify factors influencing decisions to develop and/or adopt different adaptation strategies, based on innovation or the use/substitution of existing assets; and iv) identify and evaluate potential trade-offs between adaptation options. The paper concludes by identifying interdisciplinary research needs for assessing the vulnerability of livelihoods to climate change. PMID:25844020
Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection
Ke, Ruian; Loverdo, Claude; Qi, Hangfei; Sun, Ren; Lloyd-Smith, James O.
2015-01-01
Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design. PMID:26125950
Wei, Wei; Shin, Young Shik; Xue, Min; Matsutani, Tomoo; Masui, Kenta; Yang, Huijun; Ikegami, Shiro; Gu, Yuchao; Herrmann, Ken; Johnson, Dazy; Ding, Xiangming; Hwang, Kiwook; Kim, Jungwoo; Zhou, Jian; Su, Yapeng; Li, Xinmin; Bonetti, Bruno; Chopra, Rajesh; James, C David; Cavenee, Webster K; Cloughesy, Timothy F; Mischel, Paul S; Heath, James R; Gini, Beatrice
2016-04-11
Intratumoral heterogeneity of signaling networks may contribute to targeted cancer therapy resistance, including in the highly lethal brain cancer glioblastoma (GBM). We performed single-cell phosphoproteomics on a patient-derived in vivo GBM model of mTOR kinase inhibitor resistance and coupled it to an analytical approach for detecting changes in signaling coordination. Alterations in the protein signaling coordination were resolved as early as 2.5 days after treatment, anticipating drug resistance long before it was clinically manifest. Combination therapies were identified that resulted in complete and sustained tumor suppression in vivo. This approach may identify actionable alterations in signal coordination that underlie adaptive resistance, which can be suppressed through combination drug therapy, including non-obvious drug combinations. PMID:27070703
Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai
2015-01-01
The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120
Liu, Hui; Zhang, Cai-Ming; Su, Zhi-Yuan; Wang, Kai; Deng, Kai
2015-01-01
The key problem of computer-aided diagnosis (CAD) of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO) pulmonary nodules than other typical algorithms. PMID:25945120
NASA Technical Reports Server (NTRS)
Brooke, D.; Vondrasek, D. V.
1978-01-01
The aerodynamic influence coefficients calculated using an existing linear theory program were used to modify the pressures calculated using impact theory. Application of the combined approach to several wing-alone configurations shows that the combined approach gives improved predictions of the local pressure and loadings over either linear theory alone or impact theory alone. The approach not only removes most of the short-comings of the individual methods, as applied in the Mach 4 to 8 range, but also provides the basis for an inverse design procedure applicable to high speed configurations.
Lewis, Robert Michael (College of William and Mary, Williamsburg, VA); Torczon, Virginia Joanne (College of William and Mary, Williamsburg, VA); Kolda, Tamara Gibson
2006-08-01
We consider the solution of nonlinear programs in the case where derivatives of the objective function and nonlinear constraints are unavailable. To solve such problems, we propose an adaptation of a method due to Conn, Gould, Sartenaer, and Toint that proceeds by approximately minimizing a succession of linearly constrained augmented Lagrangians. Our modification is to use a derivative-free generating set direct search algorithm to solve the linearly constrained subproblems. The stopping criterion proposed by Conn, Gould, Sartenaer and Toint for the approximate solution of the subproblems requires explicit knowledge of derivatives. Such information is presumed absent in the generating set search method we employ. Instead, we show that stationarity results for linearly constrained generating set search methods provide a derivative-free stopping criterion, based on a step-length control parameter, that is sufficient to preserve the convergence properties of the original augmented Lagrangian algorithm.
NASA Astrophysics Data System (ADS)
Chak, Yew-Chung; Varatharajoo, Renuganth
2016-07-01
Many spacecraft attitude control systems today use reaction wheels to deliver precise torques to achieve three-axis attitude stabilization. However, irrecoverable mechanical failure of reaction wheels could potentially lead to mission interruption or total loss. The electrically-powered Solar Array Drive Assemblies (SADA) are usually installed in the pitch axis which rotate the solar arrays to track the Sun, can produce torques to compensate for the pitch-axis wheel failure. In addition, the attitude control of a flexible spacecraft poses a difficult problem. These difficulties include the strong nonlinear coupled dynamics between the rigid hub and flexible solar arrays, and the imprecisely known system parameters, such as inertia matrix, damping ratios, and flexible mode frequencies. In order to overcome these drawbacks, the adaptive Jacobian tracking fuzzy control is proposed for the combined attitude and sun-tracking control problem of a flexible spacecraft during attitude maneuvers in this work. For the adaptation of kinematic and dynamic uncertainties, the proposed scheme uses an adaptive sliding vector based on estimated attitude velocity via approximate Jacobian matrix. The unknown nonlinearities are approximated by deriving the fuzzy models with a set of linguistic If-Then rules using the idea of sector nonlinearity and local approximation in fuzzy partition spaces. The uncertain parameters of the estimated nonlinearities and the Jacobian matrix are being adjusted online by an adaptive law to realize feedback control. The attitude of the spacecraft can be directly controlled with the Jacobian feedback control when the attitude pointing trajectory is designed with respect to the spacecraft coordinate frame itself. A significant feature of this work is that the proposed adaptive Jacobian tracking scheme will result in not only the convergence of angular position and angular velocity tracking errors, but also the convergence of estimated angular velocity to
NASA Astrophysics Data System (ADS)
Brüggemann, Matthias; Kays, Rüdiger; Springer, Paul; Erdler, Oliver
2015-03-01
In this paper we present a combination of block-matching and differential motion field estimation. We initialize the motion field using a predictive hierarchical block-matching approach. This vector field is refined by a pixel-recursive differential motion estimation method. We integrate image warping and adaptive filter kernels into the Horn and Schunck differential optical flow estimation approach to break the block structure of the initial correspondence vector fields and compute motion field updates to fulfill the smoothness constraint inside motion boundaries. The influence of occlusion areas is reduced by integrating an in-the-loop occlusion detection and adjusting the adaptive filter weights in the iteration process. We integrate the combined estimation into a hierarchical multi-scale framework. The refined motion on the current scale is upscaled and used as prediction for block-matching motion estimation on the next scale. With the proposed system we are able to combine the advantages of block-matching and differential motion estimation and achieve a dense vector field with floating point precision even for large motion.
Bozzatello, Paola; Bellino, Silvio
2016-06-30
Few investigations evaluated the long-term effects of psychotherapies in borderline personality disorder (BPD). In a previous study, we compared efficacy of combination of fluoxetine and interpersonal psychotherapy adapted to BPD (IPT-BPD) versus single fluoxetine administered for 32 weeks. This study is aimed to investigate whether the results obtained with the addition of IPT-BPD persist during a follow-up period. Forty-four patients who completed the 32 weeks trial underwent 24 months of follow-up receiving fluoxetine 20-40 mg/day. Clinical Global Impression Severity (CGI-S), Hamilton Rating Scales for Depression and Anxiety (HDRS, HARS), Social and Occupational Functioning Assessment Scale (SOFAS), Satisfaction Profile (SAT-P), and Borderline Personality Disorder Severity Index (BPDSI) were repeated at 6, 12, and 24 months. Statistical analysis was performed with the general linear model. Results showed that most of the differences between combined therapy and single pharmacotherapy at the end of the 32 weeks trial were maintained after 24 months follow-up. The addition of IPT-BPD to medication produced greater effects on BPD symptoms (impulsivity and interpersonal relationships) and quality of life (perception of psychological and social functioning) that endured after termination of psychotherapy. On the contrary, different effects on anxiety symptoms and affective instability were lost after 6 months. PMID:27107668
NASA Astrophysics Data System (ADS)
Ding, Zhe; Xu, Zhanqi; Zeng, Xiaodong; Ma, Tao; Yang, Fan
2014-04-01
By adopting the orthogonal frequency division multiplexing technology, spectrum-sliced elastic optical path networks can offer flexible bandwidth to each connection request and utilize the spectrum resources efficiently. The routing and spectrum assignment (RSA) problems in SLICE networks are solved by using heuristic algorithms in most prior studies and addressed by intelligent algorithms in few investigations. The performance of RSA algorithms can be further improved if we could combine such two types of algorithms. Therefore, we propose three hybrid RSA algorithms: DACE-GMSF, DACE-GLPF, and DACE-GEMkPSF, which are the combination of the heuristic algorithm and coevolution based on distance-adaptive policy. In the proposed algorithms, we first groom the connection requests, then sort the connection requests by using the heuristic algorithm (most subcarriers first, longest path first, and extended most k paths' slots first), and finally search the approximately optimal solution with the coevolutionary policy. We present a model of the RSA problem by using integral linear programming, and key elements in the proposed algorithms are addressed in detail. Simulations under three topologies show that the proposed hybrid RSA algorithms can save spectrum resources efficiently.
Spyrou, Loukianos; Blokland, Yvonne; Farquhar, Jason; Bruhn, Jorgen
2016-06-01
Brain-Computer Interface (BCI) systems are traditionally designed by taking into account user-specific data to enable practical use. More recently, subject independent (SI) classification algorithms have been developed which bypass the subject specific adaptation and enable rapid use of the system. A brain switch is a particular BCI system where the system is required to distinguish from two separate mental tasks corresponding to the on-off commands of a switch. Such applications require a low false positive rate (FPR) while having an acceptable response time (RT) until the switch is activated. In this work, we develop a methodology that produces optimal brain switch behavior through subject specific (SS) adaptation of: a) a multitrial prediction combination model and b) an SI classification model. We propose a statistical model of combining classifier predictions that enables optimal FPR calibration through a short calibration session. We trained an SI classifier on a training synchronous dataset and tested our method on separate holdout synchronous and asynchronous brain switch experiments. Although our SI model obtained similar performance between training and holdout datasets, 86% and 85% for the synchronous and 69% and 66% for the asynchronous the between subject FPR and TPR variability was high (up to 62%). The short calibration session was then employed to alleviate that problem and provide decision thresholds that achieve when possible a target FPR=1% with good accuracy for both datasets. PMID:26529768
Linder, Mats; Ranganathan, Anirudh; Brinck, Tore
2013-02-12
We present a structure-based parametrization of the Linear Interaction Energy (LIE) method and show that it allows for the prediction of absolute protein-ligand binding energies. We call the new model "Adapted" LIE (ALIE) because the α and β coefficients are defined by system-dependent descriptors and do therefore not require any empirical γ term. The best formulation attains a mean average deviation of 1.8 kcal/mol for a diverse test set and depends on only one fitted parameter. It is robust with respect to additional fitting and cross-validation. We compare this new approach with standard LIE by Åqvist and co-workers and the LIE + γSASA model (initially suggested by Jorgensen and co-workers) against in-house and external data sets and discuss their applicabilities. PMID:26588766
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
Berg, Maya; García-Hernández, Raquel; Cuypers, Bart; Vanaerschot, Manu; Manzano, José I.; Poveda, José A.; Ferragut, José A.; Castanys, Santiago
2015-01-01
Together with vector control, chemotherapy is an essential tool for the control of visceral leishmaniasis (VL), but its efficacy is jeopardized by growing resistance and treatment failure against first-line drugs. To delay the emergence of resistance, the use of drug combinations of existing antileishmanial agents has been tested systematically in clinical trials for the treatment of visceral leishmaniasis (VL). In vitro, Leishmania donovani promastigotes are able to develop experimental resistance to several combinations of different antileishmanial drugs after 10 weeks of drug pressure. Using an untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics approach, we identified metabolic changes in lines that were experimentally resistant to drug combinations and their respective single-resistant lines. This highlighted both collective metabolic changes (found in all combination therapy-resistant [CTR] lines) and specific ones (found in certain CTR lines). We demonstrated that single-resistant and CTR parasite cell lines show distinct metabolic adaptations, which all converge on the same defensive mechanisms that were experimentally validated: protection against drug-induced and external oxidative stress and changes in membrane fluidity. The membrane fluidity changes were accompanied by changes in drug uptake only in the lines that were resistant against drug combinations with antimonials, and surprisingly, drug accumulation was higher in these lines. Together, these results highlight the importance and the central role of protection against oxidative stress in the different resistant lines. Ultimately, these phenotypic changes might interfere with the mode of action of all drugs that are currently used for the treatment of VL and should be taken into account in drug development. PMID:25645828
Melatonin combined with ascorbic acid provides salt adaptation in Citrus aurantium L. seedlings.
Kostopoulou, Zacharoula; Therios, Ioannis; Roumeliotis, Efstathios; Kanellis, Angelos K; Molassiotis, Athanassios
2015-01-01
Ascorbic acid (AsA) and melatonin (Mel) are known molecules participating in stress resistance, however, their combined role in counteracting the impact of salinity in plants is still unknown. In this work the effect of exogenous application of 0.50 mΜ AsA, 1 μΜ Mel and their combination (AsA + Mel) on various stress responses in leaves and roots of Citrus aurantium L. seedlings grown under 100 mΜ NaCl for 30 days was investigated. Application of AsA, Mel or AsA + Mel to saline solution decreased NaCl-induced electrolyte leakage and lipid peroxidation and prevented NaCl-associated toxicity symptoms and pigments degradation. Also, leaves exposed to combined AsA + Mel treatment displayed lower Cl(-) accumulation. Treatments with AsA and/or Mel modulated differently carbohydrates, proline, phenols, glutathione and the total antioxidant power of tissues as well as the activities of SOD, APX, POD, GR and PPO compared to NaCl alone treatment. Exposure of leaves and roots to chemical treatments and especially to combined AsA and Mel application was able to regulate CaMIPS, CaSLAH1 and CaMYB73 expression, indicating that sugar metabolism, ion homeostasis and transcription regulation were triggered by AsA and Mel. These results provide evidence that the activation of the metabolic pathways associated with combined AsA and Mel application are linked with salt adaptation in citrus plants. PMID:25500452
Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...
Rational design and adaptive management of combination therapies for Hepatitis C virus infection
Ke, Ruian; Loverdo, Claude; Qi, Hangfei; Sun, Ren; Lloyd-Smith, James O.; Kouyos, Roger Dimitri
2015-06-30
Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design.
