Neurons with radial basis like rate functions.
Kovács, Zsolt László
2005-01-01
Artificial neural networks constructed with "locally tuned processing units" and more generally referred to as "radial basis function networks" have been proposed by a number of workers. In this communication, I submit a conjecture, based on indirect experimental and direct computational evidence of the Hodgkin-Huxley model, that there may be biological neurons in nervous systems for which the rate function is locally tuned. If proved to be valid, this conjecture may simplify neurodynamic models of some functions of nervous systems.
Generalized multiscale radial basis function networks.
Billings, Stephen A; Wei, Hua-Liang; Balikhin, Michael A
2007-12-01
A novel modelling framework is proposed for constructing parsimonious and flexible multiscale radial basis function networks (RBF). Unlike a conventional standard single scale RBF network, where all the basis functions have a common kernel width, the new network structure adopts multiscale Gaussian functions as the bases, where each selected centre has multiple kernel widths, to provide more flexible representations with better generalization properties for general nonlinear dynamical systems. As a direct extension of the traditional single scale Gaussian networks, the new multiscale network is easy to implement and is quick to learn using standard learning algorithms. A k-means clustering algorithm and an improved orthogonal least squares (OLS) algorithm are used to determine the unknown parameters in the network model including the centres and widths of the basis functions, and the weights between the basis functions. It is demonstrated that the new network can lead to a parsimonious model with much better generalization property compared with the traditional single width RBF networks.
Generalization performance of radial basis function networks.
Lei, Yunwen; Ding, Lixin; Zhang, Wensheng
2015-03-01
This paper studies the generalization performance of radial basis function (RBF) networks using local Rademacher complexities. We propose a general result on controlling local Rademacher complexities with the L1 -metric capacity. We then apply this result to estimate the RBF networks' complexities, based on which a novel estimation error bound is obtained. An effective approximation error bound is also derived by carefully investigating the Hölder continuity of the lp loss function's derivative. Furthermore, it is demonstrated that the RBF network minimizing an appropriately constructed structural risk admits a significantly better learning rate when compared with the existing results. An empirical study is also performed to justify the application of our structural risk in model selection.
A radial basis function Galerkin method for inhomogeneous nonlocal diffusion
Lehoucq, Richard B.; Rowe, Stephen T.
2016-02-01
We introduce a discretization for a nonlocal diffusion problem using a localized basis of radial basis functions. The stiffness matrix entries are assembled by a special quadrature routine unique to the localized basis. Combining the quadrature method with the localized basis produces a well-conditioned, sparse, symmetric positive definite stiffness matrix. We demonstrate that both the continuum and discrete problems are well-posed and present numerical results for the convergence behavior of the radial basis function method. As a result, we explore approximating the solution to anisotropic differential equations by solving anisotropic nonlocal integral equations using the radial basis function method.
Radial basis function neural networks applied to NASA SSME data
NASA Technical Reports Server (NTRS)
Wheeler, Kevin R.; Dhawan, Atam P.
1993-01-01
This paper presents a brief report on the application of Radial Basis Function Neural Networks (RBFNN) to the prediction of sensor values for fault detection and diagnosis of the Space Shuttle's Main Engines (SSME). The location of the Radial Basis Function (RBF) node centers was determined with a K-means clustering algorithm. A neighborhood operation about these center points was used to determine the variances of the individual processing notes.
Orthogonal least squares learning algorithm for radial basis function networks.
Chen, S; Cowan, C N; Grant, P M
1991-01-01
The radial basis function network offers a viable alternative to the two-layer neural network in many applications of signal processing. A common learning algorithm for radial basis function networks is based on first choosing randomly some data points as radial basis function centers and then using singular-value decomposition to solve for the weights of the network. Such a procedure has several drawbacks, and, in particular, an arbitrary selection of centers is clearly unsatisfactory. The authors propose an alternative learning procedure based on the orthogonal least-squares method. The procedure chooses radial basis function centers one by one in a rational way until an adequate network has been constructed. In the algorithm, each selected center maximizes the increment to the explained variance or energy of the desired output and does not suffer numerical ill-conditioning problems. The orthogonal least-squares learning strategy provides a simple and efficient means for fitting radial basis function networks. This is illustrated using examples taken from two different signal processing applications.
Point Set Denoising Using Bootstrap-Based Radial Basis Function.
Liew, Khang Jie; Ramli, Ahmad; Abd Majid, Ahmad
2016-01-01
This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.
Point Set Denoising Using Bootstrap-Based Radial Basis Function
Ramli, Ahmad; Abd. Majid, Ahmad
2016-01-01
This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study. PMID:27315105
A radial basis function neurocomputer implemented with analog VLSI circuits
NASA Technical Reports Server (NTRS)
Watkins, Steven S.; Chau, Paul M.; Tawel, Raoul
1992-01-01
An electronic neurocomputer which implements a radial basis function neural network (RBFNN) is described. The RBFNN is a network that utilizes a radial basis function as the transfer function. The key advantages of RBFNNs over existing neural network architectures include reduced learning time and the ease of VLSI implementation. This neurocomputer is based on an analog/digital hybrid design and has been constructed with both custom analog VLSI circuits and a commercially available digital signal processor. The hybrid architecture is selected because it offers high computational performance while compensating for analog inaccuracies, and it features the ability to model large problems.
Decision trees can initialize radial-basis function networks.
Kubat, M
1998-01-01
Successful implementations of radial-basis function (RBF) networks for classification tasks must deal with architectural issues, the burden of irrelevant attributes, scaling, and some other problems. This paper addresses these issues by initializing RBF networks with decision trees that define relatively pure regions in the instance space; each of these regions then determines one basis function. The resulting network is compact, easy to induce, and has favorable classification accuracy.
Surface interpolation with radial basis functions for medical imaging
Carr, J.C.; Beatson, R.K.; Fright, W.R.
1997-02-01
Radial basis functions are presented as a practical solution to the problem of interpolating incomplete surfaces derived from three-dimensional (3-D) medical graphics. The specific application considered is the design of cranial implants for the repair of defects, usually holes, in the skull. Radial basis functions impose few restrictions on the geometry of the interpolation centers and are suited to problems where interpolation centers do not form a regular grid. However, their high computational requirements have previously limited their use to problems where the number of interpolation centers is small (<300). Recently developed fast evaluation techniques have overcome these limitations and made radial basis interpolation a practical approach for larger data sets. In this paper radial basis functions are fitted to depth-maps of the skull`s surface, obtained from X-ray computed tomography (CT) data using ray-tracing techniques. They are used to smoothly interpolate the surface of the skull across defect regions. The resulting mathematical description of the skull`s surface can be evaluated at any desired resolution to be rendered on a graphics workstation or to generate instructions for operating a computer numerically controlled (CNC) mill.
Universal approximation by radial basis function networks of Delsarte translates.
Arteaga, Cristian; Marrero, Isabel
2013-10-01
We prove that, under certain mild conditions on the kernel function (or activation function), the family of radial basis function neural networks obtained by replacing the usual translation with the Delsarte one, and taking the same smoothing factor in all kernel nodes, has the universal approximation property.
Precision of a radial basis function neural network tracking method
NASA Technical Reports Server (NTRS)
Hanan, J.; Zhou, H.; Chao, T. H.
2003-01-01
The precision of a radial basis function (RBF) neural network based tracking method has been assessed against real targets. Precision was assessed against traditionally measured frame-by-frame measurements from the recorded data set. The results show the potential limit for the technique and reveal intricacies associated with empirical data not necessarily observed in simulations.
Shakespeare vs. Fletcher: A Stylometric Analysis by Radial Basis Functions.
ERIC Educational Resources Information Center
Lowe, David; Matthews, Robert
1995-01-01
Illustrates how Radial Basis Function (RBF) network techniques can be used to explore questions concerning authorship of historic documents. Demonstrates the utility and potential for using quantitative techniques to assist in the decision-making process in relatively subjective disciplines. Compares RBF neural network techniques with more…
Integration of macromolecular diffraction data using radial basis function networks.
Pokrić, B; Allinson, N M; Helliwell, J R
2000-11-01
This paper presents a novel approach for intensity calculation of X-ray diffraction spots based on a two-stage radial basis function (RBF) network. The first stage uses pre-determined reference profiles from a database as basis functions in order to locate the diffraction spots and identify any overlapping regions. The second-stage RBF network employs narrow basis functions capable of local modifications of the reference profiles leading to a more accurate observed diffraction spot approximation and therefore accurate determination of spot positions and integrated intensities.
Direction-dependent learning approach for radial basis function networks.
Singla, Puneet; Subbarao, Kamesh; Junkins, John L
2007-01-01
Direction-dependent scaling, shaping, and rotation of Gaussian basis functions are introduced for maximal trend sensing with minimal parameter representations for input output approximation. It is shown that shaping and rotation of the radial basis functions helps in reducing the total number of function units required to approximate any given input-output data, while improving accuracy. Several alternate formulations that enforce minimal parameterization of the most general radial basis functions are presented. A novel "directed graph" based algorithm is introduced to facilitate intelligent direction based learning and adaptation of the parameters appearing in the radial basis function network. Further, a parameter estimation algorithm is incorporated to establish starting estimates for the model parameters using multiple windows of the input-output data. The efficacy of direction-dependent shaping and rotation in function approximation is evaluated by modifying the minimal resource allocating network and considering different test examples. The examples are drawn from recent literature to benchmark the new algorithm versus existing methods.
Combining regression trees and radial basis function networks.
Orr, M; Hallam, J; Takezawa, K; Murra, A; Ninomiya, S; Oide, M; Leonard, T
2000-12-01
We describe a method for non-parametric regression which combines regression trees with radial basis function networks. The method is similar to that of Kubat, who was first to suggest such a combination, but has some significant improvements. We demonstrate the features of the new method, compare its performance with other methods on DELVE data sets and apply it to a real world problem involving the classification of soybean plants from digital images.
Use of Normalized Radial Basis Function in Hydrology
Cotar, Anton; Brilly, Mitja
2008-11-13
In this article we will present a use of normalized radial basis function in hydrology for prediction of missing river Reka runoff data. The method is based on multidimensional normal distribution, where standard deviation is first optimized and later the whole prediction process is learned on existing data [5]. We can conclude, that the method works very well for middle ranges of data, but not so well for extremes because of its interpolating nature.
All-frequency lighting with multiscale spherical radial basis functions.
Lam, Ping-Man; Ho, Tze-Yiu; Leung, Chi-Sing; Wong, Tien-Tsin
2010-01-01
This paper proposes a novel multiscale spherical radial basis function (MSRBF) representation for all-frequency lighting. It supports the illumination of distant environment as well as the local illumination commonly used in practical applications, such as games. The key is to define a multiscale and hierarchical structure of spherical radial basis functions (SRBFs) with basis functions uniformly distributed over the sphere. The basis functions are divided into multiple levels according to their coverage (widths). Within the same level, SRBFs have the same width. Larger width SRBFs are responsible for lower frequency lighting while the smaller width ones are responsible for the higher frequency lighting. Hence, our approach can achieve the true all-frequency lighting that is not achievable by the single-scale SRBF approach. Besides, the MSRBF approach is scalable as coarser rendering quality can be achieved without reestimating the coefficients from the raw data. With the homogeneous form of basis functions, the rendering is highly efficient. The practicability of the proposed method is demonstrated with real-time rendering and effective compression for tractable storage.
Side effects of normalising radial basis function networks.
Shorten, R; Murray-Smith, R
1996-05-01
Normalisation of the basis function activations in a Radial Basis Function (RBF) network is a common way of achieving the partition of unity often desired for modelling applications. It results in the basis functions covering the whole of the input space to the same degree. However, normalisation of the basis functions can lead to other effects which are sometimes less desirable for modelling applications. This paper describes some side effects of normalisation which fundamentally alter properties of the basis functions, e.g. the shape is no longer uniform, maxima of basis functions can be shifted from their centres, and the basis functions are no longer guaranteed to decrease monotonically as distance from their centre increases--in many cases basis functions can 'reactivate', i.e. re-appear far from the basis function centre. This paper examines how these phenomena occur, discusses their relevance for non-linear function approximation and examines the effect of normalisation on the network condition number and weights.
The Gaussian radial basis function method for plasma kinetic theory
NASA Astrophysics Data System (ADS)
Hirvijoki, E.; Candy, J.; Belli, E.; Embréus, O.
2015-10-01
Description of a magnetized plasma involves the Vlasov equation supplemented with the non-linear Fokker-Planck collision operator. For non-Maxwellian distributions, the collision operator, however, is difficult to compute. In this Letter, we introduce Gaussian Radial Basis Functions (RBFs) to discretize the velocity space of the entire kinetic system, and give the corresponding analytical expressions for the Vlasov and collision operator. Outlining the general theory, we also highlight the connection to plasma fluid theories, and give 2D and 3D numerical solutions of the non-linear Fokker-Planck equation. Applications are anticipated in both astrophysical and laboratory plasmas.
Learning and generalization in radial basis function networks.
Freeman, J A; Saad, D
1995-09-01
The two-layer radial basis function network, with fixed centers of the basis functions, is analyzed within a stochastic training paradigm. Various definitions of generalization error are considered, and two such definitions are employed in deriving generic learning curves and generalization properties, both with and without a weight decay term. The generalization error is shown analytically to be related to the evidence and, via the evidence, to the prediction error and free energy. The generalization behavior is explored; the generic learning curve is found to be inversely proportional to the number of training pairs presented. Optimization of training is considered by minimizing the generalization error with respect to the free parameters of the training algorithms. Finally, the effect of the joint activations between hidden-layer units is examined and shown to speed training.
Radial basis function networks and complexity regularization in function learning.
Krzyzak, A; Linder, T
1998-01-01
In this paper we apply the method of complexity regularization to derive estimation bounds for nonlinear function estimation using a single hidden layer radial basis function network. Our approach differs from previous complexity regularization neural-network function learning schemes in that we operate with random covering numbers and l(1) metric entropy, making it possible to consider much broader families of activation functions, namely functions of bounded variation. Some constraints previously imposed on the network parameters are also eliminated this way. The network is trained by means of complexity regularization involving empirical risk minimization. Bounds on the expected risk in terms of the sample size are obtained for a large class of loss functions. Rates of convergence to the optimal loss are also derived.
Efficient VLSI Architecture for Training Radial Basis Function Networks
Fan, Zhe-Cheng; Hwang, Wen-Jyi
2013-01-01
This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networks. The architecture contains the circuits for fuzzy C-means (FCM) and the recursive Least Mean Square (LMS) operations. The FCM circuit is designed for the training of centers in the hidden layer of the RBF network. The recursive LMS circuit is adopted for the training of connecting weights in the output layer. The architecture is implemented by the field programmable gate array (FPGA). It is used as a hardware accelerator in a system on programmable chip (SOPC) for real-time training and classification. Experimental results reveal that the proposed RBF architecture is an effective alternative for applications where fast and efficient RBF training is desired. PMID:23519346
Learning without local minima in radial basis function networks.
Bianchini, M; Frasconi, P; Gori, M
1995-01-01
Learning from examples plays a central role in artificial neural networks. The success of many learning schemes is not guaranteed, however, since algorithms like backpropagation may get stuck in local minima, thus providing suboptimal solutions. For feedforward networks, optimal learning can be achieved provided that certain conditions on the network and the learning environment are met. This principle is investigated for the case of networks using radial basis functions (RBF). It is assumed that the patterns of the learning environment are separable by hyperspheres. In that case, we prove that the attached cost function is local minima free with respect to all the weights. This provides us with some theoretical foundations for a massive application of RBF in pattern recognition.
An incremental design of radial basis function networks.
Yu, Hao; Reiner, Philip D; Xie, Tiantian; Bartczak, Tomasz; Wilamowski, Bogdan M
2014-10-01
This paper proposes an offline algorithm for incrementally constructing and training radial basis function (RBF) networks. In each iteration of the error correction (ErrCor) algorithm, one RBF unit is added to fit and then eliminate the highest peak (or lowest valley) in the error surface. This process is repeated until a desired error level is reached. Experimental results on real world data sets show that the ErrCor algorithm designs very compact RBF networks compared with the other investigated algorithms. Several benchmark tests such as the duplicate patterns test and the two spiral problem were applied to show the robustness of the ErrCor algorithm. The proposed ErrCor algorithm generates very compact networks. This compactness leads to greatly reduced computation times of trained networks.
Efficient VLSI architecture for training radial basis function networks.
Fan, Zhe-Cheng; Hwang, Wen-Jyi
2013-03-19
This paper presents a novel VLSI architecture for the training of radial basis function (RBF) networks. The architecture contains the circuits for fuzzy C-means (FCM) and the recursive Least Mean Square (LMS) operations. The FCM circuit is designed for the training of centers in the hidden layer of the RBF network. The recursive LMS circuit is adopted for the training of connecting weights in the output layer. The architecture is implemented by the field programmable gate array (FPGA). It is used as a hardware accelerator in a system on programmable chip (SOPC) for real-time training and classification. Experimental results reveal that the proposed RBF architecture is an effective alternative for applications where fast and efficient RBF training is desired.
Dynamics of learning near singularities in radial basis function networks.
Wei, Haikun; Amari, Shun-Ichi
2008-09-01
The radial basis function (RBF) networks are one of the most widely used models for function approximation in the regression problem. In the learning paradigm, the best approximation is recursively or iteratively searched for based on observed data (teacher signals). One encounters difficulties in such a process when two component basis functions become identical, or when the magnitude of one component becomes null. In this case, the number of the components reduces by one, and then the reduced component recovers as the learning process proceeds further, provided such a component is necessary for the best approximation. Strange behaviors, especially the plateau phenomena, have been observed in dynamics of learning when such reduction occurs. There exist singularities in the space of parameters, and the above reduction takes place at the singular regions. This paper focuses on a detailed analysis of the dynamical behaviors of learning near the overlap and elimination singularities in RBF networks, based on the averaged learning equation that is applicable to both on-line and batch mode learning. We analyze the stability on the overlap singularity by solving the eigenvalues of the Hessian explicitly. Based on the stability analysis, we plot the analytical dynamic vector fields near the singularity, which are then compared to those real trajectories obtained by a numeric method. We also confirm the existence of the plateaus in both batch and on-line learning by simulation.
Adaptive radial basis function mesh deformation using data reduction
NASA Astrophysics Data System (ADS)
Gillebaart, T.; Blom, D. S.; van Zuijlen, A. H.; Bijl, H.
2016-09-01
Radial Basis Function (RBF) mesh deformation is one of the most robust mesh deformation methods available. Using the greedy (data reduction) method in combination with an explicit boundary correction, results in an efficient method as shown in literature. However, to ensure the method remains robust, two issues are addressed: 1) how to ensure that the set of control points remains an accurate representation of the geometry in time and 2) how to use/automate the explicit boundary correction, while ensuring a high mesh quality. In this paper, we propose an adaptive RBF mesh deformation method, which ensures the set of control points always represents the geometry/displacement up to a certain (user-specified) criteria, by keeping track of the boundary error throughout the simulation and re-selecting when needed. Opposed to the unit displacement and prescribed displacement selection methods, the adaptive method is more robust, user-independent and efficient, for the cases considered. Secondly, the analysis of a single high aspect ratio cell is used to formulate an equation for the correction radius needed, depending on the characteristics of the correction function used, maximum aspect ratio, minimum first cell height and boundary error. Based on the analysis two new radial basis correction functions are derived and proposed. This proposed automated procedure is verified while varying the correction function, Reynolds number (and thus first cell height and aspect ratio) and boundary error. Finally, the parallel efficiency is studied for the two adaptive methods, unit displacement and prescribed displacement for both the CPU as well as the memory formulation with a 2D oscillating and translating airfoil with oscillating flap, a 3D flexible locally deforming tube and deforming wind turbine blade. Generally, the memory formulation requires less work (due to the large amount of work required for evaluating RBF's), but the parallel efficiency reduces due to the limited
Reconstructing the magnetosphere from data using radial basis functions
NASA Astrophysics Data System (ADS)
Andreeva, Varvara A.; Tsyganenko, Nikolai A.
2016-03-01
A new method is proposed to derive from data magnetospheric magnetic field configurations without any a priori assumptions on the geometry of electric currents. The approach utilizes large sets of archived satellite data and uses an advanced technique to represent the field as a sum of toroidal and poloidal parts, whose generating potentials Ψ1 and Ψ2 are expanded into series of radial basis functions (RBFs) with their nodes regularly distributed over the 3-D modeling domain. The method was tested by reconstructing the inner and high-latitude field within geocentric distances up to 12RE on the basis of magnetometer data of Geotail, Polar, Cluster, Time History of Events and Macroscale Interactions during Substorms, and Van Allen space probes, taken during 1995-2015. Four characteristic states of the magnetosphere before and during a disturbance have been modeled: a quiet prestorm period, storm deepening phase with progressively decreasing SYM-H index, the storm maximum around the negative peak of SYM-H, and the recovery phase. Fitting the RBF model to data faithfully resolved contributions to the total magnetic field from all principal sources, including the westward and eastward ring current, the tail current, diamagnetic currents associated with the polar cusps, and the large-scale effect of the field-aligned currents. For two main phase conditions, the model field exhibited a strong dawn-dusk asymmetry of the low-latitude magnetic depression, extending to low altitudes and partly spreading sunward from the terminator plane in the dusk sector. The RBF model was found to resolve even finer details, such as the bifurcation of the innermost tail current. The method can be further developed into a powerful tool for data-based studies of the magnetospheric currents.
Signal detection using the radial basis function coupled map lattice.
Leung, H; Hennessey, G; Drosopoulos, A
2000-01-01
Conventional detection methods used in current marine radar systems do not perform efficiently in detecting small targets embedded in a clutter environment. Based on a recent observation that sea clutter, radar echoes from a sea surface, is chaotic rather than random, we propose using a spatial temporal predictor to reconstruct the chaotic dynamic of sea clutter because electromagnetic wave scattering is a spatial temporal phenomenon which is physically modeled by partial differential equations. The spatial temporal predictor used here is called radial basis function coupled map lattice (RBF-CML) which uses a linear combiner to fuse either measurements in different spatial domains for an RBF prediction or predictions from several RBF nets operated on different spatial regions. Using real-life radar data, it is shown that the RBF-CML is an effective method to reconstruct the sea clutter dynamic. The RBF-CML predictor is then applied to detect small targets in sea clutter using the constant false alarm rate (CFAR) principle. The spatial temporal approach is shown, both theoretically and experimentally, to be superior to a conventional CFAR detector.
Radial basis function networks GPU-based implementation.
Brandstetter, Andreas; Artusi, Alessandro
2008-12-01
Neural networks (NNs) have been used in several areas, showing their potential but also their limitations. One of the main limitations is the long time required for the training process; this is not useful in the case of a fast training process being required to respond to changes in the application domain. A possible way to accelerate the learning process of an NN is to implement it in hardware, but due to the high cost and the reduced flexibility of the original central processing unit (CPU) implementation, this solution is often not chosen. Recently, the power of the graphic processing unit (GPU), on the market, has increased and it has started to be used in many applications. In particular, a kind of NN named radial basis function network (RBFN) has been used extensively, proving its power. However, their limiting time performances reduce their application in many areas. In this brief paper, we describe a GPU implementation of the entire learning process of an RBFN showing the ability to reduce the computational cost by about two orders of magnitude with respect to its CPU implementation.
Ultrasonic flaw detection using radial basis function networks (RBFNs).
Gil Pita, R; Vicen, R; Rosa, M; Jarabo, M P; Vera, P; Curpian, J
2004-04-01
Ultrasonic flaw detection has been studied many times in the literature. Schemes based on thresholding after a previous matched filter use to be the best solution, but results obtained with this method are only satisfactory when scattering and attenuation are not considered. In this paper, we propose an alternative solution to thresholding detection method. We deal with the usage of different flaw detection methods comparing them with the proposed one. The experiment tries to determinate whether a given ultrasonic signal contains a flaw echo or not. Starting with a set of 24,000 patterns with 750 samples each one, two subsets are defined for the experiments. The first one, the training set, is used to obtain the detection parameters of the different methods, and the second one is used to test the performance of them. The proposed method is based on radial basis functions networks, one of the most powerful neural network techniques. This signal processing technique tries to find the optimal decision criterion. Comparing this method with thresholding based ones, an improvement over 25-30% is obtained, depending on the probability of false alarm. So our new method is a good alternative to flaw detection problem.
A growing and pruning method for radial basis function networks.
Bortman, M; Aladjem, M
2009-06-01
A recently published generalized growing and pruning (GGAP) training algorithm for radial basis function (RBF) neural networks is studied and modified. GGAP is a resource-allocating network (RAN) algorithm, which means that a created network unit that consistently makes little contribution to the network's performance can be removed during the training. GGAP states a formula for computing the significance of the network units, which requires a d-fold numerical integration for arbitrary probability density function p(x) of the input data x (x in R(d)) . In this work, the GGAP formula is approximated using a Gaussian mixture model (GMM) for p(x) and an analytical solution of the approximated unit significance is derived. This makes it possible to employ the modified GGAP for input data having complex and high-dimensional p(x), which was not possible in the original GGAP. The results of an extensive experimental study show that the modified algorithm outperforms the original GGAP achieving both a lower prediction error and reduced complexity of the trained network.
Radial basis function interpolation in the limit of increasingly flat basis functions
NASA Astrophysics Data System (ADS)
Kindelan, Manuel; Moscoso, Miguel; González-Rodríguez, Pedro
2016-02-01
We propose a new approach to study Radial Basis Function (RBF) interpolation in the limit of increasingly flat functions. The new approach is based on the semi-analytical computation of the Laurent series of the inverse of the RBF interpolation matrix described in a previous paper [3]. Once the Laurent series is obtained, it can be used to compute the limiting polynomial interpolant, the optimal shape parameter of the RBFs used for interpolation, and the weights of RBF finite difference formulas, among other things.
Estimation of spatiotemporal neural activity using radial basis function networks.
Anderson, R W; Das, S; Keller, E L
1998-12-01
We report a method using radial basis function (RBF) networks to estimate the time evolution of population activity in topologically organized neural structures from single-neuron recordings. This is an important problem in neuroscience research, as such estimates may provide insights into systems-level function of these structures. Since single-unit neural data tends to be unevenly sampled and highly variable under similar behavioral conditions, obtaining such estimates is a difficult task. In particular, a class of cells in the superior colliculus called buildup neurons can have very narrow regions of saccade vectors for which they discharge at high rates but very large surround regions over which they discharge at low, but not zero, levels. Estimating the dynamic movement fields for these cells for two spatial dimensions at closely spaced timed intervals is a difficult problem, and no general method has been described that can be applied to all buildup cells. Estimation of individual collicular cells' spatiotemporal movement fields is a prerequisite for obtaining reliable two-dimensional estimates of the population activity on the collicular motor map during saccades. Therefore, we have developed several computational-geometry-based algorithms that regularize the data before computing a surface estimation using RBF networks. The method is then expanded to the problem of estimating simultaneous spatiotemporal activity occurring across the superior colliculus during a single movement (the inverse problem). In principle, this methodology could be applied to any neural structure with a regular, two-dimensional organization, provided a sufficient spatial distribution of sampled neurons is available.
Three learning phases for radial-basis-function networks.
Schwenker, F; Kestler, H A; Palm, G
2001-05-01
In this paper, learning algorithms for radial basis function (RBF) networks are discussed. Whereas multilayer perceptrons (MLP) are typically trained with backpropagation algorithms, starting the training procedure with a random initialization of the MLP's parameters, an RBF network may be trained in many different ways. We categorize these RBF training methods into one-, two-, and three-phase learning schemes. Two-phase RBF learning is a very common learning scheme. The two layers of an RBF network are learnt separately; first the RBF layer is trained, including the adaptation of centers and scaling parameters, and then the weights of the output layer are adapted. RBF centers may be trained by clustering, vector quantization and classification tree algorithms, and the output layer by supervised learning (through gradient descent or pseudo inverse solution). Results from numerical experiments of RBF classifiers trained by two-phase learning are presented in three completely different pattern recognition applications: (a) the classification of 3D visual objects; (b) the recognition hand-written digits (2D objects); and (c) the categorization of high-resolution electrocardiograms given as a time series (ID objects) and as a set of features extracted from these time series. In these applications, it can be observed that the performance of RBF classifiers trained with two-phase learning can be improved through a third backpropagation-like training phase of the RBF network, adapting the whole set of parameters (RBF centers, scaling parameters, and output layer weights) simultaneously. This, we call three-phase learning in RBF networks. A practical advantage of two- and three-phase learning in RBF networks is the possibility to use unlabeled training data for the first training phase. Support vector (SV) learning in RBF networks is a different learning approach. SV learning can be considered, in this context of learning, as a special type of one-phase learning, where
Meshless Local Petrov-Galerkin Euler-Bernoulli Beam Problems: A Radial Basis Function Approach
NASA Technical Reports Server (NTRS)
Raju, I. S.; Phillips, D. R.; Krishnamurthy, T.
2003-01-01
A radial basis function implementation of the meshless local Petrov-Galerkin (MLPG) method is presented to study Euler-Bernoulli beam problems. Radial basis functions, rather than generalized moving least squares (GMLS) interpolations, are used to develop the trial functions. This choice yields a computationally simpler method as fewer matrix inversions and multiplications are required than when GMLS interpolations are used. Test functions are chosen as simple weight functions as in the conventional MLPG method. Compactly and noncompactly supported radial basis functions are considered. The non-compactly supported cubic radial basis function is found to perform very well. Results obtained from the radial basis MLPG method are comparable to those obtained using the conventional MLPG method for mixed boundary value problems and problems with discontinuous loading conditions.
Chen, S; Mulgrew, B; Grant, P M
1993-01-01
The application of a radial basis function network to digital communications channel equalization is examined. It is shown that the radial basis function network has an identical structure to the optimal Bayesian symbol-decision equalizer solution and, therefore, can be employed to implement the Bayesian equalizer. The training of a radial basis function network to realize the Bayesian equalization solution can be achieved efficiently using a simple and robust supervised clustering algorithm. During data transmission a decision-directed version of the clustering algorithm enables the radial basis function network to track a slowly time-varying environment. Moreover, the clustering scheme provides an automatic compensation for nonlinear channel and equipment distortion. Computer simulations are included to illustrate the analytical results.
Sensitivity analysis applied to the construction of radial basis function networks.
Shi, D; Yeung, D S; Gao, J
2005-09-01
Conventionally, a radial basis function (RBF) network is constructed by obtaining cluster centers of basis function by maximum likelihood learning. This paper proposes a novel learning algorithm for the construction of radial basis function using sensitivity analysis. In training, the number of hidden neurons and the centers of their radial basis functions are determined by the maximization of the output's sensitivity to the training data. In classification, the minimal number of such hidden neurons with the maximal sensitivity will be the most generalizable to unknown data. Our experimental results show that our proposed sensitivity-based RBF classifier outperforms the conventional RBFs and is as accurate as support vector machine (SVM). Hence, sensitivity analysis is expected to be a new alternative way to the construction of RBF networks.
Sherstinsky, A; Picard, R W
1996-01-01
The efficiency of the orthogonal least squares (OLS) method for training approximation networks is examined using the criterion of energy compaction. We show that the selection of basis vectors produced by the procedure is not the most compact when the approximation is performed using a nonorthogonal basis. Hence, the algorithm does not produce the smallest possible networks for a given approximation error. Specific examples are given using the Gaussian radial basis functions type of approximation networks.
Satisfiability of logic programming based on radial basis function neural networks
NASA Astrophysics Data System (ADS)
Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged; Choon, Ong Hong
2014-07-01
In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We applied the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.
Satisfiability of logic programming based on radial basis function neural networks
Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged; Choon, Ong Hong
2014-07-10
In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We applied the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.
Finite element basis for the expansion of radial wavefunction in quantum scattering calculations
NASA Astrophysics Data System (ADS)
Hwang, Woonglin; Sup Lee, Yoon; Park, Seung C.
1991-11-01
Radial wavefunctions in quantum scattering calculations are expanded in terms of two shape functions for each finite element. This approach is the R matrix version of Kohn's variational method and also directly applicable to S matrix in the log-derivative version. The linear algebra involved amounts to solving definite banded systems. In this basis set method, R matrix or log-derivative matrix is greatly simplified and the computational effort is linearly proportional to the number of radial basis functions, promising computational efficiencies for large scale calculations. Convergences for test vases are also reasonably rapid.
Relaxed conditions for radial-basis function networks to be universal approximators.
Liao, Yi; Fang, Shu-Cherng; Nuttle, Henry L W
2003-09-01
In this paper, we investigate the universal approximation property of Radial Basis Function (RBF) networks. We show that RBFs are not required to be integrable for the REF networks to be universal approximators. Instead, RBF networks can uniformly approximate any continuous function on a compact set provided that the radial basis activation function is continuous almost everywhere, locally essentially bounded, and not a polynomial. The approximation in L(p)(micro)(1 < or = p < infinity) space is also discussed. Some experimental results are reported to illustrate our findings.
Radial Basis Function Networks: Generalization in Over-realizable and Unrealizable Scenarios.
Saad, David; Freeman, Jason A. S.
1996-12-01
Learning and generalization in a two-layer radial basis function network, with fixed centres of the basis functions, is examined within a stochastic training paradigm. Employing a Bayesian approach, expressions for generalization error are derived under the assumption that the generating mechanism (teacher) for the training data is also a radial basis function network, but one for which the basis function centres and widths need not correspond to those of the student network. The effects of regularization, via a weight decay term, are examined. The cases in which the student has greater representational power than the teacher (over-realizable), and in which the teacher has greater power than the student (unrealizable) are studied. Dependence on knowing the centres of the teacher is eliminated by introducing a single degree-of-confidence parameter. Finally, simulations are performed which validate the analytic results. Copyright 1996 Elsevier Science Ltd.