Rational design and adaptive management of combination therapies for Hepatitis C virus infection
Ke, Ruian; Loverdo, Claude; Qi, Hangfei; Sun, Ren; Lloyd-Smith, James O.; Kouyos, Roger Dimitri
2015-06-30
Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensatemore » when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design.« less
Masquelier, Timothée; Deco, Gustavo
2013-01-01
In the brain, synchronization among cells of an assembly is a common phenomenon, and thought to be functionally relevant. Here we used an in vitro experimental model of cell assemblies, cortical cultures, combined with numerical simulations of a spiking neural network (SNN) to investigate how and why spontaneous synchronization occurs. In order to deal with excitation only, we pharmacologically blocked GABAAergic transmission using bicuculline. Synchronous events in cortical cultures tend to involve almost every cell and to display relatively constant durations. We have thus named these "network spikes" (NS). The inter-NS-intervals (INSIs) proved to be a more interesting phenomenon. In most cortical cultures NSs typically come in series or bursts ("bursts of NSs", BNS), with short (~1 s) INSIs and separated by long silent intervals (tens of s), which leads to bimodal INSI distributions. This suggests that a facilitating mechanism is at work, presumably short-term synaptic facilitation, as well as two fatigue mechanisms: one with a short timescale, presumably short-term synaptic depression, and another one with a longer timescale, presumably cellular adaptation. We thus incorporated these three mechanisms into the SNN, which, indeed, produced realistic BNSs. Next, we systematically varied the recurrent excitation for various adaptation timescales. Strong excitability led to frequent, quasi-periodic BNSs (CV~0), and weak excitability led to rare BNSs, approaching a Poisson process (CV~1). Experimental cultures appear to operate within an intermediate weakly-synchronized regime (CV~0.5), with an adaptation timescale in the 2-8 s range, and well described by a Poisson-with-refractory-period model. Taken together, our results demonstrate that the INSI statistics are indeed informative: they allowed us to infer the mechanisms at work, and many parameters that we cannot access experimentally. PMID:24146781
Combining the APES and Minimum-variance Beamformers for Adaptive Ultrasound Imaging.
Mohammadzadeh Asl, Babak
2016-07-01
In recent years, adaptive minimum-variance (MV) beamforming has been successfully applied to medical ultrasound imaging, resulting in simultaneous improvement in imaging resolution and contrast. MV has high resolution and hence can provide accurate estimates of the target locations. However, the MV amplitude estimates are significantly biased downward, especially when occurring the errors in model parameters. The amplitude and phase estimation (APES) beamformer gives much more accurate amplitude estimates at the target locations, but at the cost of lower resolution. To reap the benefits of both MV and APES, we have proposed a modified APES (MAPES) beamformer by adding a parameter which controls the trade-off between spatial and amplitude resolutions. We have also proposed an adaptive beamformer which combines the MV and APES. The proposed beamformer first estimates the peak locations using the MV estimator and then refines the amplitude estimates at these locations using the MAPES estimator. By using simulated and experimental data-point targets as well as cyst phantoms-we show the efficacy of the proposed beamformers. PMID:26333280
Combined Simulation of a Micro Permanent Magnetic Linear Contactless Displacement Sensor
Gao, Jing; Müller, Wolfgang F.O.; Greiner, Felix; Eicher, Dirk; Weiland, Thomas; Schlaak, Helmut F.
2010-01-01
The permanent magnetic linear contactless displacement (PLCD) sensor is a new type of displacement sensor operating on the magnetic inductive principle. It has many excellent properties and has already been used for many applications. In this article a Micro-PLCD sensor which can be used for microelectromechanical system (MEMS) measurements is designed and simulated with the CST EM STUDIO® software, including building a virtual model, magnetostatic calculations, low frequency calculations, steady current calculations and thermal calculations. The influence of some important parameters such as air gap dimension, working frequency, coil current and eddy currents etc. is studied in depth. PMID:22163663
Combined simulation of a micro permanent magnetic linear contactless displacement sensor.
Gao, Jing; Müller, Wolfgang F O; Greiner, Felix; Eicher, Dirk; Weiland, Thomas; Schlaak, Helmut F
2010-01-01
The permanent magnetic linear contactless displacement (PLCD) sensor is a new type of displacement sensor operating on the magnetic inductive principle. It has many excellent properties and has already been used for many applications. In this article a Micro-PLCD sensor which can be used for microelectromechanical system (MEMS) measurements is designed and simulated with the CST EM STUDIO(®) software, including building a virtual model, magnetostatic calculations, low frequency calculations, steady current calculations and thermal calculations. The influence of some important parameters such as air gap dimension, working frequency, coil current and eddy currents etc. is studied in depth. PMID:22163663
NASA Astrophysics Data System (ADS)
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
NASA Astrophysics Data System (ADS)
Pei, J.-S.; Smyth, A. W.; Kosmatopoulos, E. B.
2004-08-01
This study attempts to demystify a powerful neural network approach for modelling non-linear hysteretic systems and in turn to streamline its architecture to achieve better computational efficiency. The recently developed neural network modelling approach, the Volterra/Wiener neural network (VWNN), demonstrated its usefulness in identifying the restoring forces for hysteretic systems in an off-line or even in an adaptive (on-line) mode, however, the mechanism of how and why it works has not been thoroughly explored especially in terms of a physical interpretation. Artificial neural network are often treated as "black box" modelling tools, in contrast, here the authors carry out a detailed analysis in terms of problem formulation and network architecture to explore the inner workings of this neural network. Based on the understanding of the dynamics of hysteretic systems, some simplifications and modifications are made to the original VWNN in predicting accelerations of hysteretic systems under arbitrary force excitations. Through further examination of the algorithm related to the VWNN applications, the efficiency of the previously published approach is improved by reducing the number of the hidden nodes without affecting the modelling accuracy of the network. One training example is presented to illustrate the application of the VWNN; and another is provided to demonstrate that the VWNN is able to yield a unique set of weights when the values of the controlling design parameters are fixed. The practical issue of how to choose the values of these important parameters is discussed to aid engineering applications.
Lee, Dongyul; Lee, Chaewoo
2014-01-01
The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm. PMID:25276862
Lee, Chaewoo
2014-01-01
The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm. PMID:25276862
NASA Astrophysics Data System (ADS)
Grayver, Alexander V.; Kuvshinov, Alexey V.
2016-02-01
This paper presents a methodology to sample equivalence domain (ED) in non-linear PDE-constrained inverse problems. For this purpose, we first applied state-of-the-art stochastic optimization algorithm called Covariance Matrix Adaptation Evolution Strategy (CMAES) to identify low misfit regions of the model space. These regions were then randomly sampled to create an ensemble of equivalent models and quantify uncertainty. CMAES is aimed at exploring model space globally and is robust on very ill-conditioned problems. We show that the number of iterations required to converge grows at a moderate rate with respect to number of unknowns and the algorithm is embarrassingly parallel. We formulated the problem by using the generalized Gaussian distribution. This enabled us to seamlessly use arbitrary norms for residual and regularization terms. We show that various regularization norms facilitate studying different classes of equivalent solutions. We further show how performance of the standard Metropolis-Hastings Markov chain Monte Carlo (MCMC) algorithm can be substantially improved by using information CMAES provides. This methodology was tested by using individual and joint inversions of Magneotelluric, Controlled-source Electromagnetic (EM) and Global EM induction data.
Resveratrol and its combination with α-tocopherol mediate salt adaptation in citrus seedlings.
Kostopoulou, Zacharoula; Therios, Ioannis; Molassiotis, Athanassios
2014-05-01
Resveratrol, a phytoalexin found in red wine, has the potential to impact a variety of human diseases but its function in plants exposed to stressful conditions is still unknown. In the present study the effect of exogenous application of resveratrol (Res), α-tocopherol (α-Toc) and their combination (Res+α-Toc) in salt adaptation of citrus seedlings was investigated. It was found that Res, α-Toc or Res+α-Toc treatments reduced NaCl-derived membrane permeability (EL), lipid peroxidation (MDA) and pigments degradation, whereas companied Res and α-Toc application also reduced H2O2 accumulation in leaves and restored the reduction of photosynthesis induced by NaCl. Application of Res under salinity retained Cl- in roots while Res+α-Toc reduced the translocation of Na+ and Cl- to leaves. Carbohydrates and proline, phenols, total ascorbic acid and glutathione were remarkably affected by NaCl as well as by chemical treatments in leaves and roots of citrus. NaCl treatment increased the activity of superoxide dismutase (SOD), ascorbate peroxidase (APX), peroxidase (POD), glutathione reductase (GR), polyphenol oxidase (PPO) in leaves while SOD and POD activities were decreased in roots by this treatment. Also, Res, α-Toc or Res+α-Toc treatments displayed tissue specific activation or deactivation of the antioxidant enzymes. Overall, this work revealed a new functional role of Res in plants and provided evidence that the interplay of between Res and α-Toc is involved in salinity adaptation. PMID:24602773
NASA Technical Reports Server (NTRS)
Schuecker, Clara; Davila, Carlos G.; Pettermann, Heinz E.
2008-01-01
The present work is concerned with modeling the non-linear response of fiber reinforced polymer laminates. Recent experimental data suggests that the non-linearity is not only caused by matrix cracking but also by matrix plasticity due to shear stresses. To capture the effects of those two mechanisms, a model combining a plasticity formulation with continuum damage has been developed to simulate the non-linear response of laminates under plane stress states. The model is used to compare the predicted behavior of various laminate lay-ups to experimental data from the literature by looking at the degradation of axial modulus and Poisson s ratio of the laminates. The influence of residual curing stresses and in-situ effect on the predicted response is also investigated. It is shown that predictions of the combined damage/plasticity model, in general, correlate well with the experimental data. The test data shows that there are two different mechanisms that can have opposite effects on the degradation of the laminate Poisson s ratio which is captured correctly by the damage/plasticity model. Residual curing stresses are found to have a minor influence on the predicted response for the cases considered here. Some open questions remain regarding the prediction of damage onset.
Corsini, Niccolò R. C. Greco, Andrea; Haynes, Peter D.; Hine, Nicholas D. M.; Molteni, Carla
2013-08-28
We present an implementation in a linear-scaling density-functional theory code of an electronic enthalpy method, which has been found to be natural and efficient for the ab initio calculation of finite systems under hydrostatic pressure. Based on a definition of the system volume as that enclosed within an electronic density isosurface [M. Cococcioni, F. Mauri, G. Ceder, and N. Marzari, Phys. Rev. Lett.94, 145501 (2005)], it supports both geometry optimizations and molecular dynamics simulations. We introduce an approach for calibrating the parameters defining the volume in the context of geometry optimizations and discuss their significance. Results in good agreement with simulations using explicit solvents are obtained, validating our approach. Size-dependent pressure-induced structural transformations and variations in the energy gap of hydrogenated silicon nanocrystals are investigated, including one comparable in size to recent experiments. A detailed analysis of the polyamorphic transformations reveals three types of amorphous structures and their persistence on depressurization is assessed.
NASA Astrophysics Data System (ADS)
Siami, Mohammad; Gholamian, Mohammad Reza; Basiri, Javad
2014-10-01
Nowadays, credit scoring is one of the most important topics in the banking sector. Credit scoring models have been widely used to facilitate the process of credit assessing. In this paper, an application of the locally linear model tree algorithm (LOLIMOT) was experimented to evaluate the superiority of its performance to predict the customer's credit status. The algorithm is improved with an aim of adjustment by credit scoring domain by means of data fusion and feature selection techniques. Two real world credit data sets - Australian and German - from UCI machine learning database were selected to demonstrate the performance of our new classifier. The analytical results indicate that the improved LOLIMOT significantly increase the prediction accuracy.
Linear Fresnel Reflector based Solar Radiation Concentrator for Combined Heating and Power
NASA Astrophysics Data System (ADS)
Chatterjee, Aveek; Bernal, Eva; Seshadri, Satya; Mayer, Oliver; Greaves, Mikal
2011-12-01
We have designed and realized a test rig to characterize concentrated solar-based CHP (combined heat and power) generator. Cost benefit analysis has been used to compare alternate technologies, which can cogenerate electrical and thermal power. We have summarized the experimental setup and methods to characterize a concentrated solar thermal (CST) unit. In this paper, we demonstrate the performance data of a concentrated solar thermal system.
NASA Astrophysics Data System (ADS)
Liu, Ruiming; Li, Xuelong; Han, Lei; Meng, Jiao
2013-03-01
For a long time, tracking IR point targets is a great challenge task. We propose a tracking framework based on template matching combined with Kalman prediction. Firstly, a novel template matching method for detecting infrared point targets is presented. Different from the classic template matching, the projection coefficients obtained from principal component analysis are used as templates and the non-linear correlation coefficient is used to measure the matching degree. The non-linear correlation can capture the higher-order statistics. So the detection performance is improved greatly. Secondly, a framework of tracking point targets, based on the proposed detection method and Kalman prediction, is developed. Kalman prediction reduces the searching region for the detection method and, in turn, the detection method provides the more precise measurement for Kalman prediction. They bring out the best in each other. Results of experiments show that this framework is competent to track infrared point targets.
NASA Astrophysics Data System (ADS)
Narayanan, S.; Sekar, P.
1995-07-01
The response of a single-degree-of-freedom (sdf) vibrating system with unsymmetrical piecewise linear stiffness subjected to combined harmonic and flow induced excitations is investigated. Motion limiting stops, different tension and compression behavior, etc., may introduce an unsymmetrical piecewise linear stiffness characteristic. A multi-harmonic balance cum Newton-Raphson procedure in conjunction with an FFT algorithm is adopted to determine the stable and unstable periodic solutions. The stability of the periodic solutions is investigated by using Floquet theory. Digital simulation results reveal periodic, quasi-periodic and chaotic motions of the system in a range of flow velocities. Mode locked oscillations with period 5 motions are found to occur in certain range of flow velocities. Bifurcation diagrams and Lyapunov exponents are also presented.
Page, Timothy F; Pelham, William E; Fabiano, Gregory A; Greiner, Andrew R; Gnagy, Elizabeth M; Hart, Katie C; Coxe, Stefany; Waxmonsky, James G; Foster, E Michael; Pelham, William E
2016-01-01
We conducted a cost analysis of the behavioral, pharmacological, and combined interventions employed in a sequential, multiple assignment, randomized, and adaptive trial investigating the sequencing and enhancement of treatment for children with attention deficit hyperactivity disorder (ADHD; Pelham et al., 201X; N = 146, 76% male, 80% Caucasian). The quantity of resources expended on each child's treatment was determined from records that listed the type, date, location, persons present, and duration of all services provided. The inputs considered were the amount of physician time, clinician time, paraprofessional time, teacher time, parent time, medication, and gasoline. Quantities of these inputs were converted into costs in 2013 USD using national wage estimates from the Bureau of Labor Statistics, the prices of 30-day supplies of prescription drugs from the national Express Scripts service, and mean fuel prices from the Energy Information Administration. Beginning treatment with a low-dose/intensity regimen of behavior modification (large-group parent training) was less costly for a school year of treatment ($961) than beginning treatment with a low dose of stimulant medication ($1,669), regardless of whether the initial treatment was intensified with a higher "dose" or if the other modality was added. Outcome data from the parent study (Pelham et al., 201X) found equivalent or superior outcomes for treatments beginning with low-intensity behavior modification compared to intervention beginning with medication. Combined with the present analyses, these findings suggest that initiating treatment with behavior modification rather than medication is the more cost-effective option for children with ADHD. PMID:26808137
NASA Astrophysics Data System (ADS)
Corsini, Niccolò R. C.; Greco, Andrea; Hine, Nicholas D. M.; Molteni, Carla; Haynes, Peter D.