An efficient ensemble of radial basis functions method based on quadratic programming
NASA Astrophysics Data System (ADS)
Shi, Renhe; Liu, Li; Long, Teng; Liu, Jian
2016-07-01
Radial basis function (RBF) surrogate models have been widely applied in engineering design optimization problems to approximate computationally expensive simulations. Ensemble of radial basis functions (ERBF) using the weighted sum of stand-alone RBFs improves the approximation performance. To achieve a good trade-off between the accuracy and efficiency of the modelling process, this article presents a novel efficient ERBF method to determine the weights through solving a quadratic programming subproblem, denoted ERBF-QP. Several numerical benchmark functions are utilized to test the performance of the proposed ERBF-QP method. The results show that ERBF-QP can significantly improve the modelling efficiency compared with several existing ERBF methods. Moreover, ERBF-QP also provides satisfactory performance in terms of approximation accuracy. Finally, the ERBF-QP method is applied to a satellite multidisciplinary design optimization problem to illustrate its practicality and effectiveness for real-world engineering applications.
Optical design and tolerancing of freeform surfaces using anisotropic radial basis functions
NASA Astrophysics Data System (ADS)
Maksimovic, Milan
2016-07-01
We investigate use of the anisotropic radial basis functions expansion as a means to represent surface errors on aspheric and freeform surfaces. We show how the optimal choice of the shape parameter and the placement of radial basis function (RBF) nodes can increase accuracy of the surface approximation. We show an example of the adaptive grid refinement. In our approach, complex surfaces are modeled with general arbitrary representation while the anisotropic RBFs expansion models perturbation of the base surface. We show how both the global and the localized surface errors can be modeled across a wide spatial frequency range. With our method, the impact of the structured surface errors on the arbitrary surfaces when applied on the standardized image quality metrics can be assessed for the purpose of optical tolerancing.
NASA Astrophysics Data System (ADS)
Petković, Dalibor; Gocic, Milan; Shamshirband, Shahaboddin; Qasem, Sultan Noman; Trajkovic, Slavisa
2016-08-01
Accurate estimation of the reference evapotranspiration (ET0) is important for the water resource planning and scheduling of irrigation systems. For this purpose, the radial basis function network with particle swarm optimization (RBFN-PSO) and radial basis function network with back propagation (RBFN-BP) were used in this investigation. The FAO-56 Penman-Monteith equation was used as reference equation to estimate ET0 for Serbia during the period of 1980-2010. The obtained simulation results confirmed the proposed models and were analyzed using the root mean-square error (RMSE), the mean absolute error (MAE), and the coefficient of determination ( R 2). The analysis showed that the RBFN-PSO had better statistical characteristics than RBFN-BP and can be helpful for the ET0 estimation.
A Meshless Method Using Radial Basis Functions for Beam Bending Problems
NASA Technical Reports Server (NTRS)
Raju, I. S.; Phillips, D. R.; Krishnamurthy, T.
2004-01-01
A meshless local Petrov-Galerkin (MLPG) method that uses radial basis functions (RBFs) as trial functions in the study of Euler-Bernoulli beam problems is presented. RBFs, rather than generalized moving least squares (GMLS) interpolations, are used to develop the trial functions. This choice yields a computationally simpler method as fewer matrix inversions and multiplications are required than when GMLS interpolations are used. Test functions are chosen as simple weight functions as they are in the conventional MLPG method. Compactly and noncompactly supported RBFs are considered. Noncompactly supported cubic RBFs are found to be preferable. Patch tests, mixed boundary value problems, and problems with complex loading conditions are considered. Results obtained from the radial basis MLPG method are either of comparable or better accuracy than those obtained when using the conventional MLPG method.
Radical pruning: a method to construct skeleton radial basis function networks.
Augusteijn, M F; Shaw, K A
2000-04-01
Trained radial basis function networks are well-suited for use in extracting rules and explanations because they contain a set of locally tuned units. However, for rule extraction to be useful, these networks must first be pruned to eliminate unnecessary weights. The pruning algorithm cannot search the network exhaustively because of the computational effort involved. It is shown that using multiple pruning methods with smart ordering of the pruning candidates, the number of weights in a radial basis function network can be reduced to a small fraction of the original number. The complexity of the pruning algorithm is quadratic (instead of exponential) in the number of network weights. Pruning performance is shown using a variety of benchmark problems from the University of California, Irvine machine learning database.
A short-term temperature forecaster based on a novel radial basis functions neural network.
Lanza, P A; Cosme, J M
2001-02-01
Many applications dealing with electric load forecasting in buildings require temperature prediction. A new method for short-term temperature forecasting based on a Radial Basis Functions Neural Network, initialized by a Regression Tree, is presented. In this method, each terminal node of the tree contributes one hidden unit to the RBF network. The forecaster uses the current coded hour and the temperature as inputs, and predicts the next hour temperature. The results demonstrate this predictor can be used for load forecasting.
Anderson, H C; Lotfi, A; Westphal, L C; Jang, J R
1998-01-01
The above paper claims that under a set of minor restrictions radial basis function networks and fuzzy inference systems are functionally equivalent. The purpose of this letter is to show that this set of restrictions is incomplete and that, when it is completed, the said functional equivalence applies only to a small range of fuzzy inference systems. In addition, a modified set of restrictions is proposed which is applicable for a much wider range of fuzzy inference systems.
Extending the functional equivalence of radial basis function networks and fuzzy inference systems.
Hunt, K J; Haas, R; Murray-Smith, R
1996-01-01
We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference. This generalizes an existing result which applies to the standard Gaussian RBF network and a restricted form of the Takagi-Sugeno fuzzy system. The more general framework allows the removal of some of the restrictive conditions of the previous result.
NASA Technical Reports Server (NTRS)
Clancy, Daniel J.; Oezguener, Uemit; Graham, Ronald E.
1994-01-01
The potential for excessive plume impingement loads on Space Station Freedom solar arrays, caused by jet firings from an approaching Space Shuttle, is addressed. An artificial neural network is designed to determine commanded solar array beta gimbal angle for minimum plume loads. The commanded angle would be determined dynamically. The network design proposed involves radial basis functions as activation functions. Design, development, and simulation of this network design are discussed.
Functional equivalence between radial basis function networks and fuzzy inference systems.
Jang, J R; Sun, C T
1993-01-01
It is shown that, under some minor restrictions, the functional behavior of radial basis function networks (RBFNs) and that of fuzzy inference systems are actually equivalent. This functional equivalence makes it possible to apply what has been discovered (learning rule, representational power, etc.) for one of the models to the other, and vice versa. It is of interest to observe that two models stemming from different origins turn out to be functionally equivalent.
Chen, S; Wu, Y; Luk, B L
1999-01-01
The paper presents a two-level learning method for radial basis function (RBF) networks. A regularized orthogonal least squares (ROLS) algorithm is employed at the lower level to construct RBF networks while the two key learning parameters, the regularization parameter and the RBF width, are optimized using a genetic algorithm (GA) at the upper level. Nonlinear time series modeling and prediction is used as an example to demonstrate the effectiveness of this hierarchical learning approach.
NASA Technical Reports Server (NTRS)
Burken, John J.
2005-01-01
This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.
Radial basis function networks with linear interval regression weights for symbolic interval data.
Su, Shun-Feng; Chuang, Chen-Chia; Tao, C W; Jeng, Jin-Tsong; Hsiao, Chih-Ching
2012-02-01
This paper introduces a new structure of radial basis function networks (RBFNs) that can successfully model symbolic interval-valued data. In the proposed structure, to handle symbolic interval data, the Gaussian functions required in the RBFNs are modified to consider interval distance measure, and the synaptic weights of the RBFNs are replaced by linear interval regression weights. In the linear interval regression weights, the lower and upper bounds of the interval-valued data as well as the center and range of the interval-valued data are considered. In addition, in the proposed approach, two stages of learning mechanisms are proposed. In stage 1, an initial structure (i.e., the number of hidden nodes and the adjustable parameters of radial basis functions) of the proposed structure is obtained by the interval competitive agglomeration clustering algorithm. In stage 2, a gradient-descent kind of learning algorithm is applied to fine-tune the parameters of the radial basis function and the coefficients of the linear interval regression weights. Various experiments are conducted, and the average behavior of the root mean square error and the square of the correlation coefficient in the framework of a Monte Carlo experiment are considered as the performance index. The results clearly show the effectiveness of the proposed structure.
Krzyzak, A; Linder, T; Lugosi, C
1996-01-01
Studies convergence properties of radial basis function (RBF) networks for a large class of basis functions, and reviews the methods and results related to this topic. The authors obtain the network parameters through empirical risk minimization. The authors show the optimal nets to be consistent in the problem of nonlinear function approximation and in nonparametric classification. For the classification problem the authors consider two approaches: the selection of the RBF classifier via nonlinear function estimation and the direct method of minimizing the empirical error probability. The tools used in the analysis include distribution-free nonasymptotic probability inequalities and covering numbers for classes of functions.
(abstract) Ulysses Solar Wind Ion Temperatures: Radial, Latitudinal, and Dynamical Dependencies
NASA Technical Reports Server (NTRS)
Goldstein, B. E.; Smith, E. J.; Gosling, J. T.; McComas, D. J.; Balogh, A.
1996-01-01
Observations of the Ulysses SWOOPS plasma experiment are used to determine the dependencies of solar wind ion temperatures upon radial distance, speed, and other parameters, and to estimate solar wind heating. Comparisons with three dimensional temperature estimates determined from the ion spectra by a least squares fitting program will be provided (only small samples of data have been reduced with this program).
Radial Basis Functions for Combining Shape and Speckle Tracking in 4D Echocardiography
Compas, Colin B.; Wong, Emily Y.; Huang, Xiaojie; Sampath, Smita; Lin, Ben A.; Pal, Prasanta; Papademetris, Xenophon; Thiele, Karl; Dione, Donald P.; Stacy, Mitchel; Staib, Lawrence H.; Sinusas, Albert J.; O'Donnell, Matthew; Duncan, James S.
2014-01-01
Quantitative analysis of left ventricular deformation can provide valuable information about the extent of disease as well as the efficacy of treatment. In this work, we develop an adaptive multi-level compactly supported radial basis approach for deformation analysis in 3D+time echocardiography. Our method combines displacement information from shape tracking of myocardial boundaries (derived from B-mode data) with mid-wall displacements from radio-frequency-based ultrasound speckle tracking. We evaluate our methods on open-chest canines (N=8) and show that our combined approach is better correlated to magnetic resonance tagging-derived strains than either individual method. We also are able to identify regions of myocardial infarction (confirmed by postmortem analysis) using radial strain values obtained with our approach. PMID:24893257
Adaptive optical radial basis function neural network for handwritten digit recognition
NASA Astrophysics Data System (ADS)
Foor, Wesley E.; Neifeld, Mark A.
1994-06-01
An adaptive optical radial basis function classifier for handwritten digit recognition is experimentally demonstrated. We describe a spatially- multiplexed system incorporating on-line adaptation of weights and basis function widths to provide robustness to optical system imperfections and system noise. The optical system computes the Euclidean distances between a 100-dimensional input and 198 stored reference patterns in parallel using dual vector-matrix multipliers. For this experimental software is used to perform the on-line learning of the weights and basis function widths. An experimental recognition rate of 86.7% correct out of 300 testing samples is achieved with the adaptive training versus 52.3% correct for non-adaptive training. The experimental results from the optical system are compared with data from a computer model of the system in order to identify noise sources and indicate possible improvements for system performance.
Adaptive, optical, radial basis function neural network for handwritten digit recognition
NASA Astrophysics Data System (ADS)
Foor, Wesley E.; Neifeld, Mark A.
1995-11-01
An adaptive, optical, radial basis function classifier for handwritten digit recognition is experimentally demonstrated. We describe a spatially multiplexed system that incorporates an on-line adaptation of weights and basis function widths to provide robustness to optical system imperfections and system noise. The optical system computes the Euclidean distances between a 100-dimensional input vector and 198 stored reference patterns in parallel by using dual vector-matrix multipliers and a contrast-reversing spatial light modulator. Software is used to emulate an electronic chip that performs the on-line learning of the weights and basis function widths. An experimental recognition rate of 92.7% correct out of 300 testing samples is achieved with the adaptive training, versus 31.0% correct for nonadaptive training. We compare the experimental results with a detailed computer model of the system in order to analyze the influence of various noise sources on the system performance.
Automatic determination of radial basis functions: an immunity-based approach.
de Castro, L N; Von Zuben, F J
2001-12-01
The appropriate operation of a radial basis function (RBF) neural network depends mainly upon an adequate choice of the parameters of its basis functions. The simplest approach to train an RBF network is to assume fixed radial basis functions defining the activation of the hidden units. Once the RBF parameters are fixed, the optimal set of output weights can be determined straightforwardly by using a linear least squares algorithm, which generally means reduction in the learning time as compared to the determination of all RBF network parameters using supervised learning. The main drawback of this strategy is the requirement of an efficient algorithm to determine the number, position, and dispersion of the RBFs. The approach proposed here is inspired by models derived from the vertebrate immune system, that will be shown to perform unsupervised cluster analysis. The algorithm is introduced and its performance is compared to that of the random, k-means center selection procedures and other results from the literature. By automatically defining the number of RBF centers, their positions and dispersions, the proposed method leads to parsimonious solutions. Simulation results are reported concerning regression and classification problems.
NASA Astrophysics Data System (ADS)
Roohani Ghehsareh, Hadi; Kamal Etesami, Seyed; Hajisadeghi Esfahani, Maryam
2016-08-01
In the current work, the electromagnetic (EM) scattering from infinite perfectly conducting cylinders with arbitrary cross sections in both transverse magnetic (TM) and transverse electric (TE) modes is numerically investigated. The problems of TE and TM EM scattering can be mathematically modelled via the magnetic field integral equation (MFIE) and the electric field integral equation (EFIE), respectively. An efficient technique is performed to approximate the solution of these surface integral equations. In the proposed numerical method, compactly supported radial basis functions (RBFs) are employed as the basis functions. The radial and compactly supported properties of these basis functions substantially reduce the computational cost and improve the efficiency of the method. To show the accuracy of the proposed technique, it has been applied to solve three interesting test problems. Moreover, the method is well used to compute the electric current density and also the radar cross section (RCS) for some practical scatterers with different cross section geometries. The reported numerical results through the tables and figures demonstrate the efficiency and accuracy of the proposed technique.
Identification of nonlinear dynamic processes based on dynamic radial basis function networks
NASA Astrophysics Data System (ADS)
Ayoubi, Mihiar; Isermann, Rolf
1996-03-01
An attempts has been made to establish a discrete-time neuron model with a radial basis function. The neuron is utilized to build RBF-networks with locally distributed dynamics to identify input/output models of dynamic nonlinear processes. The adaptation algorithm which ascertains the optimal network parameters is provided. Further, an enhanced parameter estimation algorithm is derived, the so-called compound estimation procedure, which combines elaborated least squares techniques to highly decrease the training times. The proposed neural model is applied to identify black-box models of a turbocharging process within a Diesel engine. Benefits and drawbacks of the proposed neural structure are worked out.
Parallel fixed point implementation of a radial basis function network in an FPGA.
de Souza, Alisson C D; Fernandes, Marcelo A C
2014-01-01
This paper proposes a parallel fixed point radial basis function (RBF) artificial neural network (ANN), implemented in a field programmable gate array (FPGA) trained online with a least mean square (LMS) algorithm. The processing time and occupied area were analyzed for various fixed point formats. The problems of precision of the ANN response for nonlinear classification using the XOR gate and interpolation using the sine function were also analyzed in a hardware implementation. The entire project was developed using the System Generator platform (Xilinx), with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA.
Optimization of global model composed of radial basis functions using the term-ranking approach
Cai, Peng; Tao, Chao Liu, Xiao-Jun
2014-03-15
A term-ranking method is put forward to optimize the global model composed of radial basis functions to improve the predictability of the model. The effectiveness of the proposed method is examined by numerical simulation and experimental data. Numerical simulations indicate that this method can significantly lengthen the prediction time and decrease the Bayesian information criterion of the model. The application to real voice signal shows that the optimized global model can capture more predictable component in chaos-like voice data and simultaneously reduce the predictable component (periodic pitch) in the residual signal.
On the capabilities of higher-order neurons: a radial basis function approach.
Schmitt, Michael
2005-03-01
Higher-order neurons with k monomials in n variables are shown to have Vapnik-Chervonenkis (VC) dimension at least nk + 1. This result supersedes the previously known lower bound obtained via k-term monotone disjunctive normal form (DNF) formulas. Moreover, it implies that the VC dimension of higher-order neurons with k monomials is strictly larger than the VC dimension of k-term monotone DNF. The result is achieved by introducing an exponential approach that employs gaussian radial basis function neural networks for obtaining classifications of points in terms of higher-order neurons.
Ni, Shengqiao; Lv, Jiancheng; Cheng, Zhehao; Li, Mao
2015-01-01
This paper presents improvements to the conventional Topology Representing Network to build more appropriate topology relationships. Based on this improved Topology Representing Network, we propose a novel method for online dimensionality reduction that integrates the improved Topology Representing Network and Radial Basis Function Network. This method can find meaningful low-dimensional feature structures embedded in high-dimensional original data space, process nonlinear embedded manifolds, and map the new data online. Furthermore, this method can deal with large datasets for the benefit of improved Topology Representing Network. Experiments illustrate the effectiveness of the proposed method.
Image interpolation for progressive transmission by using radial basis function networks.
Sigitani, T; Iiguni, Y; Maeda, H
1999-01-01
This paper investigates the application of a radial basis function network (RBFN) to a hierarchical image coding for progressive transmission. The RBFN is then used to generate an interpolated image from the subsampled version. An efficient method of computing the network parameters is developed for reduction in computational and memory requirements. The coding method does not suffer from problems of blocking effect and can produce the coarsest image quickly. Quantization error effects introduced at one stage are considered in decoding images at the following stages, thus allowing lossless progressive transmission.
Mayorga, René V; Carrera, Jonathan
2007-06-01
This Paper presents an efficient approach for the fast computation of inverse continuous time variant functions with the proper use of Radial Basis Function Networks (RBFNs). The approach is based on implementing RBFNs for computing inverse continuous time variant functions via an overall damped least squares solution that includes a novel null space vector for singularities prevention. The singularities avoidance null space vector is derived from developing a sufficiency condition for singularities prevention that conduces to establish some characterizing matrices and an associated performance index.
Ni, Shengqiao; Lv, Jiancheng; Cheng, Zhehao; Li, Mao
2015-01-01
This paper presents improvements to the conventional Topology Representing Network to build more appropriate topology relationships. Based on this improved Topology Representing Network, we propose a novel method for online dimensionality reduction that integrates the improved Topology Representing Network and Radial Basis Function Network. This method can find meaningful low-dimensional feature structures embedded in high-dimensional original data space, process nonlinear embedded manifolds, and map the new data online. Furthermore, this method can deal with large datasets for the benefit of improved Topology Representing Network. Experiments illustrate the effectiveness of the proposed method. PMID:26161960
On-line Supervised Adaptive Training Using Radial Basis Function Networks.
Luo, Wan; Billings, Steve A.; Fung, Chi F.
1996-12-01
A new recursive supervised training algorithm is derived for the radial basis neural network architecture. The new algorithm combines the procedures of on-line candidate regressor selection with the conventional Givens QR based recursive parameter estimator to provide efficient adaptive supervised network training. A new concise on-line correlation based performance monitoring scheme is also introduced as an auxiliary device to detect structural changes in temporal data processing applications. Practical and simulated examples are included to demonstrate the effectiveness of the new procedures. Copyright 1996 Elsevier Science Ltd.
Parallel Fixed Point Implementation of a Radial Basis Function Network in an FPGA
de Souza, Alisson C. D.; Fernandes, Marcelo A. C.
2014-01-01
This paper proposes a parallel fixed point radial basis function (RBF) artificial neural network (ANN), implemented in a field programmable gate array (FPGA) trained online with a least mean square (LMS) algorithm. The processing time and occupied area were analyzed for various fixed point formats. The problems of precision of the ANN response for nonlinear classification using the XOR gate and interpolation using the sine function were also analyzed in a hardware implementation. The entire project was developed using the System Generator platform (Xilinx), with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA. PMID:25268918
Fault diagnosis of electrical power systems using incremental radial basis function nets
Nagabhushana, T.N.; Chandrasekharaiah, H.S.
1995-12-31
Most of the proposed Neural Networks for fault diagnosis of power systems are Multilayer Perceptrons [MLP] employing the popular Back Propagation [BP] learning rule. It has been shown that Back Propagation algorithm usually takes a long time for convergence and sometimes get trapped into local minimum. The algorithm requires the architecture to be fixed initially (i.e., the number of hidden units) before learning begins. Final network size is obtained by repeated trials. When the size of the training set is large, especially in the case of fault diagnosis, such a repeated training consumes a large amount of time and sometimes it can be frustrating. Thus there is a need of a good Neural Network architecture that decides its size automatically while learning the input/output relationships and must possess reasonably good generalization. Recently Neural Networks based on Radial Basis Functions [RBF] have emerged as potential alternatives to MLPs. RBFs have a simple architecture and they can learn the input/output relations fast compared to MLPs. In this paper the authors present a constructive neural network based on Radial Basis Functions [RBF] due to Fritzke for classification of fault patterns in a model power system. The Performance of this neural network with traditional BP network and nonconstructive RBF network in terms of size, learning speed and generalization are presented.
Computing single step operators of logic programming in radial basis function neural networks
NASA Astrophysics Data System (ADS)
Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong
2014-07-01
Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (Tp:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.
A self-organizing radial basis network for estimating riverine fish diversity
NASA Astrophysics Data System (ADS)
Chang, Fi-John; Tsai, Wen-Ping; Chen, Hung-kwai; Yam, Rita Sau-Wai; Herricks, Edwin E.
2013-01-01
SummaryIn aquatic ecosystems, particularly rivers, hydrology plays a key role in structuring and maintaining habitats and flow regimes that influence ecological sustainability. Flow regime assessment in Taiwan has been facilitated recently by the Taiwan Eco-hydrologic Indicator System (TEIS). In this study, the self-organizing feature map (SOM) and radial basis function (RBF) neural network are combined to produce a self-organizing radial basis network (SORBN) that takes the advantages of both methods for strengthening the power of presentation and reliability of estimation. The SORBN is proposed to estimate the diversity of fish communities based on the TEIS and historic fish community composition at 36 locations in Taiwan. The discharge data are available for a minimum of 20 years. Data analysis applying a moving average method to the TEIS statistics is used to reflect the effects of antecedent flow conditions on fish diversity. Results indicate the hybrid SORBN not only effectively categorizes stream flow data but also reasonably identifies relationships between flow regime and fish community diversity. Results are encouraging so that it is possible to better relate flow and ecosystem conditions, and the proposed method can be used to quantify how flow influences river ecosystems.
Estimation of river pollution source using the space-time radial basis collocation method
NASA Astrophysics Data System (ADS)
Li, Zi; Mao, Xian-Zhong; Li, Tak Sing; Zhang, Shiyan
2016-02-01
River contaminant source identification problems can be formulated as an inverse model to estimate the missing source release history from the observed contaminant plume. In this study, the identification of pollution sources in rivers, where strong advection is dominant, is solved by the global space-time radial basis collocation method (RBCM). To search for the optimal shape parameter and scaling factor which strongly determine the accuracy of the RBCM method, a new cost function based on the residual errors of not only the observed data but also the specified governing equation, the initial and boundary conditions, was constructed for the k-fold cross-validation technique. The performance of three global radial basis functions, Hardy's multiquadric, inverse multiquadric and Gaussian, were also compared in the test cases. The numerical results illustrate that the new cost function is a good indicator to search for near-optimal solutions. Application to a real polluted river shows that the source release history is reasonably recovered, demonstrating that the RBCM with the k-fold cross-validation is a powerful tool for source identification problems in advection-dominated rivers.
Computing single step operators of logic programming in radial basis function neural networks
Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong
2014-07-10
Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.
Combustion monitoring of a water tube boiler using a discriminant radial basis network.
Sujatha, K; Pappa, N
2011-01-01
This research work includes a combination of Fisher's linear discriminant (FLD) analysis and a radial basis network (RBN) for monitoring the combustion conditions for a coal fired boiler so as to allow control of the air/fuel ratio. For this, two-dimensional flame images are required, which were captured with a CCD camera; the features of the images-average intensity, area, brightness and orientation etc of the flame-are extracted after preprocessing the images. The FLD is applied to reduce the n-dimensional feature size to a two-dimensional feature size for faster learning of the RBN. Also, three classes of images corresponding to different burning conditions of the flames have been extracted from continuous video processing. In this, the corresponding temperatures, and the carbon monoxide (CO) emissions and those of other flue gases have been obtained through measurement. Further, the training and testing of Fisher's linear discriminant radial basis network (FLDRBN), with the data collected, have been carried out and the performance of the algorithms is presented.
A New Approach to Radial Basis Function Approximation and Its Application to QSAR
2015-01-01
We describe a novel approach to RBF approximation, which combines two new elements: (1) linear radial basis functions and (2) weighting the model by each descriptor’s contribution. Linear radial basis functions allow one to achieve more accurate predictions for diverse data sets. Taking into account the contribution of each descriptor produces more accurate similarity values used for model development. The method was validated on 14 public data sets comprising nine physicochemical properties and five toxicity endpoints. We also compared the new method with five different QSAR methods implemented in the EPA T.E.S.T. program. Our approach, implemented in the program GUSAR, showed a reasonable accuracy of prediction and high coverage for all external test sets, providing more accurate prediction results than the comparison methods and even the consensus of these methods. Using our new method, we have created models for physicochemical and toxicity endpoints, which we have made freely available in the form of an online service at http://cactus.nci.nih.gov/chemical/apps/cap. PMID:24451033
Dual-orthogonal radial basis function networks for nonlinear time series prediction.
Hong, X; Billings, Steve A.
1998-04-01
A new structure of Radial Basis Function (RBF) neural network called the Dual-orthogonal RBF Network (DRBF) is introduced for nonlinear time series prediction. The hidden nodes of a conventional RBF network compare the Euclidean distance between the network input vector and the centres, and the node responses are radially symmetrical. But in time series prediction where the system input vectors are lagged system outputs, which are usually highly correlated, the Euclidean distance measure may not be appropriate. The DRBF network modifies the distance metric by introducing a classification function which is based on the estimation data set. Training the DRBF networks consists of two stages. Learning the classification related basis functions and the important input nodes, followed by selecting the regressors and learning the weights of the hidden nodes. In both cases, a forward Orthogonal Least Squares (OLS) selection procedure is applied, initially to select the important input nodes and then to select the important centres. Simulation results of single-step and multi-step ahead predictions over a test data set are included to demonstrate the effectiveness of the new approach.
Analysis of cornea curvature using radial basis functions - Part I: Methodology.
Griffiths, G W; Płociniczak, Ł; Schiesser, W E
2016-10-01
We discuss the solution of cornea curvature using a meshless method based on radial basis functions (RBFs). A full two-dimensional nonlinear thin membrane partial differential equation (PDE) model is introduced and solved using the multiquadratic (MQ) and inverse multiquadratic (IMQ) RBFs. This new approach does not rely on radial symmetry or other simplifying assumptions in respect of the cornea shape. It also provides an alternative to corneal topography modeling methods requiring accurate material parameter values, such as Young's modulus and Poisson ratio, that may not be available. The results show good agreement with published corneal data and allow back calculations for estimating certain physical properties of the cornea, such as tension and elasticity coefficient. All calculations and generation of graphics were performed using the R language programming environment [34] and RStudio, the integrated development environment (IDE) for R [36], both of which are open source and free to download. Part II [48] of this paper demonstrates how the method has been used to provide a very accurate fit to a corneal measured data set. PMID:27614697
Radial Basis Function Neural Network Application to Power System Restoration Studies
Sadeghkhani, Iman; Ketabi, Abbas; Feuillet, Rene
2012-01-01
One of the most important issues in power system restoration is overvoltages caused by transformer switching. These overvoltages might damage some equipment and delay power system restoration. This paper presents a radial basis function neural network (RBFNN) to study transformer switching overvoltages. To achieve good generalization capability for developed RBFNN, equivalent parameters of the network are added to RBFNN inputs. The developed RBFNN is trained with the worst-case scenario of switching angle and remanent flux and tested for typical cases. The simulated results for a partial of 39-bus New England test system show that the proposed technique can estimate the peak values and duration of switching overvoltages with good accuracy. PMID:22792093
An Incremental Radial Basis Function Network Based on Information Granules and Its Application
Lee, Myung-Won
2016-01-01
This paper is concerned with the design of an Incremental Radial Basis Function Network (IRBFN) by combining Linear Regression (LR) and local RBFN for the prediction of heating load and cooling load in residential buildings. Here the proposed IRBFN is designed by building a collection of information granules through Context-based Fuzzy C-Means (CFCM) clustering algorithm that is guided by the distribution of error of the linear part of the LR model. After adopting a construct of a LR as global model, refine it through local RBFN that captures remaining and more localized nonlinearities of the system to be considered. The experiments are performed on the estimation of energy performance of 768 diverse residential buildings. The experimental results revealed that the proposed IRBFN showed good performance in comparison to LR, the standard RBFN, RBFN with information granules, and Linguistic Model (LM).
Analysis of cornea curvature using radial basis functions - Part II: Fitting to data-set.
Griffiths, G W; Płociniczak, Ł; Schiesser, W E
2016-10-01
In part I we discussed the solution of corneal curvature using a 2D meshless method based on radial basis functions (RBFs). In Part II we use these methods to fit a full nonlinear thin membrane model to a measured data-set in order to generate a topological mathematical description of the cornea. In addition, we show how these results can lead to estimations for corneal radius of curvature and certain physical properties of the cornea; namely, tension and elasticity coefficient. Again all calculations and graphics generation were performed using the R language programming environment. The model describes corneal topology extremely well, and the estimated properties fall well within the expected range of values. The method is straight forward to implement and offers scope for further analysis using more detailed 3D models that include corneal thickness. PMID:27570056
Vibration measurement based on electronic speckle pattern interferometry and radial basis function
NASA Astrophysics Data System (ADS)
Dai, Xiangjun; Shao, Xinxing; Geng, Zhencen; Yang, Fujun; Jiang, Yijun; He, Xiaoyuan
2015-11-01
A method incorporating amplitude-fluctuation electronic speckle pattern interferometry (AF-ESPI) with radial basis function (RBF) was proposed to investigate vibration characteristics of structures. The vibration patterns were obtained by AF-ESPI. A novel pre-filtering RBF method was presented to improve the quality of patterns. The out-of-plane vibration amplitude was rebuilt after fringe analysis. Ideal pre-filtering widow sizes for the presented RBF were given based on numerical experiments. For validation, an aluminum circular plate with fixed boundary was determined and compared with FEM, confirming the effectiveness of the proposed method. Finally, vibration characteristics of sandwich panels with honeycomb core were measured. The influence of presence of a pre-notch at different location was also investigated.
An Incremental Radial Basis Function Network Based on Information Granules and Its Application
Lee, Myung-Won
2016-01-01
This paper is concerned with the design of an Incremental Radial Basis Function Network (IRBFN) by combining Linear Regression (LR) and local RBFN for the prediction of heating load and cooling load in residential buildings. Here the proposed IRBFN is designed by building a collection of information granules through Context-based Fuzzy C-Means (CFCM) clustering algorithm that is guided by the distribution of error of the linear part of the LR model. After adopting a construct of a LR as global model, refine it through local RBFN that captures remaining and more localized nonlinearities of the system to be considered. The experiments are performed on the estimation of energy performance of 768 diverse residential buildings. The experimental results revealed that the proposed IRBFN showed good performance in comparison to LR, the standard RBFN, RBFN with information granules, and Linguistic Model (LM). PMID:27698658
Higher-order-statistics-based radial basis function networks for signal enhancement.
Lin, Bor-Shyh; Lin, Bor-Shing; Chong, Fok-Ching; Lai, Feipei
2007-05-01
In this paper, a higher-order-statistics (HOS)-based radial basis function (RBF) network for signal enhancement is introduced. In the proposed scheme, higher order cumulants of the reference signal were used as the input of HOS-based RBF. An HOS-based supervised learning algorithm, with mean square error obtained from higher order cumulants of the desired input and the system output as the learning criterion, was used to adapt weights. The motivation is that the HOS can effectively suppress Gaussian and symmetrically distributed non-Gaussian noise. The influence of a Gaussian noise on the input of HOS-based RBF and the HOS-based learning algorithm can be mitigated. Simulated results indicate that HOS-based RBF can provide better performance for signal enhancement under different noise levels, and its performance is insensitive to the selection of learning rates. Moreover, the efficiency of HOS-based RBF under the nonstationary Gaussian noise is stable.
Radial basis function network learns ceramic processing and predicts related strength and density
NASA Technical Reports Server (NTRS)
Cios, Krzysztof J.; Baaklini, George Y.; Vary, Alex; Tjia, Robert E.
1993-01-01
Radial basis function (RBF) neural networks were trained using the data from 273 Si3N4 modulus of rupture (MOR) bars which were tested at room temperature and 135 MOR bars which were tested at 1370 C. Milling time, sintering time, and sintering gas pressure were the processing parameters used as the input features. Flexural strength and density were the outputs by which the RBF networks were assessed. The 'nodes-at-data-points' method was used to set the hidden layer centers and output layer training used the gradient descent method. The RBF network predicted strength with an average error of less than 12 percent and density with an average error of less than 2 percent. Further, the RBF network demonstrated a potential for optimizing and accelerating the development and processing of ceramic materials.
Construction of tunable radial basis function networks using orthogonal forward selection.
Chen, Sheng; Hong, Xia; Luk, Bing L; Harris, Chris J
2009-04-01
An orthogonal forward selection (OFS) algorithm based on leave-one-out (LOO) criteria is proposed for the construction of radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines an RBF node, namely, its center vector and diagonal covariance matrix, by minimizing the LOO statistics. For regression application, the LOO criterion is chosen to be the LOO mean-square error, while the LOO misclassification rate is adopted in two-class classification application. This OFS-LOO algorithm is computationally efficient, and it is capable of constructing parsimonious RBF networks that generalize well. Moreover, the proposed algorithm is fully automatic, and the user does not need to specify a termination criterion for the construction process. The effectiveness of the proposed RBF network construction procedure is demonstrated using examples taken from both regression and classification applications.