2013-08-01
We present an implementation in a linear-scaling density-functional theory code of an electronic enthalpy method, which has been found to be natural and efficient for the ab initio calculation of finite systems under hydrostatic pressure. Based on a definition of the system volume as that enclosed within an electronic density isosurface [M. Cococcioni, F. Mauri, G. Ceder, and N. Marzari, Phys. Rev. Lett. 94, 145501 (2005)], 10.1103/PhysRevLett.94.145501, it supports both geometry optimizations and molecular dynamics simulations. We introduce an approach for calibrating the parameters defining the volume in the context of geometry optimizations and discuss their significance. Results in good agreement with simulations using explicit solvents are obtained, validating our approach. Size-dependent pressure-induced structural transformations and variations in the energy gap of hydrogenated silicon nanocrystals are investigated, including one comparable in size to recent experiments. A detailed analysis of the polyamorphic transformations reveals three types of amorphous structures and their persistence on depressurization is assessed.
Corsini, Niccolò R C; Greco, Andrea; Hine, Nicholas D M; Molteni, Carla; Haynes, Peter D
2013-08-28
We present an implementation in a linear-scaling density-functional theory code of an electronic enthalpy method, which has been found to be natural and efficient for the ab initio calculation of finite systems under hydrostatic pressure. Based on a definition of the system volume as that enclosed within an electronic density isosurface [M. Cococcioni, F. Mauri, G. Ceder, and N. Marzari, Phys. Rev. Lett. 94, 145501 (2005)], it supports both geometry optimizations and molecular dynamics simulations. We introduce an approach for calibrating the parameters defining the volume in the context of geometry optimizations and discuss their significance. Results in good agreement with simulations using explicit solvents are obtained, validating our approach. Size-dependent pressure-induced structural transformations and variations in the energy gap of hydrogenated silicon nanocrystals are investigated, including one comparable in size to recent experiments. A detailed analysis of the polyamorphic transformations reveals three types of amorphous structures and their persistence on depressurization is assessed. PMID:24006984
Obtaining a linear combination of the principal components of a matrix on quantum computers
NASA Astrophysics Data System (ADS)
Daskin, Ammar
2016-07-01
Principal component analysis is a multivariate statistical method frequently used in science and engineering to reduce the dimension of a problem or extract the most significant features from a dataset. In this paper, using a similar notion to the quantum counting, we show how to apply the amplitude amplification together with the phase estimation algorithm to an operator in order to procure the eigenvectors of the operator associated to the eigenvalues defined in the range [ a, b] , where a and b are real and 0 ≤ a ≤ b ≤ 1 . This makes possible to obtain a combination of the eigenvectors associated with the largest eigenvalues and so can be used to do principal component analysis on quantum computers.
NASA Technical Reports Server (NTRS)
Davies, Misty D.; Gundy-Burlet, Karen
2010-01-01
A useful technique for the validation and verification of complex flight systems is Monte Carlo Filtering -- a global sensitivity analysis that tries to find the inputs and ranges that are most likely to lead to a subset of the outputs. A thorough exploration of the parameter space for complex integrated systems may require thousands of experiments and hundreds of controlled and measured variables. Tools for analyzing this space often have limitations caused by the numerical problems associated with high dimensionality and caused by the assumption of independence of all of the dimensions. To combat both of these limitations, we propose a technique that uses a combination of the original variables with the derived variables obtained during a principal component analysis.
Panov, Vladimir G; Varaksin, Anatoly N
2016-02-01
Within the framework of the response surface linear model with a cross term, i.e. a model of the type Y(x1, x2) = b0 + b1x1 + b2x2 + b12x1x2 (hyperbolic paraboloid), a complete solution of identification of combined action types of two toxicants x1 and x2 is presented. It is shown that the type of combined effect in this model is determined by two factors: the direction in which the toxicants act (unidirectional or oppositely directed), and the position of the saddle point S of a hyperbolic paraboloid. For unidirectional actions of toxicants, already-known ways to identify the type of combined effect (including a shape of the isobole: concave-up or concave-down) provided identical and unambiguous answers regarding the type of combined effect (antagonism or synergism). For oppositely directed actions of toxicants, the shape of the isobole (concave-up or concave-down) did not allow us to determine the type of combined action type unambiguously. We show that in both cases (unidirectional or oppositely directed actions of toxicants) the signs of the model coefficients b1, b2 and b12, in conjunction with the coordinates of the saddle point S help unambiguously identify the type of combined action by comparing the observed effect with the zero interaction response surface. An atlas of all possibly combined action types for two toxicants for the hyperbolic paraboloid model was created. Applications of the developed formalism to experimental data are provided. PMID:26894918
A Combined MPI-CUDA Parallel Solution of Linear and Nonlinear Poisson-Boltzmann Equation
Colmenares, José; Galizia, Antonella; Ortiz, Jesús; Clematis, Andrea; Rocchia, Walter
2014-01-01
The Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational structural biology to estimate the electrostatic energetic component of the assembly of molecular biological systems. In the last decades, the amount of data concerning proteins and other biological macromolecules has remarkably increased. To fruitfully exploit these data, a huge computational power is needed as well as software tools capable of exploiting it. It is therefore necessary to move towards high performance computing and to develop proper parallel implementations of already existing and of novel algorithms. Nowadays, workstations can provide an amazing computational power: up to 10 TFLOPS on a single machine equipped with multiple CPUs and accelerators such as Intel Xeon Phi or GPU devices. The actual obstacle to the full exploitation of modern heterogeneous resources is efficient parallel coding and porting of software on such architectures. In this paper, we propose the implementation of a full Poisson-Boltzmann solver based on a finite-difference scheme using different and combined parallel schemes and in particular a mixed MPI-CUDA implementation. Results show great speedups when using the two schemes, achieving an 18.9x speedup using three GPUs. PMID:25013789
A combined MPI-CUDA parallel solution of linear and nonlinear Poisson-Boltzmann equation.
Colmenares, José; Galizia, Antonella; Ortiz, Jesús; Clematis, Andrea; Rocchia, Walter
2014-01-01
The Poisson-Boltzmann equation models the electrostatic potential generated by fixed charges on a polarizable solute immersed in an ionic solution. This approach is often used in computational structural biology to estimate the electrostatic energetic component of the assembly of molecular biological systems. In the last decades, the amount of data concerning proteins and other biological macromolecules has remarkably increased. To fruitfully exploit these data, a huge computational power is needed as well as software tools capable of exploiting it. It is therefore necessary to move towards high performance computing and to develop proper parallel implementations of already existing and of novel algorithms. Nowadays, workstations can provide an amazing computational power: up to 10 TFLOPS on a single machine equipped with multiple CPUs and accelerators such as Intel Xeon Phi or GPU devices. The actual obstacle to the full exploitation of modern heterogeneous resources is efficient parallel coding and porting of software on such architectures. In this paper, we propose the implementation of a full Poisson-Boltzmann solver based on a finite-difference scheme using different and combined parallel schemes and in particular a mixed MPI-CUDA implementation. Results show great speedups when using the two schemes, achieving an 18.9x speedup using three GPUs. PMID:25013789
Hoppe, Travis; Minton, Allen P.
2015-01-01
The formation of linear protein fibrils has previously been shown to be enhanced by volume exclusion or crowding in the presence of a high concentration of chemically inert protein or polymer, and by adsorption to membrane surfaces. An equilibrium mesoscopic model for the combined effect of both crowding and adsorption upon the fibrillation of a dilute tracer protein is presented. The model exhibits behavior that differs qualitatively from that observed in the presence of crowding or adsorption alone. The model predicts that in a crowded solution, at critical values of the volume fraction of crowder or intrinsic energy of the tracer-wall interaction, the tracer protein will undergo an extremely cooperative transition—approaching a step function—from existence as a slightly self-associated species in solution to existence as a highly self-associated and completely adsorbed species. Criteria for a valid experimental test of these predictions are presented. PMID:25692600
NASA Technical Reports Server (NTRS)
Smith, Timothy D.; Steffen, Christopher J., Jr.; Yungster, Shaye; Keller, Dennis J.
1998-01-01
The all rocket mode of operation is shown to be a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. An axisymmetric RBCC engine was used to determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and multiple linear regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inlet diameter ratio. A perfect gas computational fluid dynamics analysis, using both the Spalart-Allmaras and k-omega turbulence models, was performed with the NPARC code to obtain values of vacuum specific impulse. Results from the multiple linear regression analysis showed that for both the full flow and gas generator configurations increasing mixer-ejector area ratio and rocket area ratio increase performance, while increasing mixer-ejector inlet area ratio and mixer-ejector length-to-diameter ratio decrease performance. Increasing injected secondary flow increased performance for the gas generator analysis, but was not statistically significant for the full flow analysis. Chamber pressure was found to be not statistically significant.
An adaptive three-dimensional RHT-splines formulation in linear elasto-statics and elasto-dynamics
NASA Astrophysics Data System (ADS)
Nguyen-Thanh, N.; Muthu, J.; Zhuang, X.; Rabczuk, T.
2014-02-01
An adaptive three-dimensional isogeometric formulation based on rational splines over hierarchical T-meshes (RHT-splines) for problems in elasto-statics and elasto-dynamics is presented. RHT-splines avoid some short-comings of NURBS-based formulations; in particular they allow for adaptive h-refinement with ease. In order to drive the adaptive refinement, we present a recovery-based error estimator for RHT-splines. The method is applied to several problems in elasto-statics and elasto-dynamics including three-dimensional modeling of thin structures. The results are compared to analytical solutions and results of NURBS based isogeometric formulations.
An Enhanced Approach to Combine Item Response Theory with Cognitive Diagnosis in Adaptive Testing
ERIC Educational Resources Information Center
Wang, Chun; Zheng, Chanjin; Chang, Hua-Hua
2014-01-01
Computerized adaptive testing offers the possibility of gaining information on both the overall ability and cognitive profile in a single assessment administration. Some algorithms aiming for these dual purposes have been proposed, including the shadow test approach, the dual information method (DIM), and the constraint weighted method. The…
Pierce, Simon; Brusa, Guido; Sartori, Matteo; Cerabolini, Bruno E. L.
2012-01-01
Background and Aims Hydrophytes generally exhibit highly acquisitive leaf economics. However, a range of growth forms is evident, from small, free-floating and rapidly growing Lemniden to large, broad-leaved Nymphaeiden, denoting variability in adaptive strategies. Traits used to classify adaptive strategies in terrestrial species, such as canopy height, are not applicable to hydrophytes. We hypothesize that hydrophyte leaf size traits and economics exhibit sufficient overlap with terrestrial species to allow a common classification of plant functional types, sensu Grime's CSR theory. Methods Leaf morpho-functional traits were measured for 61 species from 47 water bodies in lowland continental, sub-alpine and alpine bioclimatic zones in southern Europe and compared against the full leaf economics spectrum and leaf size range of terrestrial herbs, and between hydrophyte growth forms. Key Results Hydrophytes differed in the ranges and mean values of traits compared with herbs, but principal components analysis (PCA) demonstrated that both groups shared axes of trait variability: PCA1 encompassed size variation (area and mass), and PCA2 ranged from relatively dense, carbon-rich leaves to nitrogen-rich leaves of high specific leaf area (SLA). Most growth forms exhibited trait syndromes directly equivalent to herbs classified as R adapted, although Nymphaeiden ranged between C and SR adaptation. Conclusions Our findings support the hypothesis that hydrophyte adaptive strategy variation reflects fundamental trade-offs in economics and size that govern all plants, and that hydrophyte adaptive strategies can be directly compared with terrestrial species by combining leaf economics and size traits. PMID:22337079
2010-01-01
Background Mortality due to cannibalism in laying hens is a difficult trait to improve genetically, because censoring is high (animals still alive at the end of the testing period) and it may depend on both the individual itself and the behaviour of its group members, so-called associative effects (social interactions). To analyse survival data, survival analysis can be used. However, it is not possible to include associative effects in the current software for survival analysis. A solution could be to combine survival analysis and a linear animal model including associative effects. This paper presents a two-step approach (2STEP), combining survival analysis and a linear animal model including associative effects (LAM). Methods Data of three purebred White Leghorn layer lines from Institut de Sélection Animale B.V., a Hendrix Genetics company, were used in this study. For the statistical analysis, survival data on 16,780 hens kept in four-bird cages with intact beaks were used. Genetic parameters for direct and associative effects on survival time were estimated using 2STEP. Cross validation was used to compare 2STEP with LAM. LAM was applied directly to estimate genetic parameters for social effects on observed survival days. Results Using 2STEP, total heritable variance, including both direct and associative genetic effects, expressed as the proportion of phenotypic variance, ranged from 32% to 64%. These results were substantially larger than when using LAM. However, cross validation showed that 2STEP gave approximately the same survival curves and rank correlations as LAM. Furthermore, cross validation showed that selection based on both direct and associative genetic effects, using either 2STEP or LAM, gave the best prediction of survival time. Conclusion It can be concluded that 2STEP can be used to estimate genetic parameters for direct and associative effects on survival time in laying hens. Using 2STEP increased the heritable variance in survival time
NASA Astrophysics Data System (ADS)
Erdogan, Eren; Durmaz, Murat; Liang, Wenjing; Kappelsberger, Maria; Dettmering, Denise; Limberger, Marco; Schmidt, Michael; Seitz, Florian
2015-04-01
This project focuses on the development of a novel near real-time data adaptive filtering framework for global modeling of the vertical total electron content (VTEC). Ionospheric data can be acquired from various space geodetic observation techniques such as GNSS, altimetry, DORIS and radio occultation. The project aims to model the temporal and spatial variations of the ionosphere by a combination of these techniques in an adaptive data assimilation framework, which utilizes appropriate basis functions to represent the VTEC. The measurements naturally have inhomogeneous data distribution both in time and space. Therefore, integrating the aforementioned observation techniques into data adaptive basis selection methods (e.g. Multivariate Adaptive Regression B-Splines) with recursive filtering (e.g. Kalman filtering) to model the daily global ionosphere may deliver important improvements over classical estimation methods. Since ionospheric inverse problems are ill-posed, a suitable regularization procedure might stabilize the solution. In this contribution we present first results related to the selected evaluation procedure. Comparisons made with respect to applicability, efficiency, accuracy, and numerical efforts.
NASA Astrophysics Data System (ADS)
Samhouri, M.; Al-Ghandoor, A.; Fouad, R. H.
2009-08-01
In this study two techniques, for modeling electricity consumption of the Jordanian industrial sector, are presented: (i) multivariate linear regression and (ii) neuro-fuzzy models. Electricity consumption is modeled as function of different variables such as number of establishments, number of employees, electricity tariff, prevailing fuel prices, production outputs, capacity utilizations, and structural effects. It was found that industrial production and capacity utilization are the most important variables that have significant effect on future electrical power demand. The results showed that both the multivariate linear regression and neuro-fuzzy models are generally comparable and can be used adequately to simulate industrial electricity consumption. However, comparison that is based on the square root average squared error of data suggests that the neuro-fuzzy model performs slightly better for future prediction of electricity consumption than the multivariate linear regression model. Such results are in full agreement with similar work, using different methods, for other countries.
NASA Astrophysics Data System (ADS)
Matéo, Tony; Mofid, Yassine; Grégoire, Jean-Marc; Ossant, Frédéric
In ophtalmic ultrasonography, axial B-scans are seriously deteriorated owing to the presence of the crystalline lens. This strongly aberrating medium affects both spatial and contrast resolution and causes important distortions. To deal with this issue, an adapted beamforming (BF) has been developed and experimented with a 20 MHz linear array working with a custom US research scanner. The adapted BF computes focusing delays that compensate for crystalline phase aberration, including refraction effects. This BF was tested in vitro by imaging a wire phantom through an eye phantom consisting of a synthetic gelatin lens, shaped according to the unaccommodated state of an adult human crystalline lens, anatomically set up in an appropriate liquid (turpentine) to approach the in vivo velocity ratio. Both image quality and fidelity from the adapted BF were assessed and compared with conventional delay-and-sum BF over the aberrating medium. Results showed 2-fold improvement of the lateral resolution, greater sensitivity and 90% reduction of the spatial error (from 758 μm to 76 μm) with adapted BF compared to conventional BF. Finally, promising first ex vivo axial B-scans of a human eye are presented.
Koh, Doo-Yeol; Kim, Young-Kook; Kim, Kyung-Soo; Kim, Soohyun
2013-08-01
In mobile robotics, obtaining stable image of a mounted camera is crucial for operating a mobile system to complete given tasks. This note presents the development of a high-speed image stabilizing device using linear shaft actuator, and a new image stabilization method inspired by human gaze stabilization process known as vestibulo-ocular reflex (VOR). In the proposed control, the reference is adaptively adjusted by the VOR adaptation control to reject residual vibration of a camera as the VOR gain converges to optimal state. Through experiments on a pneumatic vibrator, it will be shown that the proposed system is capable of stabilizing 10 Hz platform vibration, which shows potential applicability of the device to a high-speed mobile robot. PMID:24007125
NASA Astrophysics Data System (ADS)
Koh, Doo-Yeol; Kim, Young-Kook; Kim, Kyung-Soo; Kim, Soohyun
2013-08-01
In mobile robotics, obtaining stable image of a mounted camera is crucial for operating a mobile system to complete given tasks. This note presents the development of a high-speed image stabilizing device using linear shaft actuator, and a new image stabilization method inspired by human gaze stabilization process known as vestibulo-ocular reflex (VOR). In the proposed control, the reference is adaptively adjusted by the VOR adaptation control to reject residual vibration of a camera as the VOR gain converges to optimal state. Through experiments on a pneumatic vibrator, it will be shown that the proposed system is capable of stabilizing 10 Hz platform vibration, which shows potential applicability of the device to a high-speed mobile robot.
Abd, Haider; Din, Norashidah Md.; Al-Mansoori, M. H.; Abdullah, F.; Fadhil, H. A.
2014-01-01
A new approach to suppressing the four-wave mixing (FWM) crosstalk by using the pairing combinations of differently linear-polarized optical signals was investigated. The simulation was conducted using a four-channel system, and the total data rate was 40 Gb/s. A comparative study on the suppression of FWM for existing and suggested techniques was conducted by varying the input power from 2 dBm to 14 dBm. The robustness of the proposed technique was examined with two types of optical fiber, namely, single-mode fiber (SMF) and dispersion-shifted fiber (DSF). The FWM power drastically reduced to less than −68 and −25 dBm at an input power of 14 dBm, when the polarization technique was conducted for SMF and DSF, respectively. With the conventional method, the FWM powers were, respectively, −56 and −20 dBm. The system performance greatly improved with the proposed polarization approach, where the bit error rates (BERs) at the first channel were 2.57 × 10−40 and 3.47 × 10−29 at received powers of −4.90 and −13.84 dBm for SMF and DSF, respectively. PMID:24883364
On the combination of a linear field free trap with a time-of-flight mass spectrometer
NASA Astrophysics Data System (ADS)
Luca, Alfonz; Schlemmer, Stephan; Čermák, Ivo; Gerlich, Dieter
2001-07-01
A new instrument has been developed which combines a rf ring electrode trap and a time-of-flight mass spectrometer (TOF-MS). The wide field free storage volume of such a trap enables the study of low temperature ion-molecule collisions; however it is not straightforward to match the nonlocalized ion cloud to the TOF-MS. For obtaining sufficient mass resolution, a special pulse sequence has been developed to transfer the ions from the whole trap volume to a small region in the vicinity of the exit electrode. Additional compression is achieved via buffer gas relaxation prior to extracting the ions. Using a linear flight path of 57 cm, a mass resolution of about 50 is routinely achieved. The mass range of the whole instrument, which is determined by the operating conditions both of the trap and the TOF-MS, has been estimated to be 3-700 u. The actual characteristics of the instrument such as mass range, resolution, and dynamical range have been determined and the results have been analyzed. As a typical application of the new instrument, the growth of (CO)n+ cluster ions is investigated at 80 K. The simultaneous detection of all masses of interest as a function of storage time allows one to follow in detail the kinetics of the reaction and loss processes involved. Limitations of the method are discussed together with ways to overcome them in an improved setup.
Samal, Pramoda Kumar; Jain, Pankaj; Saha, Rajib; Prunet, Simon; Souradeep, Tarun
2010-05-01
We estimate cosmic microwave background (CMB) polarization and temperature power spectra using Wilkinson Microwave Anisotropy Probe (WMAP) 5 year foreground contaminated maps. The power spectrum is estimated by using a model-independent method, which does not utilize directly the diffuse foreground templates nor the detector noise model. The method essentially consists of two steps: (1) removal of diffuse foregrounds contamination by making linear combination of individual maps in harmonic space and (2) cross-correlation of foreground cleaned maps to minimize detector noise bias. For the temperature power spectrum we also estimate and subtract residual unresolved point source contamination in the cross-power spectrum using the point source model provided by the WMAP science team. Our TT, TE, and EE power spectra are in good agreement with the published results of the WMAP science team. We perform detailed numerical simulations to test for bias in our procedure. We find that the bias is small in almost all cases. A negative bias at low l in TT power spectrum has been pointed out in an earlier publication. We find that the bias-corrected quadrupole power (l(l + 1)C{sub l} /2{pi}) is 532 {mu}K{sup 2}, approximately 2.5 times the estimate (213.4 {mu}K{sup 2}) made by the WMAP team.
NASA Astrophysics Data System (ADS)
Magga, Zoi; Tzovolou, Dimitra N.; Theodoropoulou, Maria A.; Tsakiroglou, Christos D.
2012-03-01
The risk assessment of groundwater pollution by pesticides may be based on pesticide sorption and biodegradation kinetic parameters estimated with inverse modeling of datasets from either batch or continuous flow soil column experiments. In the present work, a chemical non-equilibrium and non-linear 2-site sorption model is incorporated into solute transport models to invert the datasets of batch and soil column experiments, and estimate the kinetic sorption parameters for two pesticides: N-phosphonomethyl glycine (glyphosate) and 2,4-dichlorophenoxy-acetic acid (2,4-D). When coupling the 2-site sorption model with the 2-region transport model, except of the kinetic sorption parameters, the soil column datasets enable us to estimate the mass-transfer coefficients associated with solute diffusion between mobile and immobile regions. In order to improve the reliability of models and kinetic parameter values, a stepwise strategy that combines batch and continuous flow tests with adequate true-to-the mechanism analytical of numerical models, and decouples the kinetics of purely reactive steps of sorption from physical mass-transfer processes is required.
Presentation based on the following abstract: Chemical mixtures risk assessment methods are routinely used. To address combined chemical and nonchemical stressors, component-based approaches may be applicable, depending on the toxic action among diverse stressors. Such methods a...
Rajani, Karishma; Parrish, Christopher; Kottke, Timothy; Thompson, Jill; Zaidi, Shane; Ilett, Liz; Shim, Kevin G; Diaz, Rosa-Maria; Pandha, Hardev; Harrington, Kevin; Coffey, Matt; Melcher, Alan; Vile, Richard
2016-02-01
Oncolytic reovirus can be delivered both systemically and intratumorally, in both preclinical models and in early phase clinical trials. Reovirus has direct oncolytic activity against a variety of tumor types and antitumor activity is directly associated with immune activation by virus replication in tumors. Immune mechanisms of therapy include both innate immune activation against virally infected tumor cells, and the generation of adaptive antitumor immune responses as a result of in vivo priming against tumor-associated antigens. We tested the combination of local oncolytic reovirus therapy with systemic immune checkpoint inhibition. We show that treatment of subcutaneous B16 melanomas with a combination of intravenous (i.v.) anti-PD-1 antibody and intratumoral (i.t.) reovirus significantly enhanced survival of mice compared to i.t. reovirus (P < 0.01) or anti-PD-1 therapy alone. In vitro immune analysis demonstrated that checkpoint inhibition improved the ability of NK cells to kill reovirus-infected tumor cells, reduced T(reg) activity, and increased the adaptive CD8(+) T-cell-dependent antitumor T-cell response. PD-1 blockade also enhanced the antiviral immune response but through effector mechanisms which overlapped with but also differed from those affecting the antitumor response. Therefore, combination with checkpoint inhibition represents a readily translatable next step in the clinical development of reovirus viroimmunotherapy. PMID:26310630
Digital timing recovery combined with adaptive equalization for optical coherent receivers
NASA Astrophysics Data System (ADS)
Zhou, Xian; Chen, Xue; Zhou, Weiqing; Fan, Yangyang; Zhu, Hai; Li, Zhiyu
2009-11-01
We propose a novel equalization and timing recovery scheme, which adds an adaptive butterfly-structured equalizer in an all-digital timing recovery loop, for polarization multiplexing (POLMUX) coherent receivers. It resolves an incompatible problem that digital equalizer requires the timing recovered (synchronous) signal and Gardner timing-error detection algorithm requires the equalized signal because of its small tolerance on dispersion. This joint module can complete synchronization, equalization and polarization de-multiplexing simultaneously without any extra computational cost. Finally, we demonstrate the good performance of the new scheme in a 112-Gbit/s POLMUX-NRZ-DQPSK digital optical coherent receiver.
Wong, James R.; Grimm, Lisa; Oren, Reva
2005-02-01
Purpose: Multiple studies have indicated that the prostate is not stationary and can move as much as 2 cm. Such prostate movements are problematic for intensity-modulated radiotherapy, with its associated tight margins and dose escalation. Because of these intrinsic daily uncertainties, a relative generous 'margin' is necessary to avoid marginal misses. Using the CT-linear accelerator combination in the treatment suite (Primatom, Siemens), we found that the daily intrinsic prostate movements can be easily corrected before each radiotherapy session. Dosimetric calculations were performed to evaluate the amount of discrepancy of dose to the target if no correction was done for prostate movement. Methods and materials: The Primatom consists of a Siemens Somatom CT scanner and a Siemens Primus linear accelerator installed in the same treatment suite and sharing a common table/couch. The patient is scanned by the CT scanner, which is movable on a pair of horizontal rails. During scanning, the couch does not move. The exact location of the prostate, seminal vesicles, and rectum are identified and localized. These positions are then compared with the planned positions. The daily movement of the prostate and rectum were corrected for and a new isocenter derived. The patient was treated immediately using the new isocenter. Results: Of the 108 patients with primary prostate cancer studied, 540 consecutive daily CT scans were performed during the last part of the cone down treatment. Of the 540 scans, 46% required no isocenter adjustments for the AP-PA direction, 54% required a shift of {>=}3 mm, 44% required a shift of >5 mm, and 15% required a shift of >10 mm. In the superoinferior direction, 27% required a shift of >3 mm, 25% required a shift of >5 mm, and 4% required a shift of >10 mm. In the right-left direction, 34% required a shift of >3 mm, 24% required a shift of >5 mm, and 5% required a shift of >10 mm. Dosimetric calculations for a typical case of prostate cancer
NASA Astrophysics Data System (ADS)
Bekri, Eleni; Yannopoulos, Panayotis; Disse, Markus
2013-04-01
In the present study, a combined linear programming methodology, based on Li et al. (2010) and Bekri et al. (2012), is employed for optimizing water allocation under uncertain system conditions in the Alfeios River Basin, in Greece. The Alfeios River is a water resources system of great natural, ecological, social and economic importance for Western Greece, since it has the longest and highest flow rate watercourse in the Peloponnisos region. Moreover, the river basin was exposed in the last decades to a plethora of environmental stresses (e.g. hydrogeological alterations, intensively irrigated agriculture, surface and groundwater overexploitation and infrastructure developments), resulting in the degradation of its quantitative and qualitative characteristics. As in most Mediterranean countries, water resource management in Alfeios River Basin has been focused up to now on an essentially supply-driven approach. It is still characterized by a lack of effective operational strategies. Authority responsibility relationships are fragmented, and law enforcement and policy implementation are weak. The present regulated water allocation puzzle entails a mixture of hydropower generation, irrigation, drinking water supply and recreational activities. Under these conditions its water resources management is characterised by high uncertainty and by vague and imprecise data. The considered methodology has been developed in order to deal with uncertainties expressed as either probability distributions, or/and fuzzy boundary intervals, derived by associated α-cut levels. In this framework a set of deterministic submodels is studied through linear programming. The ad hoc water resources management and alternative management patterns in an Alfeios subbasin are analyzed and evaluated under various scenarios, using the above mentioned methodology, aiming to promote a sustainable and equitable water management. Li, Y.P., Huang, G.H. and S.L., Nie, (2010), Planning water resources
Leiser, Owen P.; Merkley, Eric D.; Clowers, Brian H.; Kaiser, Brooke LD; Lin, Andy; Hutchison, Janine R.; Melville, Angela M.; Wagner, David M.; Keim, Paul S.; Foster, Jeff; Kreuzer, Helen W.
2015-11-24
The bacterial pathogen Yersinia pestis, the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a Parallel Serial Passage Experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail, pepA, and zwf, suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS-based proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism, envelope biogenesis, iron storage and acquisition, and a type VI secretion system. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement.
Combining Environment-Driven Adaptation and Task-Driven Optimisation in Evolutionary Robotics
Haasdijk, Evert; Bredeche, Nicolas; Eiben, A. E.
2014-01-01
Embodied evolutionary robotics is a sub-field of evolutionary robotics that employs evolutionary algorithms on the robotic hardware itself, during the operational period, i.e., in an on-line fashion. This enables robotic systems that continuously adapt, and are therefore capable of (re-)adjusting themselves to previously unknown or dynamically changing conditions autonomously, without human oversight. This paper addresses one of the major challenges that such systems face, viz. that the robots must satisfy two sets of requirements. Firstly, they must continue to operate reliably in their environment (viability), and secondly they must competently perform user-specified tasks (usefulness). The solution we propose exploits the fact that evolutionary methods have two basic selection mechanisms–survivor selection and parent selection. This allows evolution to tackle the two sets of requirements separately: survivor selection is driven by the environment and parent selection is based on task-performance. This idea is elaborated in the Multi-Objective aNd open-Ended Evolution (monee) framework, which we experimentally validate. Experiments with robotic swarms of 100 simulated e-pucks show that monee does indeed promote task-driven behaviour without compromising environmental adaptation. We also investigate an extension of the parent selection process with a ‘market mechanism’ that can ensure equitable distribution of effort over multiple tasks, a particularly pressing issue if the environment promotes specialisation in single tasks. PMID:24901702
Combining environment-driven adaptation and task-driven optimisation in evolutionary robotics.