Gradient radial basis function networks for nonlinear and nonstationary time series prediction.
Chng, E S; Chen, S; Mulgrew, B
1996-01-01
We present a method of modifying the structure of radial basis function (RBF) network to work with nonstationary series that exhibit homogeneous nonstationary behavior. In the original RBF network, the hidden node's function is to sense the trajectory of the time series and to respond when there is a strong correlation between the input pattern and the hidden node's center. This type of response, however, is highly sensitive to changes in the level and trend of the time series. To counter these effects, the hidden node's function is modified to one which detects and reacts to the gradient of the series. We call this new network the gradient RBF (GRBF) model. Single and multistep predictive performance for the Mackey-Glass chaotic time series were evaluated using the classical RBF and GRBF models. The simulation results for the series without and with a tine-varying mean confirm the superior performance of the GRBF predictor over the RBF predictor.
Ma, Shu-min; Liu, Si-dong; Zhang, Zhuo-yong; Fan, Guo-qiang
2005-06-01
The Fourier transform infrared spectrometry (FTIRS) and radial basis function neural network (RBF-NN) have been applied to develop classification models for identifying official and unofficial rhubarb samples. The original data were compressed from 775 variables to 49 variables by using wavelet transformation method. The compressed spectra with reduced variables maintain the characteristics of the IR spectra and speed up the network training process. The effects of network parameters including error goal and spread constant, were investigated. The rate of correct classification is up to 97.78% at optimized conditions. Results show that the combination of IRS and ANN can be used as fast and convenient tool for identification of Chinese herbal samples.
Research on an online self-organizing radial basis function neural network
Han, Honggui; Chen, Qili
2010-01-01
A new growing and pruning algorithm is proposed for radial basis function (RBF) neural network structure design in this paper, which is named as self-organizing RBF (SORBF). The structure of the RBF neural network is introduced in this paper first, and then the growing and pruning algorithm is used to design the structure of the RBF neural network automatically. The growing and pruning approach is based on the radius of the receptive field of the RBF nodes. Meanwhile, the parameters adjusting algorithms are proposed for the whole RBF neural network. The performance of the proposed method is evaluated through functions approximation and dynamic system identification. Then, the method is used to capture the biochemical oxygen demand (BOD) concentration in a wastewater treatment system. Experimental results show that the proposed method is efficient for network structure optimization, and it achieves better performance than some of the existing algorithms. PMID:20651904
The neural basis of a deficit in abstract thinking in patients with schizophrenia.
Oh, Jooyoung; Chun, Ji-Won; Joon Jo, Hang; Kim, Eunseong; Park, Hae-Jeong; Lee, Boreom; Kim, Jae-Jin
2015-10-30
Abnormal abstract thinking is a major cause of social dysfunction in patients with schizophrenia, but little is known about its neural basis. In this study, we aimed to determine the characteristic abstract thinking-related brain responses in patients using a task reflecting social situations. We conducted functional magnetic resonance imaging while 16 patients with schizophrenia and 16 healthy controls performed a theme-identification task, in which various emotional pictures depicting social situations were presented. Compared with healthy controls, the patients showed significantly decreased activity in the left frontopolar and right orbitofrontal cortices during theme identification. Activity in these two regions correlated well in the controls, but not in patients. Instead, the patients exhibited a close correlation between activity in both sides of the frontopolar cortex, and a positive correlation between the right orbitofrontal cortex activity and degrees of theme identification. Reduced activity in the left frontopolar and right orbitofrontal cortices and the underlying aberrant connectivity may be implicated in the patients' deficits in abstract thinking. These newly identified features of the neural basis of abnormal abstract thinking are important as they have implications for the impaired social behavior of patients with schizophrenia during real-life situations.
Babu, G S; Suresh, S
2013-02-01
In this paper, we present a sequential projection-based metacognitive learning algorithm in a radial basis function network (PBL-McRBFN) for classification problems. The algorithm is inspired by human metacognitive learning principles and has two components: a cognitive component and a metacognitive component. The cognitive component is a single-hidden-layer radial basis function network with evolving architecture. The metacognitive component controls the learning process in the cognitive component by choosing the best learning strategy for the current sample and adapts the learning strategies by implementing self-regulation. In addition, sample overlapping conditions and past knowledge of the samples in the form of pseudosamples are used for proper initialization of new hidden neurons to minimize the misclassification. The parameter update strategy uses projection-based direct minimization of hinge loss error. The interaction of the cognitive component and the metacognitive component addresses the what-to-learn, when-to-learn, and how-to-learn human learning principles efficiently. The performance of the PBL-McRBFN is evaluated using a set of benchmark classification problems from the University of California Irvine machine learning repository. The statistical performance evaluation on these problems proves the superior performance of the PBL-McRBFN classifier over results reported in the literature. Also, we evaluate the performance of the proposed algorithm on a practical Alzheimer's disease detection problem. The performance results on open access series of imaging studies and Alzheimer's disease neuroimaging initiative datasets, which are obtained from different demographic regions, clearly show that PBL-McRBFN can handle a problem with change in distribution.
Hancock, M.F. Jr.
1995-12-31
The National Council on Compensation Insurance (NCCI) maintains a national data base of outcomes of workers` compensation claims. We consider whether a radial basis function network can predict the total dollar value of a claim based upon medical and demographic indicators (MDI`s). This work used data from 12,130 workers` compensation claims collected over a period of four years from the state of New Mexico. Two problems were addressed: (1) How well can the total incurred medical expense for all claims be predicted from available MDI`s? For individual claims? (2) How well can the duration of disability be predicted from available MDI`s? The available features intuitively correlated with total medical cost were selected, including type of injury, part of body injured, person`s age at time of injury, gender, marital status, etc. These features were statistically standardized and sorted by correlation with outcome valuation. Principal component analysis was applied. A radial basis function neural network was applied to the feature sets in both supervised and unsupervised training modes. For sets used in training, individual case valuations could consistently be predicted to within $1000 over 98% of the time. For these sets, it was possible to predict total medical expense for the training sets themselves to within 10%. When applied as blind tests against sets which were NOT part of the training data, the prediction was within 15% on the whole sets. Results on individual cases were very poor in only 30% of the cases were the predictions for the training sets within $1000 of their actual valuations. Single-factor analysis suggested that the presence of an attorney strongly decorrelated the data. A simple stratification was performed to remove cases involving attorneys and contested claims, and the procedures above repeated. Preliminary results based upon the very limited effort applied indicate that NCCI data support population estimates, but not single-point estimates.
Numerical solution of differential equations using multiquadric radial basis functions networks.
Mai-Duy, N; Tran-Cong, T
2001-03-01
This paper presents mesh-free procedures for solving linear differential equations (ODEs and elliptic PDEs) based on multiquadric (MQ) radial basis function networks (RBFNs). Based on our study of approximation of function and its derivatives using RBFNs that was reported in an earlier paper (Mai-Duy, N. & Tran-Cong, T. (1999). Approximation of function and its derivatives using radial basis function networks. Neural networks, submitted), new RBFN approximation procedures are developed in this paper for solving DEs, which can also be classified into two types: a direct (DRBFN) and an indirect (IRBFN) RBFN procedure. In the present procedures, the width of the RBFs is the only adjustable parameter according to a(i) = betad(i), where d(i) is the distance from the ith centre to the nearest centre. The IRBFN method is more accurate than the DRBFN one and experience so far shows that beta can be chosen in the range 7 < or = beta 10 for the former. Different combinations of RBF centres and collocation points (uniformly and randomly distributed) are tested on both regularly and irregularly shaped domains. The results for a 1D Poisson's equation show that the DRBFN and the IRBFN procedures achieve a norm of error of at least O(1.0 x 10(-4)) and O(1.0 x 10(-8)), respectively, with a centre density of 50. Similarly, the results for a 2D Poisson's equation show that the DRBFN and the IRBFN procedures achieve a norm of error of at least O(1.0 x 10(-3)) and O(1.0 x10(-6)) respectively, with a centre density of 12 X 12.
Approximating Gaussian mixture model or radial basis function network with multilayer perceptron.
Patrikar, Ajay M
2013-07-01
Gaussian mixture models (GMMs) and multilayer perceptron (MLP) are both popular pattern classification techniques. This brief shows that a multilayer perceptron with quadratic inputs (MLPQ) can accurately approximate GMMs with diagonal covariance matrices. The mapping equations between the parameters of GMM and the weights of MLPQ are presented. A similar approach is applied to radial basis function networks (RBFNs) to show that RBFNs with Gaussian basis functions and Euclidean norm can be approximated accurately with MLPQ. The mapping equations between RBFN and MLPQ weights are presented. There are well-established training procedures for GMMs, such as the expectation maximization (EM) algorithm. The GMM parameters obtained by the EM algorithm can be used to generate a set of initial weights of MLPQ. Similarly, a trained RBFN can be used to generate a set of initial weights of MLPQ. MLPQ training can be continued further with gradient-descent based methods, which can lead to improvement in performance compared to the GMM or RBFN from which it is initialized. Thus, the MLPQ can always perform as well as or better than the GMM or RBFN.
Selver, M Alper; Güzeliş, Cüneyt
2009-01-01
As being a tool that assigns optical parameters used in interactive visualization, Transfer Functions (TF) have important effects on the quality of volume rendered medical images. Unfortunately, finding accurate TFs is a tedious and time consuming task because of the trade off between using extensive search spaces and fulfilling the physician's expectations with interactive data exploration tools and interfaces. By addressing this problem, we introduce a semi-automatic method for initial generation of TFs. The proposed method uses a Self Generating Hierarchical Radial Basis Function Network to determine the lobes of a Volume Histogram Stack (VHS) which is introduced as a new domain by aligning the histograms of slices of a image series. The new self generating hierarchical design strategy allows the recognition of suppressed lobes corresponding to suppressed tissues and representation of the overlapping regions which are parts of the lobes but can not be represented by the Gaussian bases in VHS. Moreover, approximation with a minimum set of basis functions provides the possibility of selecting and adjusting suitable units to optimize the TF. Applications on different CT and MR data sets show enhanced rendering quality and reduced optimization time in abdominal studies.
GRACE L1b inversion through a self-consistent modified radial basis function approach
NASA Astrophysics Data System (ADS)
Yang, Fan; Kusche, Juergen; Rietbroek, Roelof; Eicker, Annette
2016-04-01
Implementing a regional geopotential representation such as mascons or, more general, RBFs (radial basis functions) has been widely accepted as an efficient and flexible approach to recover the gravity field from GRACE (Gravity Recovery and Climate Experiment), especially at higher latitude region like Greenland. This is since RBFs allow for regionally specific regularizations over areas which have sufficient and dense GRACE observations. Although existing RBF solutions show a better resolution than classical spherical harmonic solutions, the applied regularizations cause spatial leakage which should be carefully dealt with. It has been shown that leakage is a main error source which leads to an evident underestimation of yearly trend of ice-melting over Greenland. Unlike some popular post-processing techniques to mitigate leakage signals, this study, for the first time, attempts to reduce the leakage directly in the GRACE L1b inversion by constructing an innovative modified (MRBF) basis in place of the standard RBFs to retrieve a more realistic temporal gravity signal along the coastline. Our point of departure is that the surface mass loading associated with standard RBF is smooth but disregards physical consistency between continental mass and passive ocean response. In this contribution, based on earlier work by Clarke et al.(2007), a physically self-consistent MRBF representation is constructed from standard RBFs, with the help of the sea level equation: for a given standard RBF basis, the corresponding MRBF basis is first obtained by keeping the surface load over the continent unchanged, but imposing global mass conservation and equilibrium response of the oceans. Then, the updated set of MRBFs as well as standard RBFs are individually employed as the basis function to determine the temporal gravity field from GRACE L1b data. In this way, in the MRBF GRACE solution, the passive (e.g. ice melting and land hydrology response) sea level is automatically
A radial basis classifier for the automatic detection of aspiration in children with dysphagia
Lee, Joon; Blain, Stefanie; Casas, Mike; Kenny, Dave; Berall, Glenn; Chau, Tom
2006-01-01
Background Silent aspiration or the inhalation of foodstuffs without overt physiological signs presents a serious health issue for children with dysphagia. To date, there are no reliable means of detecting aspiration in the home or community. An assistive technology that performs in these environments could inform caregivers of adverse events and potentially reduce the morbidity and anxiety of the feeding experience for the child and caregiver, respectively. This paper proposes a classifier for automatic classification of aspiration and swallow vibration signals non-invasively recorded on the neck of children with dysphagia. Methods Vibration signals associated with safe swallows and aspirations, both identified via videofluoroscopy, were collected from over 100 children with neurologically-based dysphagia using a single-axis accelerometer. Five potentially discriminatory mathematical features were extracted from the accelerometry signals. All possible combinations of the five features were investigated in the design of radial basis function classifiers. Performance of different classifiers was compared and the best feature sets were identified. Results Optimal feature combinations for two, three and four features resulted in statistically comparable adjusted accuracies with a radial basis classifier. In particular, the feature pairing of dispersion ratio and normality achieved an adjusted accuracy of 79.8 ± 7.3%, a sensitivity of 79.4 ± 11.7% and specificity of 80.3 ± 12.8% for aspiration detection. Addition of a third feature, namely energy, increased adjusted accuracy to 81.3 ± 8.5% but the change was not statistically significant. A closer look at normality and dispersion ratio features suggest leptokurticity and the frequency and magnitude of atypical values as distinguishing characteristics between swallows and aspirations. The achieved accuracies are 30% higher than those reported for bedside cervical auscultation. Conclusion The proposed aspiration
Estimating diffusion propagator and its moments using directional radial basis functions
Ning, Lipeng; Westin, Carl-Fredrik; Rathi, Yogesh
2015-01-01
The ensemble average diffusion propagator (EAP) obtained from diffusion MRI (dMRI) data captures important structural properties of the underlying tissue. As such, it is imperative to derive an accurate estimate of the EAP from the acquired diffusion data. In this work, we propose a novel method for estimating the EAP by representing the diffusion signal as a linear combination of directional radial basis functions scattered in q-space. In particular, we focus on a special case of anisotropic Gaussian basis functions and derive analytical expressions for the diffusion orientation distribution function (ODF), the return-to-origin probability (RTOP), and mean-squared-displacement (MSD). A significant advantage of the proposed method is that the second and the fourth order moment tensors of the EAP can be computed explicitly. This allows for computing several novel scalar indices (from the moment tensors) such as mean-fourth-order-displacement (MFD) and generalized kurtosis (GK) – which is a generalization of the mean kurtosis measure used in diffusion kurtosis imaging. Additionally, we also propose novel scalar indices computed from the signal in q-space, called the q-space mean-squared-displacement (QMSD) and the q-space mean-fourth-order-displacement (QMFD), which are sensitive to short diffusion time scales. We validate our method extensively on data obtained from a physical phantom with known crossing angle as well as on in-vivo human brain data. Our experiments demonstrate the robustness of our method for different combinations of b-values and number of gradient directions. PMID:25838518
Logistic regression by means of evolutionary radial basis function neural networks.
Gutierrez, Pedro Antonio; Hervas-Martinez, César; Martinez-Estudillo, Francisco J
2011-02-01
This paper proposes a hybrid multilogistic methodology, named logistic regression using initial and radial basis function (RBF) covariates. The process for obtaining the coefficients is carried out in three steps. First, an evolutionary programming (EP) algorithm is applied, in order to produce an RBF neural network (RBFNN) with a reduced number of RBF transformations and the simplest structure possible. Then, the initial attribute space (or, as commonly known as in logistic regression literature, the covariate space) is transformed by adding the nonlinear transformations of the input variables given by the RBFs of the best individual in the final generation. Finally, a maximum likelihood optimization method determines the coefficients associated with a multilogistic regression model built in this augmented covariate space. In this final step, two different multilogistic regression algorithms are applied: one considers all initial and RBF covariates (multilogistic initial-RBF regression) and the other one incrementally constructs the model and applies cross validation, resulting in an automatic covariate selection [simplelogistic initial-RBF regression (SLIRBF)]. Both methods include a regularization parameter, which has been also optimized. The methodology proposed is tested using 18 benchmark classification problems from well-known machine learning problems and two real agronomical problems. The results are compared with the corresponding multilogistic regression methods applied to the initial covariate space, to the RBFNNs obtained by the EP algorithm, and to other probabilistic classifiers, including different RBFNN design methods [e.g., relaxed variable kernel density estimation, support vector machines, a sparse classifier (sparse multinomial logistic regression)] and a procedure similar to SLIRBF but using product unit basis functions. The SLIRBF models are found to be competitive when compared with the corresponding multilogistic regression methods and the
NASA Astrophysics Data System (ADS)
Stevens, D.; Power, H.