Haasdijk, Evert; Bredeche, Nicolas; Eiben, A E
2014-01-01
Embodied evolutionary robotics is a sub-field of evolutionary robotics that employs evolutionary algorithms on the robotic hardware itself, during the operational period, i.e., in an on-line fashion. This enables robotic systems that continuously adapt, and are therefore capable of (re-)adjusting themselves to previously unknown or dynamically changing conditions autonomously, without human oversight. This paper addresses one of the major challenges that such systems face, viz. that the robots must satisfy two sets of requirements. Firstly, they must continue to operate reliably in their environment (viability), and secondly they must competently perform user-specified tasks (usefulness). The solution we propose exploits the fact that evolutionary methods have two basic selection mechanisms-survivor selection and parent selection. This allows evolution to tackle the two sets of requirements separately: survivor selection is driven by the environment and parent selection is based on task-performance. This idea is elaborated in the Multi-Objective aNd open-Ended Evolution (monee) framework, which we experimentally validate. Experiments with robotic swarms of 100 simulated e-pucks show that monee does indeed promote task-driven behaviour without compromising environmental adaptation. We also investigate an extension of the parent selection process with a 'market mechanism' that can ensure equitable distribution of effort over multiple tasks, a particularly pressing issue if the environment promotes specialisation in single tasks. PMID:24901702
Fitzgerald, J P S; Word, R C; Könenkamp, R
2012-04-01
We present a theoretical analysis of an electrostatic triode mirror combined with an einzel lens for the correction of spherical and chromatic aberration. We show that this device adaptively corrects spherical and chromatic aberration simultaneously and independently. Chromatic aberration can be compensated over a relative range of -38% to +100%, and spherical aberration over ±100% range. We compare the analytic calculation with a numerical simulation and show that the two descriptions agree to within 5% in the relevant operating regime of the device. PMID:22459116
Dong, Shan; Jacob, Tim J C
2016-03-15
Bright light therapy has been shown to have a positive impact on seasonal affective disorder (SAD), depression and anxiety. Smell has also has been shown to have effects on mood, stress, anxiety and depression. The objective of this study was to investigate the effect of the combination of light and smell in a non-adaptive cycle. Human subjects were given smell (lemon, lavender or peppermint) and light stimuli in a triangular wave (60scycle) for 15min. Blood pressure and heart rate were monitored before and after each session for 5 consecutive days and a Profile of Mood States (POMS) test was administered before and after the sensory stimulation on days 1, 3 and 5. The light-smell stimulus lowered blood pressure, both systolic and diastolic, and reduced heart rate for all odours compared to control. Of the two sensory stimuli, the odour stimulus contributed most to this effect. The different aromas in the light-smell combinations could be distinguished by their different effects on the mood factors with lemon inducing the greatest mood changes in Dejection-Depression, Anger-Hostility, Tension-Anxiety. In conclusion, combined light and smell stimulation was effective in lowering blood pressure, reducing heart rate and improving mood. The combination was more effective than either smell or light stimuli alone, suggesting that a light-smell combination would be a more robust and efficacious alternative treatment for depression, anxiety and stress. PMID:26780148
A Two-Stage Combining Classifier Model for the Development of Adaptive Dialog Systems.
Griol, David; Iglesias, José Antonio; Ledezma, Agapito; Sanchis, Araceli
2016-02-01
This paper proposes a statistical framework to develop user-adapted spoken dialog systems. The proposed framework integrates two main models. The first model is used to predict the user's intention during the dialog. The second model uses this prediction and the history of dialog up to the current moment to predict the next system response. This prediction is performed with an ensemble-based classifier trained for each of the tasks considered, so that a better selection of the next system can be attained weighting the outputs of these specialized classifiers. The codification of the information and the definition of data structures to store the data supplied by the user throughout the dialog makes the estimation of the models from the training data and practical domains manageable. We describe our proposal and its application and detailed evaluation in a practical spoken dialog system. PMID:26678250
Leiser, Owen P; Merkley, Eric D; Clowers, Brian H; Deatherage Kaiser, Brooke L; Lin, Andy; Hutchison, Janine R; Melville, Angela M; Wagner, David M; Keim, Paul S; Foster, Jeffrey T; Kreuzer, Helen W
2015-01-01
The bacterial pathogen Yersinia pestis, the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a parallel serial passage experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing, LC-MS/MS proteomic analysis, and GC/MS metabolomics. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail, pepA, and zwf, suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS/MS proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism and cell envelope biogenesis. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement. PMID:26599979
Leiser, Owen P.; Merkley, Eric D.; Clowers, Brian H.; Kaiser, Brooke L. Deatherage; Lin, Andy; Hutchison, Janine R.; Melville, Angela M.; Wagner, David M.; Keim, Paul S.; Foster, Jeff; et al
2015-11-24
Here, the bacterial pathogen Yersinia pestis, the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a Parallel Serial Passage Experimentmore » (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail, pepA, and zwf, suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS-based proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism, envelope biogenesis, iron storage and acquisition, and a type VI secretion system. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement.« less
Clowers, Brian H.; Deatherage Kaiser, Brooke L.; Lin, Andy; Hutchison, Janine R.; Melville, Angela M.; Wagner, David M.; Keim, Paul S.; Foster, Jeffrey T.; Kreuzer, Helen W.
2015-01-01
The bacterial pathogen Yersinia pestis, the cause of plague in humans and animals, normally has a sylvatic lifestyle, cycling between fleas and mammals. In contrast, laboratory-grown Y. pestis experiences a more constant environment and conditions that it would not normally encounter. The transition from the natural environment to the laboratory results in a vastly different set of selective pressures, and represents what could be considered domestication. Understanding the kinds of adaptations Y. pestis undergoes as it becomes domesticated will contribute to understanding the basic biology of this important pathogen. In this study, we performed a parallel serial passage experiment (PSPE) to explore the mechanisms by which Y. pestis adapts to laboratory conditions, hypothesizing that cells would undergo significant changes in virulence and nutrient acquisition systems. Two wild strains were serially passaged in 12 independent populations each for ~750 generations, after which each population was analyzed using whole-genome sequencing, LC-MS/MS proteomic analysis, and GC/MS metabolomics. We observed considerable parallel evolution in the endpoint populations, detecting multiple independent mutations in ail, pepA, and zwf, suggesting that specific selective pressures are shaping evolutionary responses. Complementary LC-MS/MS proteomic data provide physiological context to the observed mutations, and reveal regulatory changes not necessarily associated with specific mutations, including changes in amino acid metabolism and cell envelope biogenesis. Proteomic data support hypotheses generated by genomic data in addition to suggesting future mechanistic studies, indicating that future whole-genome sequencing studies be designed to leverage proteomics as a critical complement. PMID:26599979
Chen, Baojun; Wang, Qining
2015-01-01
Affording lower-limb amputees the ability to volitionally control robotic prostheses can improve the adaptability to terrain changes as well as enhancing proprioception. However, it also increases amputees' conscious burdens for prosthesis control. Therefore, in this paper, we aim to propose a hybrid controller which combines human volitional control with the intrinsic controller on the robotic transtibial prosthesis, enabling the amputee actively controlling prosthesis with little conscious attention. In this preliminary study, a hybrid controller for adaptive slope walking was designed. A slope estimator was embedded in the intrinsic controller to estimate the ground slope of the previous step using signals measured by prosthetic sensors. And a myoelectric controller allows the amputee subject to convey slope changes to prosthetic controller by volitionally contract his residual muscles, whose electromyography signals were mapped to the slope increment. The hybrid controller combined these two results to obtain the estimated slope. One male transtibial amputee subject was recruited in this research. Experiment results showed that the intrinsic slope estimator produced satisfactory estimation results with an average absolute error of 0.70 ± 0.54 degrees. By adding amputee's volitional control, the hybrid controller is able to predict the upcoming slope changes. PMID:26737362
NASA Astrophysics Data System (ADS)
Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.
2011-04-01
Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.
NASA Astrophysics Data System (ADS)
Song, Ningfang; Luo, Xinkai; Li, Huipeng; Li, Jiao
2015-10-01
The non-linearity of the phase shifting mechanism in white light interferometry system can seriously affect the measuring accuracy of the system. In this paper, the correcting method is to combine the displacement feedback control technology with the fuzzy PID control technology. Displacement feedback control mechanism and fuzzy PID controller are designed and then try to figure it out through Matlab simulation and experiment.. The result shows that combining the displacement feedback control technology with the fuzzy PID control technology can fulfill decent overall non-linear correction in the white light interferometry measuring system. Meanwhile, the accuracy of the correction is high and the non-linearity drop from 2% to 0.1%.
Human torque velocity adaptations to sprint, endurance, or combined modes of training
NASA Technical Reports Server (NTRS)
Shealy, M. J.; Callister, R.; Dudley, G. A.; Fleck, S. J.
1992-01-01
We had groups of athletes perform sprint and endurance run training independently or concurrently for 8 weeks to examine the voluntary in vivo mechanical responses to each type of training. Pre- and posttraining angle-specific peak torque during knee extension and flexion were determined at 0, 0.84, 1.65, 2.51, 3.35, 4.19, and 5.03 radian.sec-1 and normalized for lean body mass. Knee extension torque in the sprint-trained group increased across all test velocities, the endurance-trained group increased at 2.51, 3.34, 4.19, and 5.03 radian.sec-1, and the group performing the combined training showed no change at any velocity. Knee flexion torque of the sprint and combined groups decreased at 0.84, 1.65, and 2.51 radian.sec-1. Knee flexion torque in the sprint-trained group also decreased at 0 radian.sec-1 and in the combined group at 3.34 radian.sec-1. Knee flexion torque in the endurance-trained group showed no change at any velocity of contraction. Mean knee flexion:extension ratios across the test velocities significantly decreased in the sprint-trained group. Knee extension endurance during 30 seconds of maximal contractions significantly increased in all groups. Only the sprint-trained group showed a significant increase in endurance of the knee flexors. These data suggest that changes in the voluntary in vivo mechanical characteristics of knee extensor and flexor skeletal muscles are specific to the type of run training performed.
ERIC Educational Resources Information Center
Dimitrov, Dimiter M.; Raykov, Tenko; AL-Qataee, Abdullah Ali
2015-01-01
This article is concerned with developing a measure of general academic ability (GAA) for high school graduates who apply to colleges, as well as with the identification of optimal weights of the GAA indicators in a linear combination that yields a composite score with maximal reliability and maximal predictive validity, employing the framework of…
ERIC Educational Resources Information Center
Shieh, Gwowen; Jan, Show-Li
2015-01-01
The general formulation of a linear combination of population means permits a wide range of research questions to be tested within the context of ANOVA. However, it has been stressed in many research areas that the homogeneous variances assumption is frequently violated. To accommodate the heterogeneity of variance structure, the…
Zhang, S.B.; Zunger, A.
1996-01-01
First-principles calculations of atomic structure and formation energies of semiconductor surfaces and surface steps are often complicated by complex structural patterns. We suggest here a simpler, algebraic (not differential) approach that is based on two observations distilled from previous first-principles calculations. {ital First}, a relatively large collection of equilibrium structures of surfaces and bulk point defects can be built from a limited number of recurring local {open_quote}{open_quote}structural motifs,{close_quote}{close_quote} including for GaAs tetrahedrally bonded Ga and As and miscoordinated atoms such as threefold-coordinated pyramidal As. {ital Second}, the structure is such that band-gap levels are emptied, resulting in charged miscoordinated atoms. These charges compensate each other. We thus express the total energy of a given surface as a sum of the energies of the motifs, and an electrostatic term representing the Madelung energy of point charges. The motif energies are derived by fitting them to a set of pseudopotential total-energy calculations for {ital flat} GaAs(001) surfaces and for point defects in {ital bulk} GaAs. This set of parameters is shown to suffice to reproduce the energies of {ital other} (001) surfaces, calculated using the same pseudopotential approach. Application of the {open_quote}{open_quote}linear combination of structural motif{close_quote}{close_quote} (LCSM) method to flat GaAs(001) surfaces reveals the following: (i) The observed {ital h}(2{times}3) surface may be a disordered {ital c}(8{times}6) surface. (ii) The observed (2{times}6) surface is a metastable surface, only 0.03 eV/(1{times}1) higher than the {alpha}(2{times}4) surface having the same surface coverage. (iii) We confirm the recent suggestion by Hashizume {ital et} {ital al}. that the observed {gamma}(2{times}4) phase of the (2{times}4) surface is a mixture of the {beta}2(2{times}4) and {ital c}(4{times}4) surfaces. (Abstract Truncated)
Vector Adaptive/Predictive Encoding Of Speech
NASA Technical Reports Server (NTRS)
Chen, Juin-Hwey; Gersho, Allen
1989-01-01
Vector adaptive/predictive technique for digital encoding of speech signals yields decoded speech of very good quality after transmission at coding rate of 9.6 kb/s and of reasonably good quality at 4.8 kb/s. Requires 3 to 4 million multiplications and additions per second. Combines advantages of adaptive/predictive coding, and code-excited linear prediction, yielding speech of high quality but requires 600 million multiplications and additions per second at encoding rate of 4.8 kb/s. Vector adaptive/predictive coding technique bridges gaps in performance and complexity between adaptive/predictive coding and code-excited linear prediction.
NASA Astrophysics Data System (ADS)
Lin, Tsungpo
Performance engineers face the major challenge in modeling and simulation for the after-market power system due to system degradation and measurement errors. Currently, the majority in power generation industries utilizes the deterministic data matching method to calibrate the model and cascade system degradation, which causes significant calibration uncertainty and also the risk of providing performance guarantees. In this research work, a maximum-likelihood based simultaneous data reconciliation and model calibration (SDRMC) is used for power system modeling and simulation. By replacing the current deterministic data matching with SDRMC one can reduce the calibration uncertainty and mitigate the error propagation to the performance simulation. A modeling and simulation environment for a complex power system with certain degradation has been developed. In this environment multiple data sets are imported when carrying out simultaneous data reconciliation and model calibration. Calibration uncertainties are estimated through error analyses and populated to performance simulation by using principle of error propagation. System degradation is then quantified by performance comparison between the calibrated model and its expected new & clean status. To mitigate smearing effects caused by gross errors, gross error detection (GED) is carried out in two stages. The first stage is a screening stage, in which serious gross errors are eliminated in advance. The GED techniques used in the screening stage are based on multivariate data analysis (MDA), including multivariate data visualization and principal component analysis (PCA). Subtle gross errors are treated at the second stage, in which the serial bias compensation or robust M-estimator is engaged. To achieve a better efficiency in the combined scheme of the least squares based data reconciliation and the GED technique based on hypotheses testing, the Levenberg-Marquardt (LM) algorithm is utilized as the optimizer. To
Martín-Arévalo, Elisa; Salemme, Romeo; Pisella, Laure; Farnè, Alessandro
2016-01-01
Rightward prism adaptation ameliorates neglect symptoms while leftward prism adaptation (LPA) induces neglect-like biases in healthy individuals. Similarly, inhibitory repetitive transcranial magnetic stimulation (rTMS) on the right posterior parietal cortex (PPC) induces neglect-like behavior, whereas on the left PPC it ameliorates neglect symptoms and normalizes hyperexcitability of left hemisphere parietal-motor (PPC-M1) connectivity. Based on this analogy we hypothesized that LPA increases PPC-M1 excitability in the left hemisphere and decreases it in the right one. In an attempt to shed some light on the mechanisms underlying LPA's effects on cognition, we investigated this hypothesis in healthy individuals measuring PPC-M1 excitability with dual-site paired-pulse TMS (ppTMS). We found a left hemisphere increase and a right hemisphere decrease in the amplitude of motor evoked potentials elicited by paired as well as single pulses on M1. While this could indicate that LPA biases interhemispheric connectivity, it contradicts previous evidence that M1-only MEPs are unchanged after LPA. A control experiment showed that input-output curves were not affected by LPA per se. We conclude that LPA combined with ppTMS on PPC-M1 differentially alters the excitability of the left and right M1. PMID:27418979
Schintu, Selene; Martín-Arévalo, Elisa; Vesia, Michael; Rossetti, Yves; Salemme, Romeo; Pisella, Laure; Farnè, Alessandro; Reilly, Karen T
2016-01-01
Rightward prism adaptation ameliorates neglect symptoms while leftward prism adaptation (LPA) induces neglect-like biases in healthy individuals. Similarly, inhibitory repetitive transcranial magnetic stimulation (rTMS) on the right posterior parietal cortex (PPC) induces neglect-like behavior, whereas on the left PPC it ameliorates neglect symptoms and normalizes hyperexcitability of left hemisphere parietal-motor (PPC-M1) connectivity. Based on this analogy we hypothesized that LPA increases PPC-M1 excitability in the left hemisphere and decreases it in the right one. In an attempt to shed some light on the mechanisms underlying LPA's effects on cognition, we investigated this hypothesis in healthy individuals measuring PPC-M1 excitability with dual-site paired-pulse TMS (ppTMS). We found a left hemisphere increase and a right hemisphere decrease in the amplitude of motor evoked potentials elicited by paired as well as single pulses on M1. While this could indicate that LPA biases interhemispheric connectivity, it contradicts previous evidence that M1-only MEPs are unchanged after LPA. A control experiment showed that input-output curves were not affected by LPA per se. We conclude that LPA combined with ppTMS on PPC-M1 differentially alters the excitability of the left and right M1. PMID:27418979
NASA Technical Reports Server (NTRS)
McCrea, R. A.; Chen-Huang, C.; Peterson, B. W. (Principal Investigator)
1999-01-01
The contributions of vestibular nerve afferents and central vestibular pathways to the angular (AVOR) and linear (LVOR) vestibulo-ocular reflex were studied in squirrel monkeys during fixation of near and far targets. Irregular vestibular afferents did not appear to be necessary for the LVOR, since when they were selectively silenced with galvanic currents the LVOR was essentially unaffected during both far- and near-target viewing. The linear translation signals generated by secondary AVOR neurons in the vestibular nuclei were, on average, in phase with head velocity, inversely related to viewing distance, and were nearly as strong as AVOR-related signals. We suggest that spatial-temporal transformation of linear head translation signals to angular eye velocity commands is accomplished primarily by the addition of viewing distance multiplied, centrally integrated, otolith regular afferent signals to angular VOR pathways.
Barrett, Harrison H.; Furenlid, Lars R.; Freed, Melanie; Hesterman, Jacob Y.; Kupinski, Matthew A.; Clarkson, Eric; Whitaker, Meredith K.
2008-01-01
Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed. PMID:18541485
Bagherpoor, H M; Salmasi, Farzad R
2015-07-01
In this paper, robust model reference adaptive tracking controllers are considered for Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) linear systems containing modeling uncertainties, unknown additive disturbances and actuator fault. Two new lemmas are proposed for both SISO and MIMO, under which dead-zone modification rule is improved such that the tracking error for any reference signal tends to zero in such systems. In the conventional approach, adaption of the controller parameters is ceased inside the dead-zone region which results tracking error, while preserving the system stability. In the proposed scheme, control signal is reinforced with an additive term based on tracking error inside the dead-zone which results in full reference tracking. In addition, no Fault Detection and Diagnosis (FDD) unit is needed in the proposed approach. Closed loop system stability and zero tracking error are proved by considering a suitable Lyapunov functions candidate. It is shown that the proposed control approach can assure that all the signals of the close loop system are bounded in faulty conditions. Finally, validity and performance of the new schemes have been illustrated through numerical simulations of SISO and MIMO systems in the presence of actuator faults, modeling uncertainty and output disturbance. PMID:25744053
NASA Astrophysics Data System (ADS)
Ye, Tianyu; Liu, Han-Chun; Mani, Ramesh; Wegscheider, Werner; Georgia State University Collaboration; ETH Zurich Collaboration
2014-03-01
Microwave radiation induced magnetoresistance oscillations (MRIMOs) represent an interesting electrical property of the high mobility two dimensional electron gas (2DEG) at low temperatures in a perpendicular magnetic field and under microwave excitation. Some questions under discussion in this topic include: (a) whether MRIMOs' amplitudes grow linearly with the microwave power and (b) how the MRIMO amplitudes change with the rotation of the microwave polarization with respect to the sample. In this study, we utilize swept microwave power and continuously changed linear polarized microwave polarization angle as two variables in four-terminal low-frequency lock-in magnetoresistance measurements of the 2DEG samples. The results show that amplitude of MRIMOs varies non-linearly with the microwave power. Also, the microwave polarization dependence measurements show that MRIMOs depend sensitively on the polarization angle of the linearly polarized microwaves, while the oscillatory magnetoresistance follows a cosine square function of the polarization angle. We provide a simple model that conveys our understanding of our observations. Basic research at Georgia State University is supported by the DOE-BES, MSE Division under DE-SC0001762. Microwave work is supported by the ARO under W911NF-07-01-0158.
Technology Transfer Automated Retrieval System (TEKTRAN)
A site-specific controller, hardware and software systems were developed with the capability to switch between either mid-elevation spray application (MESA) or low energy precision application (LEPA) methods. These systems were field tested and used to manage site-specific irrigations under a linear...
Topalova, Y.; Dimkov, R. . Faculty of Biology); Kozuharov, D. )
1999-01-01
The reaction of the real aerobic activated sludge taken from the Sofia Waste Water Treatment Plant (SWWTP) and treated with the xenobiotics pentachlorphenol (PCP) (0.16 mMol), ortho-nitrophenol (oNP) (0.58 mMol) and with a combination of PCP (0.08 mMol), oNP (0.29 mMol) has been investigated in a model detoxification process. The adaptive changes are studied in the microbial structure level and at the level of changes in the qualitative and quantitative parameters of the macro-organisms in the activated sludge (consuments of 1 and 2 level). The presence of several different taxonomic groups has been shown by other researchers to be essential in the detoxification process. The quantitative changes in these taxonomic and physiological groups of micro-organisms are studied. The number of micro-organisms from Pseudomonas, Acinetobacter and the bacteria from the xenobiotic-catabolizing complex considerably increased with the individual and the combined effect of the xenobiotics oNP, PCP and oNP PCP. At the same time the toxic shock leads to a remarkable reduction of NH[sub 3] releasing, nitrifying bacteria and those from family Enterobacteriaceae. It is ascertained that the number of Ciliata, Flagellata apochromata, Oligochaeta and Rotatoria is strongly decreased in the series of samples treated with xenobiotics. The leading role of micro-organisms in the real detoxification of hazardous pollutants was experimentally confirmed by research.
NASA Astrophysics Data System (ADS)
Wells-Gray, Elaine M.; Zawadzki, Robert J.; Finn, Susanna C.; Greiner, Cherry; Werner, John S.; Choi, Stacey S.; Doble, Nathan
2015-03-01
We describe the design and performance of a recently implemented retinal imaging system for the human eye that combines adaptive optics (AO) with spectral domain optical coherence tomography (OCT) and scanning laser ophthalmoscopy (SLO). The AO-OCT-SLO system simultaneously acquires SLO frames and OCT B-scans at 60 Hz with an OCT volume acquisition scan rate of 0.24 Hz. The SLO images are used to correct for eye motion during the registration of OCT B-scans. Key optical design considerations are discussed including: minimizing system aberrations through the use of off-axis relay telescopes; choice of telescope magnification based on pupil plane requirements and restrictions; and the use of dichroic beam splitters to separate and re-combine OCT and SLO beams around the nonshared horizontal scanning mirrors. We include an analysis of closed-loop AO correction on a model eye and compare these findings with system performance in vivo. The 2D and 3D OCT scans included in this work demonstrate the ability of this system to laterally and axially resolve individual cone photoreceptors, while the corresponding SLO images show the en face mosaics at the photoreceptor layer showing rods and cones. Images from both healthy and diseased retina are presented.
Andermatt, Samuel; Cha, Jinwoong; Schiffmann, Florian; VandeVondele, Joost
2016-07-12
In this work, methods for the efficient simulation of large systems embedded in a molecular environment are presented. These methods combine linear-scaling (LS) Kohn-Sham (KS) density functional theory (DFT) with subsystem (SS) DFT. LS DFT is efficient for large subsystems, while SS DFT is linear scaling with a smaller prefactor for large sets of small molecules. The combination of SS and LS, which is an embedding approach, can result in a 10-fold speedup over a pure LS simulation for large systems in aqueous solution. In addition to a ground-state Born-Oppenheimer SS+LS implementation, a time-dependent density functional theory-based Ehrenfest molecular dynamics (EMD) using density matrix propagation is presented that allows for performing nonadiabatic dynamics. Density matrix-based EMD in the SS framework is naturally linear scaling and appears suitable to study the electronic dynamics of molecules in solution. In the LS framework, linear scaling results as long as the density matrix remains sparse during time propagation. However, we generally find a less than exponential decay of the density matrix after a sufficiently long EMD run, preventing LS EMD simulations with arbitrary accuracy. The methods are tested on various systems, including spectroscopy on dyes, the electronic structure of TiO2 nanoparticles, electronic transport in carbon nanotubes, and the satellite tobacco mosaic virus in explicit solution. PMID:27244103
NASA Astrophysics Data System (ADS)
Sharma, S.; Narayan, A.
2001-06-01
The non-linear oscillation of inter-connected satellites system about its equilibrium position in the neighabourhood of main resonance ??=3D 1, under the combined effects of the solar radiation pressure and the dissipative forces of general nature has been discussed. It is found that the oscillation of the system gets disturbed when the frequency of the natural oscillation approaches the resonance frequency.
Ghosh, A
1989-06-15
There are two different approaches for improving the accuracy of analog optical associative processors: postprocessing with a bimodal system and preprocessing with a preconditioner. These two approaches can be combined to develop an adaptive optical multiprocessor that can adjust the computational steps depending on the data and produce solutions of linear algebra problems with a specified accuracy in a given amount of time. PMID:19752909
NASA Astrophysics Data System (ADS)
Thomas, Patrick Ryan
Large simulation cell sizes, relativistic effects, and the need to correctly model excited state properties are major impediments to the accurate prediction of the optical properties of candidate materials for solid-state laser crystal and luminescent applications. To overcome these challenges, new methods must be created to improve the electron orbital wavefunction and interactions. In this work, a method has been developed to create new analytical four-component, fully-relativistic and single-component scalar relativistic descriptions of the atomic orbital wave functions from Grasp2K numerically represented atomic orbitals. In addition, adapted theory for the calculation of the relativistic kinetic energy contribution to Hamiltonian which bypasses directly solving the Dirac equation has been explicated. The orbital description improvements are tested against YAG, YBCO, SnO2 and BiF3. The improvements to the basis set reflect an improvement in both computational speed and accuracy.
Zhang, Qiang; Hong, Yongmi; Zou, Fasheng; Zhang, Min; Lee, Tien Ming; Song, Xiangjin; Rao, Jiteng
2016-01-01
The extent to which species' traits, behavior and habitat synergistically determine their response to extreme weather events (EWE) remains poorly understood. By quantifying bird and vegetation assemblages before and after the 2008 ice storm in China, combined with interspecific interactions and foraging behaviours, we disentangled whether storm influences avian reassembly directly via functional traits (i.e. behavioral adaptations), or indirectly via habitat variations. We found that overall species richness decreased, with 20 species detected exclusively before the storm, and eight species detected exclusively after. These shifts in bird relative abundance were linked to habitat preferences, dietary guild and flocking behaviours. For instance, forest specialists at higher trophic levels (e.g. understory-insectivores, woodpeckers and kingfishers) were especially vulnerable, whereas open-habitat generalists (e.g. bulbuls) were set to benefit from potential habitat homogenization. Alongside population fluctuations, we found that community reassembly can be rapidly adjusted via foraging plasticity (i.e. increased flocking propensity and reduced perching height). And changes in preferred habitat corresponded to a variation in bird assemblages and traits, as represented by intact canopy cover and high density of large trees. Accurate predictions of community responses to EWE are crucial to understanding ecosystem disturbances, thus linking species-oriented traits to a coherent analytical framework. PMID:26929387
NASA Astrophysics Data System (ADS)
Denker, Carsten; Mascarinas, Dulce; Xu, Yan; Cao, Wenda; Yang, Guo; Wang, Haimin; Goode, Philip R.; Rimmele, Thomas
2005-04-01
We present, for the first time, high-spatial-resolution observations combining high-order adaptive optics (AO), frame selection, and post-facto image correction via speckle masking. The data analysis is based on observations of solar active region NOAA 10486 taken with the Dunn Solar Telescope (DST) at the Sacramento Peak Observatory (SPO) of the National Solar Observatory (NSO) on 29 October 2003. The high Strehl ratio encountered in AO corrected short-exposure images provides highly improved signal-to-noise ratios leading to a superior recovery of the object’s Fourier phases. This allows reliable detection of small-scale solar features near the diffraction limit of the telescope. Speckle masking imaging provides access to high-order wavefront aberrations, which predominantly originate at high atmospheric layers and are only partially corrected by the AO system. In addition, the observations provided qualitative measures of the image correction away from the lock point of the AO system. We further present a brief inspection of the underlying imaging theory discussing the limitations and prospects of this multi-faceted image reconstruction approach in terms of the recovery of spatial information, photometric accuracy, and spectroscopic applications.