2015-10-01
We propose a node-based local meshless method for advective transport problems that is capable of operating on centrally defined stencils and is suitable for shock-capturing purposes. High spatial convergence rates can be achieved; in excess of eighth-order in some cases. Strongly-varying smooth profiles may be captured at infinite Péclet number without instability, and for discontinuous profiles the solution exhibits neutrally stable oscillations that can be damped by introducing a small artificial diffusion parameter, allowing a good approximation to the shock-front to be maintained for long travel times without introducing spurious oscillations. The proposed method is based on local collocation with radial basis functions (RBFs) in a "finite collocation" configuration. In this approach the PDE governing and boundary equations are enforced directly within the local RBF collocation systems, rather than being reconstructed from fixed interpolating functions as is typical of finite difference, finite volume or finite element methods. In this way the interpolating basis functions naturally incorporate information from the governing PDE, including the strength and direction of the convective velocity field. By using these PDE-enhanced interpolating functions an "implicit upwinding" effect is achieved, whereby the flow of information naturally respects the specifics of the local convective field. This implicit upwinding effect allows high-convergence solutions to be obtained on centred stencils for advection problems. The method is formulated using a high-convergence implicit timestepping algorithm based on Richardson extrapolation. The spatial and temporal convergence of the proposed approach is demonstrated using smooth functions with large gradients. The capture of discontinuities is then investigated, showing how the addition of a dynamic stabilisation parameter can damp the neutrally stable oscillations with limited smearing of the shock front.
[Automated recognition of quasars based on adaptive radial basis function neural networks].
Zhao, Mei-Fang; Luo, A-Li; Wu, Fu-Chao; Hu, Zhan-Yi
2006-02-01
Recognizing and certifying quasars through the research on spectra is an important method in the field of astronomy. This paper presents a novel adaptive method for the automated recognition of quasars based on the radial basis function neural networks (RBFN). The proposed method is composed of the following three parts: (1) The feature space is reduced by the PCA (the principal component analysis) on the normalized input spectra; (2) An adaptive RBFN is constructed and trained in this reduced space. At first, the K-means clustering is used for the initialization, then based on the sum of squares errors and a gradient descent optimization technique, the number of neurons in the hidden layer is adaptively increased to improve the recognition performance; (3) The quasar spectra recognition is effectively carried out by the above trained RBFN. The author's proposed adaptive RBFN is shown to be able to not only overcome the difficulty of selecting the number of neurons in hidden layer of the traditional RBFN algorithm, but also increase the stability and accuracy of recognition of quasars. Besides, the proposed method is particularly useful for automatic voluminous spectra processing produced from a large-scale sky survey project, such as our LAMOST, due to its efficiency.
Fire Risk Assessment of Some Indian Coals Using Radial Basis Function (RBF) Technique
NASA Astrophysics Data System (ADS)
Nimaje, Devidas; Tripathy, Debi Prasad
2016-03-01
Fires, whether surface or underground, pose serious and environmental problems in the global coal mining industry. It is causing huge loss of coal due to burning and loss of lives, sterilization of coal reserves and environmental pollution. Most of the instances of coal mine fires happening worldwide are mainly due to the spontaneous combustion. Hence, attention must be paid to take appropriate measures to prevent occurrence and spread of fire. In this paper, to evaluate the different properties of coals for fire risk assessment, forty-nine in situ coal samples were collected from major coalfields of India. Intrinsic properties viz. proximate and ultimate analysis; and susceptibility indices like crossing point temperature, flammability temperature, Olpinski index and wet oxidation potential method of Indian coals were carried out to ascertain the liability of coal to spontaneous combustion. Statistical regression analysis showed that the parameters of ultimate analysis provide significant correlation with all investigated susceptibility indices as compared to the parameters of proximate analysis. Best correlated parameters (ultimate analysis) were used as inputs to the radial basis function network model. The model revealed that Olpinski index can be used as a reliable method to assess the liability of Indian coals to spontaneous combustion.
Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao
2014-09-18
The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.
[Resolution of overlapping chromatographic peaks by radial basis function neural network].
Li, Y B; Huang, X Y; Sha, M; Meng, X S
2001-03-01
A new algorithm-resolution of overlapping chromatographic peaks by radial basis function neural network(RBFNN) is presented. A two-phase genetic algorithm(GA) which has robustness and random globe optimization is used to train RBFNN so that it has the ability on the resolution of overlapping chromatographic peaks. The two-phase genetic algorithm involves two procedures: training structure and optimizing parameter. The first procedure uses GA to train the architectures of RBFNN, the second procedure uses gradient descent to train the center(tR) and the width(sigma) of RBFNN. The alternate use of these two procedures makes the network having the ability to learn structure, therefore makes itself adaptable to resolution of the chromatographic peaks with unknown number of components. The method proposed here needs no artificial interference, not only has it robustness and globalism, but also the ability of accurate resolution to completely overlapped chromatographic peaks. The simulation experiments show that this method is more accurate than other methods. PMID:12541651
An efficient method for ectopic beats cancellation based on radial basis function.
Mateo, Jorge; Torres, Ana; Rieta, José J
2011-01-01
The analysis of the surface Electrocardiogram (ECG) is the most extended noninvasive technique in cardiological diagnosis. In order to properly use the ECG, we need to cancel out ectopic beats. These beats may occur in both normal subjects and patients with heart disease, and their presence represents an important source of error which must be handled before any other analysis. This paper presents a method for electrocardiogram ectopic beat cancellation based on Radial Basis Function Neural Network (RBFNN). A train-able neural network ensemble approach to develop customized electrocardiogram beat classifier in an effort to further improve the performance of ECG processing and to offer individualized health care is presented. Six types of beats including: Normal Beats (NB); Premature Ventricular Contractions (PVC); Left Bundle Branch Blocks (LBBB); Right Bundle Branch Blocks (RBBB); Paced Beats (PB) and Ectopic Beats (EB) are obtained from the MIT-BIH arrhythmia database. Four morphological features are extracted from each beat after the preprocessing of the selected records. Average Results for the RBFNN based method provided an ectopic beat reduction (EBR) of (mean ± std) EBR = 7, 23 ± 2.18 in contrast to traditional compared methods that, for the best case, yielded EBR = 4.05 ± 2.13. The results prove that RBFNN based methods are able to obtain a very accurate reduction of ectopic beats together with low distortion of the QRST complex.
Simulation of structural response using a recurrent radial basis function network
Paez, T.L.
1994-08-01
System behaviors can be accurately simulated using artificial neural networks (ANNs), and one that performs well in simulation of structural response is the radial basis function network. A specific implementation of this is the connectionist normalized linear spline (CNLS) network, investigated in this study. A useful framework for ANN simulation of structural response is the recurrent network. This framework simulates the response of a structure one step at a time. It requires as inputs some measures of the excitation, and the response at previous times. On output, the recurrent ANN yields the response at some time in the future. This framework is practical to implement because every ANN requires training, and this is executed by showing the ANN examples of correct input/output behavior (exemplars), and requiring the ANN to simulate this behavior. In practical applications, hundreds or, perhaps, thousands, of exemplars are required for ANN training. The usual laboratory and non-neural numerical applications to be simulated by ANNs produce these amounts of information. Once the recurrent ANN is trained, it can be provided with excitation information, and used to propagate structural response, simulating the response it was trained to approximate. The structural characteristics, parameters in the CNLS network, and degree of training influence the accuracy of approximation. This investigation studies the accuracy of structural response simulation for a single-degree-of-freedom (SDF), nonlinear system excited by random vibration loading. The ANN used to simulate structural response is a recurrent CNLS network. We investigate the error in structural system simulation.
Solution of the quantum fluid dynamical equations with radial basis function interpolation
NASA Astrophysics Data System (ADS)
Hu, Xu-Guang; Ho, Tak-San; Rabitz, Herschel; Askar, Attila
2000-05-01
The paper proposes a numerical technique within the Lagrangian description for propagating the quantum fluid dynamical (QFD) equations in terms of the Madelung field variables R and S, which are connected to the wave function via the transformation ψ=exp\\{(R+iS)/ħ\\}. The technique rests on the QFD equations depending only on the form, not the magnitude, of the probability density ρ=\\|ψ\\|2 and on the structure of R=ħ/2 ln ρ generally being simpler and smoother than ρ. The spatially smooth functions R and S are especially suitable for multivariate radial basis function interpolation to enable the implementation of a robust numerical scheme. Examples of two-dimensional model systems show that the method rivals, in both efficiency and accuracy, the split-operator and Chebychev expansion methods. The results on a three-dimensional model system indicates that the present method is superior to the existing ones, especially, for its low storage requirement and its uniform accuracy. The advantage of the new algorithm is expected to increase for higher dimensional systems to provide a practical computational tool.
Solution of the quantum fluid dynamical equations with radial basis function interpolation
Hu; Ho; Rabitz; Askar
2000-05-01
The paper proposes a numerical technique within the Lagrangian description for propagating the quantum fluid dynamical (QFD) equations in terms of the Madelung field variables R and S, which are connected to the wave function via the transformation psi = exp(R + iS)/[symbol: see text]. The technique rests on the QFD equations depending only on the form, not the magnitude, of the probability density rho = magnitude of psi 2 and on the structure of R = [symbol: see text]/2 ln rho generally being simpler and smoother than rho. The spatially smooth functions R and S are especially suitable for multivariate radial basis function interpolation to enable the implementation of a robust numerical scheme. Examples of two-dimensional model systems show that the method rivals, in both efficiency and accuracy, the split-operator and Chebychev expansion methods. The results on a three-dimensional model system indicates that the present method is superior to the existing ones, especially, for its low storage requirement and its uniform accuracy. The advantage of the new algorithm is expected to increase for higher dimensional systems to provide a practical computational tool. PMID:11031661
Solution of the quantum fluid dynamical equations with radial basis function interpolation
Hu, Xu-Guang; Ho, Tak-San; Rabitz, Herschel; Askar, Attila
2000-05-01
The paper proposes a numerical technique within the Lagrangian description for propagating the quantum fluid dynamical (QFD) equations in terms of the Madelung field variables R and S, which are connected to the wave function via the transformation {psi}=exp{l_brace}(R+iS)/({Dirac_h}/2{pi})(right brace). The technique rests on the QFD equations depending only on the form, not the magnitude, of the probability density {rho}=|{psi}|{sup 2} and on the structure of R=({Dirac_h}/2{pi})/2 ln {rho} generally being simpler and smoother than {rho}. The spatially smooth functions R and S are especially suitable for multivariate radial basis function interpolation to enable the implementation of a robust numerical scheme. Examples of two-dimensional model systems show that the method rivals, in both efficiency and accuracy, the split-operator and Chebychev expansion methods. The results on a three-dimensional model system indicates that the present method is superior to the existing ones, especially, for its low storage requirement and its uniform accuracy. The advantage of the new algorithm is expected to increase for higher dimensional systems to provide a practical computational tool. (c) 2000 The American Physical Society.
Space shuttle main engine sensor modeling using radial-basis-function neural networks
NASA Astrophysics Data System (ADS)
Wheeler, Kevin R.; Dhawan, Atam P.; Meyer, Claudia M.
1994-11-01
An efficient method of parameter prediction is needed for sensor validation of space shuttle main-engine (SSME) parameters during real-time safety monitoring and post-test analysis. Feedforward neural networks (FFNN) have been used to model the highly nonlinear and dynamic SSME parameters during startup. Due to several problems associated with the use of feedforward networks, radial-basis-function neural networks (RBFNN) were investigated in modeling SSME parameters. In this paper, RBFNNs are used to predict the high-pressure oxidizer turbine discharge temperature, a redlined parameter, during the startup transient. Data from SSME ground test firings were used to train and validate the RBFNNs. The performance of the RBFNN model is compared with that of a FFNN model, trained with the Quickprop learning algorithm. In comparison with the FFNN model, the RBFNN-based model was found to be more robust against variations in architecture and network parameters, and was faster to train. In addition, the performance of the RBFNN model during nominal operation and during simulated input sensor failures was found to be robust in the presence of small deviations in the input.
Online dimensionality reduction using competitive learning and Radial Basis Function network.
Tomenko, Vladimir
2011-06-01
The general purpose dimensionality reduction method should preserve data interrelations at all scales. Additional desired features include online projection of new data, processing nonlinearly embedded manifolds and large amounts of data. The proposed method, called RBF-NDR, combines these features. RBF-NDR is comprised of two modules. The first module learns manifolds by utilizing modified topology representing networks and geodesic distance in data space and approximates sampled or streaming data with a finite set of reference patterns, thus achieving scalability. Using input from the first module, the dimensionality reduction module constructs mappings between observation and target spaces. Introduction of specific loss function and synthesis of the training algorithm for Radial Basis Function network results in global preservation of data structures and online processing of new patterns. The RBF-NDR was applied for feature extraction and visualization and compared with Principal Component Analysis (PCA), neural network for Sammon's projection (SAMANN) and Isomap. With respect to feature extraction, the method outperformed PCA and yielded increased performance of the model describing wastewater treatment process. As for visualization, RBF-NDR produced superior results compared to PCA and SAMANN and matched Isomap. For the Topic Detection and Tracking corpus, the method successfully separated semantically different topics.
NASA Astrophysics Data System (ADS)
An, Yu; Liu, Jie; Zhang, Guanglei; Ye, Jinzuo; Mao, Yamin; Jiang, Shixin; Shang, Wenting; Du, Yang; Chi, Chongwei; Tian, Jie
2015-10-01
Fluorescence molecular tomography (FMT) is a promising tool in the study of cancer, drug discovery, and disease diagnosis, enabling noninvasive and quantitative imaging of the biodistribution of fluorophores in deep tissues via image reconstruction techniques. Conventional reconstruction methods based on the finite-element method (FEM) have achieved acceptable stability and efficiency. However, some inherent shortcomings in FEM meshes, such as time consumption in mesh generation and a large discretization error, limit further biomedical application. In this paper, we propose a meshless method for reconstruction of FMT (MM-FMT) using compactly supported radial basis functions (CSRBFs). With CSRBFs, the image domain can be accurately expressed by continuous CSRBFs, avoiding the discretization error to a certain degree. After direct collocation with CSRBFs, the conventional optimization techniques, including Tikhonov, L1-norm iteration shrinkage (L1-IS), and sparsity adaptive matching pursuit, were adopted to solve the meshless reconstruction. To evaluate the performance of the proposed MM-FMT, we performed numerical heterogeneous mouse experiments and in vivo bead-implanted mouse experiments. The results suggest that the proposed MM-FMT method can reduce the position error of the reconstruction result to smaller than 0.4 mm for the double-source case, which is a significant improvement for FMT.
Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao
2014-01-01
The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality. PMID:25237902
Mass predictions of the relativistic mean-field model with the radial basis function approach
NASA Astrophysics Data System (ADS)
Zheng, J. S.; Wang, N. Y.; Wang, Z. Y.; Niu, Z. M.; Niu, Y. F.; Sun, B.
2014-07-01
The radial basis function (RBF) is a powerful tool to improve mass predictions of nuclear models. By combining the RBF approach with the relativistic mean-field (RMF) model, the systematic deviations between mass predictions of the RMF model and the experimental data are eliminated to a large extent and the resulting rms deviation is reduced from 2.217 to 0.488 MeV. Furthermore, it is found that the RBF approach has a relatively reliable extrapolative power along the distance from the β-stability line except for a large uncertainty around the region at magic number. From the deduced neutron separation energies, we found that the description of the nuclear shell structure and shape transition is also significantly improved by the RBF approach, thus improving agreement with the solar r-process abundances before A =130 and speeding up the r-matter flow. Therefore, a shorter irradiation time is enough to reproduce the solar r-process abundance distribution for the improved RMF mass model, which is closer to the irradiation time for those sophisticated mass models.
An, Yu; Liu, Jie; Zhang, Guanglei; Ye, Jinzuo; Mao, Yamin; Jiang, Shixin; Shang, Wenting; Du, Yang; Chi, Chongwei; Tian, Jie
2015-10-01
Fluorescence molecular tomography (FMT) is a promising tool in the study of cancer, drug discovery, and disease diagnosis, enabling noninvasive and quantitative imaging of the biodistribution of fluorophores in deep tissues via image reconstruction techniques. Conventional reconstruction methods based on the finite-element method (FEM) have achieved acceptable stability and efficiency. However, some inherent shortcomings in FEM meshes, such as time consumption in mesh generation and a large discretization error, limit further biomedical application. In this paper, we propose a meshless method for reconstruction of FMT (MM-FMT) using compactly supported radial basis functions (CSRBFs). With CSRBFs, the image domain can be accurately expressed by continuous CSRBFs, avoiding the discretization error to a certain degree. After direct collocation with CSRBFs, the conventional optimization techniques, including Tikhonov, L1-norm iteration shrinkage (L1-IS), and sparsity adaptive matching pursuit, were adopted to solve the meshless reconstruction. To evaluate the performance of the proposed MM-FMT, we performed numerical heterogeneous mouse experiments and in vivo bead-implanted mouse experiments. The results suggest that the proposed MM-FMT method can reduce the position error of the reconstruction result to smaller than 0.4 mm for the double-source case, which is a significant improvement for FMT. PMID:26451513
Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao
2014-01-01
The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality. PMID:25237902
Enhancing finite differences with radial basis functions: Experiments on the Navier-Stokes equations
NASA Astrophysics Data System (ADS)
Flyer, Natasha; Barnett, Gregory A.; Wicker, Louis J.
2016-07-01
Polynomials are used together with polyharmonic spline (PHS) radial basis functions (RBFs) to create local RBF-finite-difference (RBF-FD) weights on different node layouts for spatial discretizations that can be viewed as enhancements of the classical finite differences (FD). The presented method replicates the convergence properties of FD but for arbitrary node layouts. It is tested on the 2D compressible Navier-Stokes equations at low Mach number, relevant to atmospheric flows. Test cases are taken from the numerical weather prediction community and solved on bounded domains. Thus, attention is given on how to handle boundaries with the RBF-FD method, as well as a novel implementation for hyperviscosity. Comparisons are done on Cartesian, hexagonal, and quasi-uniform node layouts. Consideration and guidelines are given on PHS order, polynomial degree and stencil size. The main advantages of the present method are: 1) capturing the basic physics of the problem surprisingly well, even at very coarse resolutions, 2) high-order accuracy without the need of tuning a shape parameter, and 3) the inclusion of polynomials eliminates stagnation (saturation) errors. A MATLAB code is given to calculate the differentiation weights for this novel approach.
Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction
Venkatesan, R.
2016-01-01
Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets. PMID:27738649
Spatial modeling of PM2.5 concentrations with a multifactoral radial basis function neural network.
Zou, Bin; Wang, Min; Wan, Neng; Wilson, J Gaines; Fang, Xin; Tang, Yuqi
2015-07-01
Accurate measurements of PM2.5 concentration over time and space are especially critical for reducing adverse health outcomes. However, sparsely stationary monitoring sites considerably hinder the ability to effectively characterize observed concentrations. Utilizing data on meteorological and land-related factors, this study introduces a radial basis function (RBF) neural network method for estimating PM2.5 concentrations based on sparse observed inputs. The state of Texas in the USA was selected as the study area. Performance of the RBF models was evaluated by statistic indices including mean square error, mean absolute error, mean relative deviation, and the correlation coefficient. Results show that the annual PM2.5 concentrations estimated by the RBF models with meteorological factors and/or land-related factors were markedly closer to the observed concentrations. RBF models with combined meteorological and land-related factors achieved best performance relative to ones with either type of these factors only. It can be concluded that meteorological factors and land-related factors are useful for articulating the variation of PM2.5 concentration in a given study area. With these covariate factors, the RBF neural network can effectively estimate PM2.5 concentrations with acceptable accuracy under the condition of sparse monitoring stations. The improved accuracy of air concentration estimation would greatly benefit epidemiological and environmental studies in characterizing local air pollution and in helping reduce population exposures for areas with limited availability of air quality data.
Behnia, Pouran
2007-06-15
The metallogeny of Central Iran is characterized mainly by the presence of several iron, apatite, and uranium deposits of Proterozoic age. Radial Basis Function Link Networks (RBFLN) were used as a data-driven method for GIS-based predictive mapping of Proterozoic mineralization in this area. To generate the input data for RBFLN, the evidential maps comprising stratigraphic, structural, geophysical, and geochemical data were used. Fifty-eight deposits and 58 'nondeposits' were used to train the network. The operations for the application of neural networks employed in this study involve both multiclass and binary representation of evidential maps. Running RBFLN on different input data showed that an increase in the number of evidential maps and classes leads to a larger classification sum of squared error (SSE). As a whole, an increase in the number of iterations resulted in the improvement of training SSE. The results of applying RBFLN showed that a successful classification depends on the existence of spatially well distributed deposits and nondeposits throughout the study area.
Solution to PDEs using radial basis function finite-differences (RBF-FD) on multiple GPUs
Bollig, Evan F.; Flyer, Natasha; Erlebacher, Gordon
2012-08-30
This paper presents parallelization strategies for the radial basis function-finite difference (RBF-FD) method. As a generalized finite differencing scheme, the RBF-FD method functions without the need for underlying meshes to structure nodes. It offers high-order accuracy approximation and scales as O(N) per time step, with N being with the total number of nodes. To our knowledge, this is the first implementation of the RBF-FD method to leverage GPU accelerators for the solution of PDEs. Additionally, this implementation is the first to span both multiple CPUs and multiple GPUs. OpenCL kernels target the GPUs and inter-processor communication and synchronization is managed by the Message Passing Interface (MPI). We verify our implementation of the RBF-FD method with two hyperbolic PDEs on the sphere, and demonstrate up to 9x speedup on a commodity GPU with unoptimized kernel implementations. On a high performance cluster, the method achieves up to 7x speedup for the maximum problem size of 27,556 nodes.
Ensembles of radial basis function networks for spectroscopic detection of cervical precancer
NASA Technical Reports Server (NTRS)
Tumer, K.; Ramanujam, N.; Ghosh, J.; Richards-Kortum, R.
1998-01-01
The mortality related to cervical cancer can be substantially reduced through early detection and treatment. However, current detection techniques, such as Pap smear and colposcopy, fail to achieve a concurrently high sensitivity and specificity. In vivo fluorescence spectroscopy is a technique which quickly, noninvasively and quantitatively probes the biochemical and morphological changes that occur in precancerous tissue. A multivariate statistical algorithm was used to extract clinically useful information from tissue spectra acquired from 361 cervical sites from 95 patients at 337-, 380-, and 460-nm excitation wavelengths. The multivariate statistical analysis was also employed to reduce the number of fluorescence excitation-emission wavelength pairs required to discriminate healthy tissue samples from precancerous tissue samples. The use of connectionist methods such as multilayered perceptrons, radial basis function (RBF) networks, and ensembles of such networks was investigated. RBF ensemble algorithms based on fluorescence spectra potentially provide automated and near real-time implementation of precancer detection in the hands of nonexperts. The results are more reliable, direct, and accurate than those achieved by either human experts or multivariate statistical algorithms.
Fast and efficient second-order method for training radial basis function networks.
Xie, Tiantian; Yu, Hao; Hewlett, Joel; Rózycki, Paweł; Wilamowski, Bogdan
2012-04-01
This paper proposes an improved second order (ISO) algorithm for training radial basis function (RBF) networks. Besides the traditional parameters, including centers, widths and output weights, the input weights on the connections between input layer and hidden layer are also adjusted during the training process. More accurate results can be obtained by increasing variable dimensions. Initial centers are chosen from training patterns and other parameters are generated randomly in limited range. Taking the advantages of fast convergence and powerful search ability of second order algorithms, the proposed ISO algorithm can normally reach smaller training/testing error with much less number of RBF units. During the computation process, quasi Hessian matrix and gradient vector are accumulated as the sum of related sub matrices and vectors, respectively. Only one Jacobian row is stored and used for multiplication, instead of the entire Jacobian matrix storage and multiplication. Memory reduction benefits the computation speed and allows the training of problems with basically unlimited number of patterns. Several practical discrete and continuous classification problems are applied to test the properties of the proposed ISO training algorithm.
Sun, Gang; Hoff, Steven J; Zelle, Brian C; Nelson, Minda A
2008-12-01
It is vital to forecast gas and particle matter concentrations and emission rates (GPCER) from livestock production facilities to assess the impact of airborne pollutants on human health, ecological environment, and global warming. Modeling source air quality is a complex process because of abundant nonlinear interactions between GPCER and other factors. The objective of this study was to introduce statistical methods and radial basis function (RBF) neural network to predict daily source air quality in Iowa swine deep-pit finishing buildings. The results show that four variables (outdoor and indoor temperature, animal units, and ventilation rates) were identified as relative important model inputs using statistical methods. It can be further demonstrated that only two factors, the environment factor and the animal factor, were capable of explaining more than 94% of the total variability after performing principal component analysis. The introduction of fewer uncorrelated variables to the neural network would result in the reduction of the model structure complexity, minimize computation cost, and eliminate model overfitting problems. The obtained results of RBF network prediction were in good agreement with the actual measurements, with values of the correlation coefficient between 0.741 and 0.995 and very low values of systemic performance indexes for all the models. The good results indicated the RBF network could be trained to model these highly nonlinear relationships. Thus, the RBF neural network technology combined with multivariate statistical methods is a promising tool for air pollutant emissions modeling.
Ensembles of radial basis function networks for spectroscopic detection of cervical precancer.
Tumer, K; Ramanujam, N; Ghosh, J; Richards-Kortum, R
1998-08-01
The mortality related to cervical cancer can be substantially reduced through early detection and treatment. However, current detection techniques, such as Pap smear and colposcopy, fail to achieve a concurrently high sensitivity and specificity. In vivo fluorescence spectroscopy is a technique which quickly, noninvasively and quantitatively probes the biochemical and morphological changes that occur in precancerous tissue. A multivariate statistical algorithm was used to extract clinically useful information from tissue spectra acquired from 361 cervical sites from 95 patients at 337-, 380-, and 460-nm excitation wavelengths. The multivariate statistical analysis was also employed to reduce the number of fluorescence excitation-emission wavelength pairs required to discriminate healthy tissue samples from precancerous tissue samples. The use of connectionist methods such as multilayered perceptrons, radial basis function (RBF) networks, and ensembles of such networks was investigated. RBF ensemble algorithms based on fluorescence spectra potentially provide automated and near real-time implementation of precancer detection in the hands of nonexperts. The results are more reliable, direct, and accurate than those achieved by either human experts or multivariate statistical algorithms.
Zhang, Zhuoyong; Wang, Dan; Harrington, Peter de B; Voorhees, Kent J; Rees, Jon
2004-06-17
Forward selection improved radial basis function (RBF) network was applied to bacterial classification based on the data obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The classification of each bacterium cultured at different time was discussed and the effect of parameters of the RBF network was investigated. The new method involves forward selection to prevent overfitting and generalized cross-validation (GCV) was used as model selection criterion (MSC). The original data was compressed by using wavelet transformation to speed up the network training and reduce the number of variables of the original MS data. The data was normalized prior training and testing a network to define the area the neural network to be trained in, accelerate the training rate, and reduce the range the parameters to be selected in. The one-out-of-n method was used to split the data set of p samples into a training set of size p-1 and a test set of size 1. With the improved method, the classification correctness for the five bacteria discussed in the present paper are 87.5, 69.2, 80, 92.3, and 92.8%, respectively.
Radial Basis Function Based Neural Network for Motion Detection in Dynamic Scenes.
Huang, Shih-Chia; Do, Ben-Hsiang
2014-01-01
Motion detection, the process which segments moving objects in video streams, is the first critical process and plays an important role in video surveillance systems. Dynamic scenes are commonly encountered in both indoor and outdoor situations and contain objects such as swaying trees, spouting fountains, rippling water, moving curtains, and so on. However, complete and accurate motion detection in dynamic scenes is often a challenging task. This paper presents a novel motion detection approach based on radial basis function artificial neural networks to accurately detect moving objects not only in dynamic scenes but also in static scenes. The proposed method involves two important modules: a multibackground generation module and a moving object detection module. The multibackground generation module effectively generates a flexible probabilistic model through an unsupervised learning process to fulfill the property of either dynamic background or static background. Next, the moving object detection module achieves complete and accurate detection of moving objects by only processing blocks that are highly likely to contain moving objects. This is accomplished by two procedures: the block alarm procedure and the object extraction procedure. The detection results of our method were evaluated by qualitative and quantitative comparisons with other state-of-the-art methods based on a wide range of natural video sequences. The overall results show that the proposed method substantially outperforms existing methods with Similarity and F1 accuracy rates of 69.37% and 65.50%, respectively. PMID:24108721
A Fast Incremental Learning for Radial Basis Function Networks Using Local Linear Regression
NASA Astrophysics Data System (ADS)
Ozawa, Seiichi; Okamoto, Keisuke
To avoid the catastrophic interference in incremental learning, we have proposed Resource Allocating Network with Long Term Memory (RAN-LTM). In RAN-LTM, not only new training data but also some memory items stored in long-term memory are trained either by a gradient descent algorithm or by solving a linear regression problem. In the latter approach, radial basis function (RBF) centers are not trained but selected based on output errors when connection weights are updated. The proposed incremental learning algorithm belongs to the latter approach where the errors not only for a training data but also for several retrieved memory items and pseudo training data are minimized to suppress the catastrophic interference. The novelty of the proposed algorithm is that connection weights to be learned are restricted based on RBF activation in order to improve the efficiency in learning time and memory size. We evaluate the performance of the proposed algorithm in one-dimensional and multi-dimensional function approximation problems in terms of approximation accuracy, learning time, and average memory size. The experimental results demonstrate that the proposed algorithm can learn fast and have good performance with less memory size compared to memory-based learning methods.
NASA Astrophysics Data System (ADS)
Shankar, Praveen
The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance. The training algorithm to grow the network and adapt the parameters is derived from Lyapunov theory. In addition to growing the network of basis functions, a pruning strategy is incorporated to keep the size of the network as small as possible. This algorithm is implemented on a high performance flight vehicle such as F-15 military aircraft. The baseline dynamic inversion controller is augmented with a Self-Organizing Radial Basis Function Network (SORBFN) to minimize the effect of the inversion error which may occur due to imperfect modeling, approximate inversion or sudden changes in aircraft dynamics. The dynamic inversion controller is simulated for different situations including control surface failures, modeling errors and external disturbances with and without the adaptive network. A performance measure of maximum tracking error is specified for both the controllers a priori. Excellent tracking error minimization to a pre-specified level using the adaptive approximation based controller was achieved while the baseline dynamic inversion controller failed to meet this performance specification. The performance of the SORBFN based controller is also compared to a fixed RBF network
ERIC Educational Resources Information Center
Kayri, Murat
2015-01-01
The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…
Yoo, Sung-Hoon; Oh, Sung-Kwun; Pedrycz, Witold
2015-09-01
In this study, we propose a hybrid method of face recognition by using face region information extracted from the detected face region. In the preprocessing part, we develop a hybrid approach based on the Active Shape Model (ASM) and the Principal Component Analysis (PCA) algorithm. At this step, we use a CCD (Charge Coupled Device) camera to acquire a facial image by using AdaBoost and then Histogram Equalization (HE) is employed to improve the quality of the image. ASM extracts the face contour and image shape to produce a personal profile. Then we use a PCA method to reduce dimensionality of face images. In the recognition part, we consider the improved Radial Basis Function Neural Networks (RBF NNs) to identify a unique pattern associated with each person. The proposed RBF NN architecture consists of three functional modules realizing the condition phase, the conclusion phase, and the inference phase completed with the help of fuzzy rules coming in the standard 'if-then' format. In the formation of the condition part of the fuzzy rules, the input space is partitioned with the use of Fuzzy C-Means (FCM) clustering. In the conclusion part of the fuzzy rules, the connections (weights) of the RBF NNs are represented by four kinds of polynomials such as constant, linear, quadratic, and reduced quadratic. The values of the coefficients are determined by running a gradient descent method. The output of the RBF NNs model is obtained by running a fuzzy inference method. The essential design parameters of the network (including learning rate, momentum coefficient and fuzzification coefficient used by the FCM) are optimized by means of Differential Evolution (DE). The proposed P-RBF NNs (Polynomial based RBF NNs) are applied to facial recognition and its performance is quantified from the viewpoint of the output performance and recognition rate. PMID:26163042
NASA Astrophysics Data System (ADS)
Voigt, M.; Lorenz, P.; Kruschke, T.; Osinski, R.; Ulbrich, U.; Leckebusch, G. C.
2012-04-01
Winterstorms and related gusts can cause extensive socio-economic damages. Knowledge about the occurrence and the small scale structure of such events may help to make regional estimations of storm losses. For a high spatial and temporal representation, the use of dynamical downscaling methods (RCM) is a cost-intensive and time-consuming option and therefore only applicable for a limited number of events. The current study explores a methodology to provide a statistical downscaling, which offers small scale structured gust fields from an extended large scale structured eventset. Radial-basis-function (RBF) networks in combination with bidirectional Kohonen (BDK) maps are used to generate the gustfields on a spatial resolution of 7 km from the 6-hourly mean sea level pressure field from ECMWF reanalysis data. BDK maps are a kind of neural network which handles supervised classification problems. In this study they are used to provide prototypes for the RBF network and give a first order approximation for the output data. A further interpolation is done by the RBF network. For the training process the 50 most extreme storm events over the North Atlantic area from 1957 to 2011 are used, which have been selected from ECMWF reanalysis datasets ERA40 and ERA-Interim by an objective wind based tracking algorithm. These events were downscaled dynamically by application of the DWD model chain GME → COSMO-EU. Different model parameters and their influence on the quality of the generated high-resolution gustfields are studied. It is shown that the statistical RBF network approach delivers reasonable results in modeling the regional gust fields for untrained events.