Zhang, Qiang; Hong, Yongmi; Zou, Fasheng; Zhang, Min; Lee, Tien Ming; Song, Xiangjin; Rao, Jiteng
2016-01-01
The extent to which species’ traits, behavior and habitat synergistically determine their response to extreme weather events (EWE) remains poorly understood. By quantifying bird and vegetation assemblages before and after the 2008 ice storm in China, combined with interspecific interactions and foraging behaviours, we disentangled whether storm influences avian reassembly directly via functional traits (i.e. behavioral adaptations), or indirectly via habitat variations. We found that overall species richness decreased, with 20 species detected exclusively before the storm, and eight species detected exclusively after. These shifts in bird relative abundance were linked to habitat preferences, dietary guild and flocking behaviours. For instance, forest specialists at higher trophic levels (e.g. understory-insectivores, woodpeckers and kingfishers) were especially vulnerable, whereas open-habitat generalists (e.g. bulbuls) were set to benefit from potential habitat homogenization. Alongside population fluctuations, we found that community reassembly can be rapidly adjusted via foraging plasticity (i.e. increased flocking propensity and reduced perching height). And changes in preferred habitat corresponded to a variation in bird assemblages and traits, as represented by intact canopy cover and high density of large trees. Accurate predictions of community responses to EWE are crucial to understanding ecosystem disturbances, thus linking species-oriented traits to a coherent analytical framework. PMID:26929387
Lin, Wan-Yu; Liang, Yun-Chieh
2016-01-01
Detection of rare causal variants can help uncover the etiology of complex diseases. Recruiting case-parent trios is a popular study design in family-based studies. If researchers can obtain data from population controls, utilizing them in trio analyses can improve the power of methods. The transmission disequilibrium test (TDT) is a well-known method to analyze case-parent trio data. It has been extended to rare-variant association testing (abbreviated as “rvTDT”), with the flexibility to incorporate population controls. The rvTDT method is robust to population stratification. However, power loss may occur in the conditioning process. Here we propose a “conditioning adaptive combination of P-values method” (abbreviated as “conADA”), to analyze trios with/without unrelated controls. By first truncating the variants with larger P-values, we decrease the vulnerability of conADA to the inclusion of neutral variants. Moreover, because the test statistic is developed by conditioning on parental genotypes, conADA generates valid statistical inference in the presence of population stratification. With regard to statistical methods for next-generation sequencing data analyses, validity may be hampered by population stratification, whereas power may be affected by the inclusion of neutral variants. We recommend conADA for its robustness to these two factors (population stratification and the inclusion of neutral variants). PMID:27341039
NASA Astrophysics Data System (ADS)
Hoyos, Mauricio; Moore, Lee; Williams, P. Stephen; Zborowski, Maciej
2011-05-01
The Quadrupole Magnetic Sorter (QMS), employing an annular flow channel concentric with the aperture of a quadrupole magnet, is well established for cell and particle separations. Here we propose a magnetic particle separator comprising a linear array of cylindrical magnets, analogous to the array proposed by Klaus Halbach, mated to a substantially improved form of a parallel plate SPLITT channel, known as the step-SPLITT channel. While the magnetic force and throughput are generally lower than for the QMS, the new separator has advantages in ease of fabrication and the ability to vary the magnetic force to suit the separands. Preliminary experiments yield results consistent with prediction and show promise regarding future separations of cells of biomedical interest.
NASA Astrophysics Data System (ADS)
Molina, Enrique; Estrada, Ernesto; Nodarse, Delvin; Torres, Luis A.; González, Humberto; Uriarte, Eugenio
Time-dependent antibacterial activity of 2-furylethylenes using quantum chemical, topographic, and topological indices is described as inhibition of respiration in E. coli. A QSAR strategy based on the combination of the linear piecewise regression and the discriminant analysis is used to predict the biological activity values of strong and moderates antibacterial furylethylenes. The breakpoint in the values of the biological activity was detected. The biological activities of the compounds are described by two linear regression equations. A discriminant analysis is carried out to classify the compounds in one of the biological activity two groups. The results showed using different kind of descriptors were compared. In all cases the piecewise linear regression - discriminant analysis (PLR-DA) method produced significantly better QSAR models than the linear regression analysis. The QSAR models were validated using an external validation previously extracted from the original data. A prediction of reported antibacterial activity analysis was carried out showing dependence between the probability of a good classification and the experimental antibacterial activity. Statistical parameters showed the quality of quantum-chemical descriptors based models prediction in LDA having an accuracy of 0.9 and a C of 0.9. The best PLR-DA model explains more than 92% of the variance of experimental activity. Models with best prediction results were those based on quantum-chemical descriptors. An interpretation of quantum-chemical descriptors entered in models was carried out.
Darzi, Soodabeh; Kiong, Tiong Sieh; Islam, Mohammad Tariqul; Ismail, Mahamod; Kibria, Salehin; Salem, Balasem
2014-01-01
Linear constraint minimum variance (LCMV) is one of the adaptive beamforming techniques that is commonly applied to cancel interfering signals and steer or produce a strong beam to the desired signal through its computed weight vectors. However, weights computed by LCMV usually are not able to form the radiation beam towards the target user precisely and not good enough to reduce the interference by placing null at the interference sources. It is difficult to improve and optimize the LCMV beamforming technique through conventional empirical approach. To provide a solution to this problem, artificial intelligence (AI) technique is explored in order to enhance the LCMV beamforming ability. In this paper, particle swarm optimization (PSO), dynamic mutated artificial immune system (DM-AIS), and gravitational search algorithm (GSA) are incorporated into the existing LCMV technique in order to improve the weights of LCMV. The simulation result demonstrates that received signal to interference and noise ratio (SINR) of target user can be significantly improved by the integration of PSO, DM-AIS, and GSA in LCMV through the suppression of interference in undesired direction. Furthermore, the proposed GSA can be applied as a more effective technique in LCMV beamforming optimization as compared to the PSO technique. The algorithms were implemented using Matlab program. PMID:25147859
Sieh Kiong, Tiong; Tariqul Islam, Mohammad; Ismail, Mahamod; Salem, Balasem
2014-01-01
Linear constraint minimum variance (LCMV) is one of the adaptive beamforming techniques that is commonly applied to cancel interfering signals and steer or produce a strong beam to the desired signal through its computed weight vectors. However, weights computed by LCMV usually are not able to form the radiation beam towards the target user precisely and not good enough to reduce the interference by placing null at the interference sources. It is difficult to improve and optimize the LCMV beamforming technique through conventional empirical approach. To provide a solution to this problem, artificial intelligence (AI) technique is explored in order to enhance the LCMV beamforming ability. In this paper, particle swarm optimization (PSO), dynamic mutated artificial immune system (DM-AIS), and gravitational search algorithm (GSA) are incorporated into the existing LCMV technique in order to improve the weights of LCMV. The simulation result demonstrates that received signal to interference and noise ratio (SINR) of target user can be significantly improved by the integration of PSO, DM-AIS, and GSA in LCMV through the suppression of interference in undesired direction. Furthermore, the proposed GSA can be applied as a more effective technique in LCMV beamforming optimization as compared to the PSO technique. The algorithms were implemented using Matlab program. PMID:25147859
NASA Astrophysics Data System (ADS)
Trigo, F. C.; Martins, F. P. R.; Fleury, A. T.; Silva, H. C.
2014-02-01
Aiming at overcoming the difficulties derived from the traditional camera calibration methods to record the underwater environment of a towing tank where experiments of scaled-model risers are carried on, a computer vision method, combining traditional image processing algorithms and a self-calibration technique was implemented. This method was used to identify the coordinates of control-points viewed on a scaled-model riser submitted to a periodic force applied to its fairlead attachment point. To study the observed motion, the riser was represented as a pseudo-rigid body model (PRBM) and the hypotheses of compliant mechanisms theory were assumed in order to cope with its elastic behavior. The derived Lagrangian equations of motion were linearized and expressed as a state-space model in which the state variables include the generalized coordinates and the unknown generalized forces. The state-vector thus assembled is estimated through a Kalman Filter. The estimation procedure allows the determination of both the generalized forces and the tension along the cable, with statistically proven convergence.
Holly, J E
2000-01-01
The laws of physics explain many human misperceptions of whole-body passive self-motion. One classic misperception occurs in a rotating chair in the dark: If the chair is decelerated to a stop after a period of counterclockwise rotation, then a subject will typically perceive clockwise rotation. The laws of physics show that, indeed, a clockwise rotation would be perceived even by a perfect processor of angular acceleration information, assuming that the processor is initialized (prior to the deceleration) with a typical subject's initial perception - of no rotation in this case. The motion perceived by a perfect acceleration processor serves as a baseline by which to judge human self-motion perception; this baseline makes a rough prediction and also forms a basis for comparison, with uniquely physiological properties of perception showing up as deviations from the baseline. These same principles, using the motion perceived by a perfect acceleration processor as a baseline, are used in the present paper to investigate complex motions that involve simultaneous linear and angular accelerations with a changing axis of rotation. Baselines - motions that would be perceived by a perfect acceleration processor, given the same initial perception (prior to the motion of interest) as that of a typical subject - are computed for the acceleration and deceleration stages of centrifuge runs in which the human carriage tilts along with the vector resultant of the centripetal and gravity vectors. The computations generate a three-dimensional picture of the motion perceived by a perfect acceleration processor, by simultaneously using all six interacting degrees of freedom (three angular and three linear) and taking into account the non-commutativity of rotations in three dimensions. The resulting three-dimensional baselines predict stronger perceptual effects during deceleration than during acceleration, despite the equal magnitudes (with opposite direction) of forces on the
NASA Astrophysics Data System (ADS)
Shen, Chong; Cao, Huiliang; Li, Jie; Tang, Jun; Zhang, Xiaoming; Shi, Yunbo; Yang, Wei; Liu, Jun
2016-03-01
A noise reduction algorithm based on an improved empirical mode decomposition (EMD) and forward linear prediction (FLP) is proposed for the fiber optic gyroscope (FOG). Referred to as the EMD-FLP algorithm, it was developed to decompose the FOG outputs into a number of intrinsic mode functions (IMFs) after which mode manipulations are performed to select noise-only IMFs, mixed IMFs, and residual IMFs. The FLP algorithm is then employed to process the mixed IMFs, from which the refined IMFs components are reconstructed to produce the final de-noising results. This hybrid approach is applied to, and verified using, both simulated signals and experimental FOG outputs. The results from the applications show that the method eliminates noise more effectively than the conventional EMD or FLP methods and decreases the standard deviations of the FOG outputs after de-noising from 0.17 to 0.026 under sweep frequency vibration and from 0.22 to 0.024 under fixed frequency vibration.
Shen, Chong; Cao, Huiliang; Li, Jie; Tang, Jun; Zhang, Xiaoming; Shi, Yunbo; Yang, Wei; Liu, Jun
2016-03-01
A noise reduction algorithm based on an improved empirical mode decomposition (EMD) and forward linear prediction (FLP) is proposed for the fiber optic gyroscope (FOG). Referred to as the EMD-FLP algorithm, it was developed to decompose the FOG outputs into a number of intrinsic mode functions (IMFs) after which mode manipulations are performed to select noise-only IMFs, mixed IMFs, and residual IMFs. The FLP algorithm is then employed to process the mixed IMFs, from which the refined IMFs components are reconstructed to produce the final de-noising results. This hybrid approach is applied to, and verified using, both simulated signals and experimental FOG outputs. The results from the applications show that the method eliminates noise more effectively than the conventional EMD or FLP methods and decreases the standard deviations of the FOG outputs after de-noising from 0.17 to 0.026 under sweep frequency vibration and from 0.22 to 0.024 under fixed frequency vibration. PMID:27036770
NASA Astrophysics Data System (ADS)
Lark, R. M.; Marchant, B. P.; Dove, D.; Green, S. L.; Stewart, H.; Diesing, M.
2015-10-01
Seabed sediment texture can be mapped by geostatistical prediction from limited direct observations such as grab-samples. A geostatistical model can provide local estimates of the probability of each texture class so the most probable sediment class can be identified at any unsampled location, and the uncertainty of this prediction can be quantified. In this paper we show, in a case study off the northeast coast of England, how swath bathymetry and backscatter can be incorporated into a geostatistical linear mixed model (LMM) as fixed effects (covariates). Parameters of the LMM were estimated by maximum likelihood which allowed us to show that both covariates provided useful information. In a cross-validation, each observation was predicted from the rest using the LMMs with (i) no covariates, or (ii) bathymetry and backscatter as covariates. The proportion of cases in which the most probable class according to the prediction corresponded to the observed class was increased (from 58% to 65% of cases) by including the covariates which also increased the information content of the predictions, measured by the entropy of the class probabilities. A qualitative assessment of the geostatistical results shows that the model correctly predicts, for example, the occurrence of coarser sediment over discrete glacial sediment landforms, and muddier sediment in relatively quiescent, localized deep water environments. This demonstrates the potential for assimilating geophysical data with direct observations by the LMM, and could offer a basis for a routine mapping procedure which incorporates these and other ancillary information such as manually-interpreted geological and geomorphological maps.
NASA Astrophysics Data System (ADS)
Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara
2015-09-01
Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the
Dynamical Adaptation in Photoreceptors
Clark, Damon A.; Benichou, Raphael; Meister, Markus; Azeredo da Silveira, Rava
2013-01-01
Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300 ms—i. e., over the time scale of the response itself—and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant. PMID:24244119
Zhang, Junwen; Wang, Jing; Xu, Yuming; Xu, Mu; Lu, Feng; Cheng, Lin; Yu, Jianjun; Chang, Gee-Kung
2016-05-01
We propose and experimentally demonstrate a novel fiber-wireless integrated mobile backhaul network based on a hybrid millimeter-wave (MMW) and free-space-optics (FSO) architecture using an adaptive combining technique. Both 60 GHz MMW and FSO links are demonstrated and fully integrated with optical fibers in a scalable and cost-effective backhaul system setup. Joint signal processing with an adaptive diversity combining technique (ADCT) is utilized at the receiver side based on a maximum ratio combining algorithm. Mobile backhaul transportation of 4-Gb/s 16 quadrature amplitude modulation frequency-division multiplexing (QAM-OFDM) data is experimentally demonstrated and tested under various weather conditions synthesized in the lab. Performance improvement in terms of reduced error vector magnitude (EVM) and enhanced link reliability are validated under fog, rain, and turbulence conditions. PMID:27128036
NASA Technical Reports Server (NTRS)
Clancy, John P.
1988-01-01
The object of the invention is to provide a mechanical force actuator which is lightweight and manipulatable and utilizes linear motion for push or pull forces while maintaining a constant overall length. The mechanical force producing mechanism comprises a linear actuator mechanism and a linear motion shaft mounted parallel to one another. The linear motion shaft is connected to a stationary or fixed housing and to a movable housing where the movable housing is mechanically actuated through actuator mechanism by either manual means or motor means. The housings are adapted to releasably receive a variety of jaw or pulling elements adapted for clamping or prying action. The stationary housing is adapted to be pivotally mounted to permit an angular position of the housing to allow the tool to adapt to skewed interfaces. The actuator mechanisms is operated by a gear train to obtain linear motion of the actuator mechanism.
Gobrecht, Alexia; Bendoula, Ryad; Roger, Jean-Michel; Bellon-Maurel, Véronique
2015-01-01
Visible and Near Infrared (Vis-NIR) Spectroscopy is a powerful non destructive analytical method used to analyze major compounds in bulk materials and products and requiring no sample preparation. It is widely used in routine analysis and also in-line in industries, in-vivo with biomedical applications or in-field for agricultural and environmental applications. However, highly scattering samples subvert Beer-Lambert law's linear relationship between spectral absorbance and the concentrations. Instead of spectral pre-processing, which is commonly used by Vis-NIR spectroscopists to mitigate the scattering effect, we put forward an optical method, based on Polarized Light Spectroscopy to improve the absorbance signal measurement on highly scattering samples. This method selects part of the signal which is less impacted by scattering. The resulted signal is combined in the Absorption/Remission function defined in Dahm's Representative Layer Theory to compute an absorbance signal fulfilling Beer-Lambert's law, i.e. being linearly related to concentration of the chemicals composing the sample. The underpinning theories have been experimentally evaluated on scattering samples in liquid form and in powdered form. The method produced more accurate spectra and the Pearson's coefficient assessing the linearity between the absorbance spectra and the concentration of the added dye improved from 0.94 to 0.99 for liquid samples and 0.84-0.97 for powdered samples. PMID:25467494
Stepushina, O A; Bol'shunov, A V
2011-01-01
15 patients with diabetic and hypertensive retinopathy are examined. Retinal vascular caliber was measured using adaptive multifocal fundus camera (AMFC), fundus camera "Topcon" TRS-NW200 and FAG. Combination of retinal vascular caliber measurement and fundus foto using AMFC in patients with ametropia and astigmatismus showed apparently lower arteriolovenular coefficient (A VC) compared with that estimated using FAG imaging. Retinal vascular caliber measurement using adaptive optics is a highly sensitive method of visualization and monitoring of early signs of diabetic and hypertensive retinopathy. PMID:21721269
Collin, Helene; Burri, Reto; Comtesse, Fabien; Fumagalli, Luca
2013-01-01
Abstract Host–pathogen interactions are a major evolutionary force promoting local adaptation. Genes of the major histocompatibility complex (MHC) represent unique candidates to investigate evolutionary processes driving local adaptation to parasite communities. The present study aimed at identifying the relative roles of neutral and adaptive processes driving the evolution of MHC class IIB (MHCIIB) genes in natural populations of European minnows (Phoxinus phoxinus). To this end, we isolated and genotyped exon 2 of two MHCIIB gene duplicates (DAB1 and DAB3) and 1′665 amplified fragment length polymorphism (AFLP) markers in nine populations, and characterized local bacterial communities by 16S rDNA barcoding using 454 amplicon sequencing. Both MHCIIB loci exhibited signs of historical balancing selection. Whereas genetic differentiation exceeded that of neutral markers at both loci, the populations' genetic diversities were positively correlated with local pathogen diversities only at DAB3. Overall, our results suggest pathogen-mediated local adaptation in European minnows at both MHCIIB loci. While at DAB1 selection appears to favor different alleles among populations, this is only partially the case in DAB3, which appears to be locally adapted to pathogen communities in terms of genetic diversity. These results provide new insights into the importance of host–pathogen interactions in driving local adaptation in the European minnow, and highlight that the importance of adaptive processes driving MHCIIB gene evolution may differ among duplicates within species, presumably as a consequence of alternative selective regimes or different genomic context. Using next-generation sequencing, the present manuscript identifies the relative roles of neutral and adaptive processes driving the evolution of MHC class IIB (MHCIIB) genes in natural populations of a cyprinid fish: the European minnow (Phoxinus phoxinus). We highlight that the relative importance of neutral
Ghose, Kaushik; Moss, Cynthia F.
2012-01-01
Adaptive behaviors require sensorimotor computations that convert information represented initially in sensory coordinates to commands for action in motor coordinates. Fundamental to these computations is the relationship between the region of the environment sensed by the animal (gaze) and the animal’s locomotor plan. Studies of visually guided animals have revealed an anticipatory relationship between gaze direction and the locomotor plan during target-directed locomotion. Here, we study an acoustically guided animal, an echolocating bat, and relate acoustic gaze (direction of the sonar beam) to flight planning as the bat searches for and intercepts insect prey. We show differences in the relationship between gaze and locomotion as the bat progresses through different phases of insect pursuit. We define acoustic gaze angle, θgaze, to be the angle between the sonar beam axis and the bat’s flight path. We show that there is a strong linear linkage between acoustic gaze angle at time t [θgaze(t)] and flight turn rate at time t + τ into the future [θ̇flight (t + τ)], which can be expressed by the formula θ̇flight (t + τ) = kθgaze(t). The gain, k, of this linkage depends on the bat’s behavioral state, which is indexed by its sonar pulse rate. For high pulse rates, associated with insect attacking behavior, k is twice as high compared with low pulse rates, associated with searching behavior. We suggest that this adjustable linkage between acoustic gaze and motor output in a flying echolocating bat simplifies the transformation of auditory information to flight motor commands. PMID:16467518
Doulamis, Nikolaos D; Doulamis, Anastasios D; Panagakis, Athanasios; Dolkas, Konstantinos; Varvarigou, Theodora A; Varvarigos, Emmanuel
2004-04-01
Implementation of a commercial application to a grid infrastructure introduces new challenges in managing the quality-of-service (QoS) requirements, most stem from the fact that negotiation on QoS between the user and the service provider should strictly be satisfied. An interesting commercial application with a wide impact on a variety of fields, which can benefit from the computational grid technologies, is three-dimensional (3-D) rendering. In order to implement, however, 3-D rendering to a grid infrastructure, we should develop appropriate scheduling and resource allocation mechanisms so that the negotiated (QoS) requirements are met. Efficient scheduling schemes require modeling and prediction of rendering workload. In this paper workload prediction is addressed based on a combined fuzzy classification and neural network model. Initially, appropriate descriptors are extracted to represent the synthetic world. The descriptors are obtained by parsing RIB formatted files, which provides a general structure for describing computer-generated images. Fuzzy classification is used for organizing rendering descriptor so that a reliable representation is accomplished which increases the prediction accuracy. Neural network performs workload prediction by modeling the nonlinear input-output relationship between rendering descriptors and the respective computational complexity. To increase prediction accuracy, a constructive algorithm is adopted in this paper to train the neural network so that network weights and size are simultaneously estimated. Then, a grid scheduler scheme is proposed to estimate the queuing order that the tasks should be executed and the most appopriate processor assignment so that the demanded QoS are satisfied as much as possible. A fair scheduling policy is considered as the most appropriate. Experimental results on a real grid infrastructure are presented to illustrate the efficiency of the proposed workload prediction--scheduling algorithm
Leonard, Bobby E.; Thompson, Richard E.; Beecher, Georgia C.
2012-01-01
Since the publication of the BEIR VI (1999) report on health risks from radon, a significant amount of new data has been published showing various mechanisms that may affect the ultimate assessment of radon as a carcinogen, in particular the potentially deleterious Bystander Effect (BE) and the potentially beneficial Adaptive Response radio-protection (AR). The case-control radon lung cancer risk data of the pooled 13 European countries radon study (Darby et al 2005, 2006) and the 8 North American pooled study (Krewski et al 2005, 2006) have been evaluated. The large variation in the odds ratios of lung cancer from radon risk is reconciled, based on the large variation in geological and ecological conditions and variation in the degree of adaptive response radio-protection against the bystander effect induced lung damage. The analysis clearly shows Bystander Effect radon lung cancer induction and Adaptive Response reduction in lung cancer in some geographical regions. It is estimated that for radon levels up to about 400 Bq m−3 there is about a 30% probability that no human lung cancer risk from radon will be experienced and a 20% probability that the risk is below the zero-radon, endogenic spontaneous or perhaps even genetically inheritable lung cancer risk rate. The BEIR VI (1999) and EPA (2003) estimates of human lung cancer deaths from radon are most likely significantly excessive. The assumption of linearity of risk, by the Linear No-Threshold Model, with increasing radon exposure is invalid. PMID:22942874
NASA Astrophysics Data System (ADS)
Bogatina, Nina; Sheykina, Nadiia
Dependencies of gravitropic reactions in the static magnetic field and at different frequencies of alternative component of the combined magnetic fields were investigated. These frequencies were equal to the cyclotron frequencies of Са2+, Mg2+ ions and ions of auxin and abscisic acid. It was shown that the increasing of magnetic field noise assisted both to the observation of biological effects and to the acceleration of adaptation processes.
NASA Astrophysics Data System (ADS)
Hasegawa, Takemitsu; Hibino, Susumu; Hosoda, Yohsuke; Ninomiya, Ichizo
2007-08-01
An improvement is made to an automatic quadrature due to Ninomiya (J. Inf. Process. 3:162?170, 1980) of adaptive type based on the Newton?Cotes rule by incorporating a doubly-adaptive algorithm due to Favati, Lotti and Romani (ACM Trans. Math. Softw. 17:207?217, 1991; ACM Trans. Math. Softw. 17:218?232, 1991). We compare the present method in performance with some others by using various test problems including Kahaner?s ones (Computation of numerical quadrature formulas. In: Rice, J.R. (ed.) Mathematical Software, 229?259. Academic, Orlando, FL, 1971).
NASA Astrophysics Data System (ADS)
Zhou, J. X.; Zhang, L.
2005-01-01
Incremental harmonic balance (IHB) formulations are derived for general multiple degrees of freedom (d.o.f.) non-linear autonomous systems. These formulations are developed for a concerned four-d.o.f. aircraft wheel shimmy system with combined Coulomb and velocity-squared damping. A multi-harmonic analysis is performed and amplitudes of limit cycles are predicted. Within a large range of parametric variations with respect to aircraft taxi velocity, the IHB method can, at a much cheaper cost, give results with high accuracy as compared with numerical results given by a parametric continuation method. In particular, the IHB method avoids the stiff problems emanating from numerical treatment of aircraft wheel shimmy system equations. The development is applicable to other vibration control systems that include commonly used dry friction devices or velocity-squared hydraulic dampers.
NASA Astrophysics Data System (ADS)
Pebdani, Arezou Amiri; Shabani, Ali Mohammad Haji; Dadfarnia, Shayessteh; Khodadoust, Saeid
2015-08-01
A simple solid phase microextraction method based on molecularly imprinted polymer sorbent in the hollow fiber (MIP-HF-SPME) combined with fiber optic-linear array spectrophotometer has been applied for the extraction and determination of diclofenac in environmental and biological samples. The effects of different parameters such as pH, times of extraction, type and volume of the organic solvent, stirring rate and donor phase volume on the extraction efficiency of the diclofenac were investigated and optimized. Under the optimal conditions, the calibration graph was linear (r2 = 0.998) in the range of 3.0-85.0 μg L-1 with a detection limit of 0.7 μg L-1 for preconcentration of 25.0 mL of the sample and the relative standard deviation (n = 6) less than 5%. This method was applied successfully for the extraction and determination of diclofenac in different matrices (water, urine and plasma) and accuracy was examined through the recovery experiments.
NASA Astrophysics Data System (ADS)
Ibanez, C. A. G.; Carcellar, B. G., III; Paringit, E. C.; Argamosa, R. J. L.; Faelga, R. A. G.; Posilero, M. A. V.; Zaragosa, G. P.; Dimayacyac, N. A.
2016-06-01
Diameter-at-Breast-Height Estimation is a prerequisite in various allometric equations estimating important forestry indices like stem volume, basal area, biomass and carbon stock. LiDAR Technology has a means of directly obtaining different forest parameters, except DBH, from the behavior and characteristics of point cloud unique in different forest classes. Extensive tree inventory was done on a two-hectare established sample plot in Mt. Makiling, Laguna for a natural growth forest. Coordinates, height, and canopy cover were measured and types of species were identified to compare to LiDAR derivatives. Multiple linear regression was used to get LiDAR-derived DBH by integrating field-derived DBH and 27 LiDAR-derived parameters at 20m, 10m, and 5m grid resolutions. To know the best combination of parameters in DBH Estimation, all possible combinations of parameters were generated and automated using python scripts and additional regression related libraries such as Numpy, Scipy, and Scikit learn were used. The combination that yields the highest r-squared or coefficient of determination and lowest AIC (Akaike's Information Criterion) and BIC (Bayesian Information Criterion) was determined to be the best equation. The equation is at its best using 11 parameters at 10mgrid size and at of 0.604 r-squared, 154.04 AIC and 175.08 BIC. Combination of parameters may differ among forest classes for further studies. Additional statistical tests can be supplemented to help determine the correlation among parameters such as Kaiser- Meyer-Olkin (KMO) Coefficient and the Barlett's Test for Spherecity (BTS).
ERIC Educational Resources Information Center
Harsch, Claudia; Martin, Guido
2012-01-01
We explore how a local rating scale can be based on the Common European Framework CEF-proficiency scales. As part of the scale validation (Alderson, 1991; Lumley, 2002), we examine which adaptations are needed to turn CEF-proficiency descriptors into a rating scale for a local context, and to establish a practicable method to revise the initial…
Technology Transfer Automated Retrieval System (TEKTRAN)
Recent mutational strategies for generating and screening of genes for optimized traits, including directed evolution, domain shuffling, random mutagenesis, and site-directed mutagenesis, have been adapted for automated platforms. Here we discuss the amino acid scanning mutational strategy and its ...
Hirakawa, Akihiro; Wages, Nolan A.; Sato, Hiroyuki; Matsui, Shigeyuki
2016-01-01
Little is known about the relative performance of competing model-based dose-finding methods for combination phase I trials. In this study, we focused on five model-based dose-finding methods that have been recently developed. We compared the recommendation rates for true maximum-tolerated dose combinations (MTDCs) and over-dose combinations among these methods under 16 scenarios for 3 × 3, 4 × 4, 2 × 4, and 3 × 5 dose combination matrices. We found that performance of the model-based dose-finding methods varied depending on (1) whether the dose combination matrix is square or not; (2) whether the true MTDCs exist within the same group along the diagonals of the dose combination matrix; and (3) the number of true MTDCs. We discuss the details of the operating characteristics and the advantages and disadvantages of the five methods compared. PMID:25974405
Zhu, Eric F; Gai, Shuning A; Opel, Cary F; Kwan, Byron H; Surana, Rishi; Mihm, Martin C; Kauke, Monique J; Moynihan, Kelly D; Angelini, Alessandro; Williams, Robert T; Stephan, Matthias T; Kim, Jacob S; Yaffe, Michael B; Irvine, Darrell J; Weiner, Louis M; Dranoff, Glenn; Wittrup, K Dane
2015-04-13
Cancer immunotherapies under development have generally focused on either stimulating T cell immunity or driving antibody-directed effector functions of the innate immune system such as antibody-dependent cell-mediated cytotoxicity (ADCC). We find that a combination of an anti-tumor antigen antibody and an untargeted IL-2 fusion protein with delayed systemic clearance induces significant tumor control in aggressive isogenic tumor models via a concerted innate and adaptive response involving neutrophils, NK cells, macrophages, and CD8(+) T cells. This combination therapy induces an intratumoral "cytokine storm" and extensive lymphocyte infiltration. Adoptive transfer of anti-tumor T cells together with this combination therapy leads to robust cures of established tumors and development of immunological memory. PMID:25873172