Yoo, Sung-Hoon; Oh, Sung-Kwun; Pedrycz, Witold
2015-09-01
In this study, we propose a hybrid method of face recognition by using face region information extracted from the detected face region. In the preprocessing part, we develop a hybrid approach based on the Active Shape Model (ASM) and the Principal Component Analysis (PCA) algorithm. At this step, we use a CCD (Charge Coupled Device) camera to acquire a facial image by using AdaBoost and then Histogram Equalization (HE) is employed to improve the quality of the image. ASM extracts the face contour and image shape to produce a personal profile. Then we use a PCA method to reduce dimensionality of face images. In the recognition part, we consider the improved Radial Basis Function Neural Networks (RBF NNs) to identify a unique pattern associated with each person. The proposed RBF NN architecture consists of three functional modules realizing the condition phase, the conclusion phase, and the inference phase completed with the help of fuzzy rules coming in the standard 'if-then' format. In the formation of the condition part of the fuzzy rules, the input space is partitioned with the use of Fuzzy C-Means (FCM) clustering. In the conclusion part of the fuzzy rules, the connections (weights) of the RBF NNs are represented by four kinds of polynomials such as constant, linear, quadratic, and reduced quadratic. The values of the coefficients are determined by running a gradient descent method. The output of the RBF NNs model is obtained by running a fuzzy inference method. The essential design parameters of the network (including learning rate, momentum coefficient and fuzzification coefficient used by the FCM) are optimized by means of Differential Evolution (DE). The proposed P-RBF NNs (Polynomial based RBF NNs) are applied to facial recognition and its performance is quantified from the viewpoint of the output performance and recognition rate.
Near and long-term load prediction using radial basis function networks
Hancock, M.F.
1995-12-31
A number of researchers have investigated the application of multi-layer perceptrons (MLP`s), a variety of neural network, to the problem of short-term load forecasting for electric utilities (e.g., Rahman & Hazin, IEEE Trans. Power Systems, May 1993). {open_quotes}Short-term{close_quotes} in this context typically means {open_quotes}next day{close_quotes}. These forecasts have been based upon previous day actual loads and meteorological factors (e.g., max-min temperature, relative humidity). We describe the application of radial basis function networks (RBF`s) to the {open_quotes}long-term{close_quotes} (next year) load forecasting problem. The RBF network performs a two-stage classification based upon annual average loads and meteorological data. During stage 1, discrete classification is performed using radius-limited elements. During stage 2, a multi-layer perceptron may be applied. The quantized output is used to correct a prediction template. The stage 1 classifier is trained by maximizing an objective function (the {open_quotes}disambiguity{close_quotes}). The stage 2 MLP`s are trained by standard back-propagation. This work uses 12 months of hourly meteorological data, and the corresponding hourly load data for both commercial and residential feeders. At the current stage of development, the RBF machine can train on 20% of the weather/load data (selected by simple linear sampling), and estimate the hourly load for an entire year (8,760 data points) with 9.1% error (RMS, relative to daily peak load). (By comparison, monthly mean profiles perform at c. 12% error.) The best short-term load forecasters operate in the 2% error range. The current system is an engineering prototype, and development is continuing.
Hernández-Caraballo, Edwin A; Avila de Hernández, Rita M; Rivas-Echeverría, Francklin; Capote-Luna, Tarcisio
2008-01-15
Radial basis neural networks (RBNNs) were developed and evaluated for discrimination of specimens of 'aguardiente de Cocuy', a spirituous beverage produced in the northwestern region of Venezuela. The beverage is distilled from the must of Agave cocui Trelease in an artisanship fashion with little quality control. Forty specimens, with known concentrations of copper, iron, and zinc, were used in this study. The specimens were previously collected in various locations around Sucre Municipality (Falcón State) and Urdaneta Municipality (Lara State). The normalized concentrations of these elements served as indirect descriptors of origin (input data). They were presented to the neural networks through 1-3 input nodes in seven different combinations. In addition, two categories (two collection sites) and four categories (two collection sites+two manufacturing conditions) were designated as output data, in order to assess the impact of such selection on the discrimination performance. The overall performance of the four-category RBNNs was as follows (the input data is indicated in parentheses): (Cu-Fe)>(Cu-Zn)>(Cu)>(Zn)>(Fe-Zn)>(Cu-Fe-Zn)>(Fe). In this case, the highest percentage of correct hits was 82.5%. For the two-category RBNNs, the performance decreased as indicated below: (Cu)>(Cu-Fe)>(Cu-Zn)>(Fe-Zn)>(Zn) approximately (Cu-Fe-Zn)>(Fe). The reduction in the number of categories led to an increase in the discrimination performance of all the RBNNs, the best of which was 90.0%. The possibility of discriminating specimens of 'aguardiente de Cocuy' with such an accuracy, based on a single-element determination, is particularly attractive as it would result in a reduction of analysis' costs and laboratory's response time.
Unification of Plasma Fluid and Kinetic Theory via Gaussian Radial Basis Functions
NASA Astrophysics Data System (ADS)
Candy, J. M.
2015-11-01
A fundamental macroscopic description of a magnetized plasma is the Vlasov equation supplemented by the nonlinear inverse-square force Fokker-Planck collision operator [Rosenbluth et al., Phys. Rev. 107, 1957]. The Vlasov part describes advection in a six-dimensional phase space whereas the collision operator contains friction and diffusion coefficients that are weighted velocity-space integrals of the particle distribution function. The Fokker-Planck collision operator is an integro-differential, nonlinear (bilinear) operator. Numerical discretization of the operator, in particular for collisions of unlike species, is extremely challenging. In this work, we describe a new approach to discretize the entire kinetic system based on an expansion in Gaussian Radial Basis functions (RBFs). This approach is particularly well-suited to treat the collision operator because the friction and diffusion coefficients can be analytically calculated. Although the RBF method is known to be a powerful scheme for the interpolation of scattered multidimensional data, Gaussian RBFs also have a deep physical interpretation in statistical mechanics and plasma physics as local thermodynamic equilibria. We outline the general theory, highlight the connection to plasma fluid theories, and also give 2D and 3D numerical solutions of the nonlinear Fokker-Planck equation. A broad spectrum of applications for the new method is anticipated in both astrophysical and laboratory plasmas. In particular, we believe that the RBF method may provide a new bridge between fluid and kinetic descriptions of magnetized plasma. Work supported in part by US DOE under DE-FG02-08ER54963.
Hernández-Caraballo, Edwin A; Avila de Hernández, Rita M; Rivas-Echeverría, Francklin; Capote-Luna, Tarcisio
2008-01-15
Radial basis neural networks (RBNNs) were developed and evaluated for discrimination of specimens of 'aguardiente de Cocuy', a spirituous beverage produced in the northwestern region of Venezuela. The beverage is distilled from the must of Agave cocui Trelease in an artisanship fashion with little quality control. Forty specimens, with known concentrations of copper, iron, and zinc, were used in this study. The specimens were previously collected in various locations around Sucre Municipality (Falcón State) and Urdaneta Municipality (Lara State). The normalized concentrations of these elements served as indirect descriptors of origin (input data). They were presented to the neural networks through 1-3 input nodes in seven different combinations. In addition, two categories (two collection sites) and four categories (two collection sites+two manufacturing conditions) were designated as output data, in order to assess the impact of such selection on the discrimination performance. The overall performance of the four-category RBNNs was as follows (the input data is indicated in parentheses): (Cu-Fe)>(Cu-Zn)>(Cu)>(Zn)>(Fe-Zn)>(Cu-Fe-Zn)>(Fe). In this case, the highest percentage of correct hits was 82.5%. For the two-category RBNNs, the performance decreased as indicated below: (Cu)>(Cu-Fe)>(Cu-Zn)>(Fe-Zn)>(Zn) approximately (Cu-Fe-Zn)>(Fe). The reduction in the number of categories led to an increase in the discrimination performance of all the RBNNs, the best of which was 90.0%. The possibility of discriminating specimens of 'aguardiente de Cocuy' with such an accuracy, based on a single-element determination, is particularly attractive as it would result in a reduction of analysis' costs and laboratory's response time. PMID:18371722
Detection of hard exudates in retinal images using a radial basis function classifier.
García, María; Sánchez, Clara I; Poza, Jesús; López, María I; Hornero, Roberto
2009-07-01
Diabetic retinopathy (DR) is one of the most important causes of visual impairment. Automatic recognition of DR lesions, like hard exudates (EXs), in retinal images can contribute to the diagnosis and screening of the disease. The aim of this study was to automatically detect these lesions in fundus images. To achieve this goal, each image was normalized and the candidate EX regions were segmented by a combination of global and adaptive thresholding. Then, a group of features was extracted from image regions and the subset which best discriminated between EXs and retinal background was selected by means of logistic regression (LR). This optimal subset was subsequently used as input to a radial basis function (RBF) neural network. To improve the performance of the proposed algorithm, some noisy regions were eliminated by an innovative postprocessing of the image. The main novelty of the paper is the use of LR in conjunction with RBF and the proposed postprocessing technique. Our database was composed of 117 images with variable color, brightness and quality. The database was divided into a training set of 50 images (from DR patients) and a test set of 67 images (40 from DR patients and 27 from healthy retinas). Using a lesion-based criterion (pixel resolution), a mean sensitivity of 92.1% and a mean positive predictive value of 86.4% were obtained. With an image-based criterion, a mean sensitivity of 100%, mean specificity of 70.4% and mean accuracy of 88.1% were achieved. These results suggest that the proposed method could be a diagnostic aid for ophthalmologists in the screening for DR.
A new discrete-continuous algorithm for radial basis function networks construction.
Zhang, Long; Li, Kang; He, Haibo; Irwin, George W
2013-11-01
The construction of a radial basis function (RBF) network involves the determination of the model size, hidden nodes, and output weights. Least squares-based subset selection methods can determine a RBF model size and its parameters simultaneously. Although these methods are robust, they may not achieve optimal results. Alternatively, gradient methods are widely used to optimize all the parameters. The drawback is that most algorithms may converge slowly as they treat hidden nodes and output weights separately and ignore their correlations. In this paper, a new discrete-continuous algorithm is proposed for the construction of a RBF model. First, the orthogonal least squares (OLS)-based forward stepwise selection constructs an initial model by selecting model terms one by one from a candidate term pool. Then a new Levenberg-Marquardt (LM)-based parameter optimization is proposed to further optimize the hidden nodes and output weights in the continuous space. To speed up the convergence, the proposed parameter optimization method considers the correlation between the hidden nodes and output weights, which is achieved by translating the output weights to dependent parameters using the OLS method. The correlation is also used by the previously proposed continuous forward algorithm (CFA). However, unlike the CFA, the new method optimizes all the parameters simultaneously. In addition, an equivalent recursive sum of squared error is derived to reduce the computation demanding for the first derivatives used in the LM method. Computational complexity is given to confirm the new method is much more computationally efficient than the CFA. Different numerical examples are presented to illustrate the effectiveness of the proposed method. Further, Friedman statistical tests on 13 classification problems are performed, and the results demonstrate that RBF networks built by the new method are very competitive in comparison with some popular classifiers.
Lee, Tzong-Yi; Chen, Shu-An; Hung, Hsin-Yi; Ou, Yu-Yen
2011-03-09
Ubiquitin (Ub) is a small protein that consists of 76 amino acids about 8.5 kDa. In ubiquitin conjugation, the ubiquitin is majorly conjugated on the lysine residue of protein by Ub-ligating (E3) enzymes. Three major enzymes participate in ubiquitin conjugation. They are E1, E2 and E3 which are responsible for activating, conjugating and ligating ubiquitin, respectively. Ubiquitin conjugation in eukaryotes is an important mechanism of the proteasome-mediated degradation of a protein and regulating the activity of transcription factors. Motivated by the importance of ubiquitin conjugation in biological processes, this investigation develops a method, UbSite, which uses utilizes an efficient radial basis function (RBF) network to identify protein ubiquitin conjugation (ubiquitylation) sites. This work not only investigates the amino acid composition but also the structural characteristics, physicochemical properties, and evolutionary information of amino acids around ubiquitylation (Ub) sites. With reference to the pathway of ubiquitin conjugation, the substrate sites for E3 recognition, which are distant from ubiquitylation sites, are investigated. The measurement of F-score in a large window size (-20∼+20) revealed a statistically significant amino acid composition and position-specific scoring matrix (evolutionary information), which are mainly located distant from Ub sites. The distant information can be used effectively to differentiate Ub sites from non-Ub sites. As determined by five-fold cross-validation, the model that was trained using the combination of amino acid composition and evolutionary information performs best in identifying ubiquitin conjugation sites. The prediction sensitivity, specificity, and accuracy are 65.5%, 74.8%, and 74.5%, respectively. Although the amino acid sequences around the ubiquitin conjugation sites do not contain conserved motifs, the cross-validation result indicates that the integration of distant sequence features of Ub
Hung, Hsin-Yi; Ou, Yu-Yen
2011-01-01
Ubiquitin (Ub) is a small protein that consists of 76 amino acids about 8.5 kDa. In ubiquitin conjugation, the ubiquitin is majorly conjugated on the lysine residue of protein by Ub-ligating (E3) enzymes. Three major enzymes participate in ubiquitin conjugation. They are – E1, E2 and E3 which are responsible for activating, conjugating and ligating ubiquitin, respectively. Ubiquitin conjugation in eukaryotes is an important mechanism of the proteasome-mediated degradation of a protein and regulating the activity of transcription factors. Motivated by the importance of ubiquitin conjugation in biological processes, this investigation develops a method, UbSite, which uses utilizes an efficient radial basis function (RBF) network to identify protein ubiquitin conjugation (ubiquitylation) sites. This work not only investigates the amino acid composition but also the structural characteristics, physicochemical properties, and evolutionary information of amino acids around ubiquitylation (Ub) sites. With reference to the pathway of ubiquitin conjugation, the substrate sites for E3 recognition, which are distant from ubiquitylation sites, are investigated. The measurement of F-score in a large window size (−20∼+20) revealed a statistically significant amino acid composition and position-specific scoring matrix (evolutionary information), which are mainly located distant from Ub sites. The distant information can be used effectively to differentiate Ub sites from non-Ub sites. As determined by five-fold cross-validation, the model that was trained using the combination of amino acid composition and evolutionary information performs best in identifying ubiquitin conjugation sites. The prediction sensitivity, specificity, and accuracy are 65.5%, 74.8%, and 74.5%, respectively. Although the amino acid sequences around the ubiquitin conjugation sites do not contain conserved motifs, the cross-validation result indicates that the integration of distant sequence features
Evaluation of Radial Basis Function Neural Networks in Subsurface Seismic Characterization
NASA Astrophysics Data System (ADS)
Zhao, T.; Ramachandran, K.
2012-12-01
Neural network provides a mathematical non-linear mapping technique that has been employed in many scientific and engineering studies. A radial basis function (RBF) neural network is a kind of supervised non-linear neural network with two main advantages: mathematically simple and computationally cheap. The structure of a typical RBF network has three parts: an input layer, an output layer and a hidden layer. In this study we are interested in the performance of a RBF neural network with respect to hidden layers and arrive at an optimal structure for a RBF network with a fixed number of nodes. Subsurface seismic characterization requires building a relationship (commonly non-linear) between seismic attributes and rock/fluid properties. With such a relationship, the rock/fluid properties computed from well logs can be extended to interwell points. Neural networks are powerful tools to obtain this non-linear relationship. Well logs are separated into two groups, a training group and a test group. Optimized seismic attributes and logs from training group act as inputs and outputs, respectively, to train the RBF network; then the network is deployed to the whole data set and the misfit between the calculated results and the test group is obtained. This overall misfit is utilized to evaluate the performance of networks with different structures. The data we use in this study is a part of the Boonsville 3-D seismic data contributed by the Bureau of Economic Geology of the University of Texas at Austin. Since there are limited numbers of wells with sonic curves, a log prediction using RBF networks is used. A typical single-layer RBF network is used for simplicity. An impedance inversion is applied to constrain the characterization process.
NASA Astrophysics Data System (ADS)
Yan, Qin; Zhong, Yanfei
2008-12-01
The radial basis function (RBF) neural network is a powerful method for remote sensing image classification. It has a simple architecture and the learning algorithm corresponds to the solution of a linear regression problem, resulting in a fast training process. The main drawback of this strategy is the requirement of an efficient algorithm to determine the number, position, and dispersion of the RBF. Traditional methods to determine the centers are: randomly choose input vectors from the training data set; vectors obtained from unsupervised clustering algorithms, such as k-means, applied to the input data. These conduce that traditional RBF neural network is sensitive to the center initialization. In this paper, the artificial immune network (aiNet) model, a new computational intelligence based on artificial immune networks (AIN), is applied to obtain appropriate centers for remote sensing image classification. In the aiNet-RBF algorihtm, each input pattern corresonds to an antigenic stimulus, while each RBF candidate center is considered to be an element, or cell, of the immune network model. The steps are as follows: A set of candidate centers is initialized at random, where the initial number of candidates and their positions is not crucial to the performance. Then, the clonal selection principle will control which candidates will be selected and how they will be upadated. Note that the clonal selection principle will be responsible for how the centers will represent the training data set. Finally, the immune network will identify and eliminate or suppress self-recognizing individuals to control the number of candidate centers. After the above learning phase, the aiNet network centers represent internal images of the inuput patterns presented to it. The algorithm output is taken to be the matrix of memory cells' coordinates that represent the final centers to be adopted by the RBF network. The stopping criterion of the proposed algorithm is given by a pre
Application of Polynomial and Radial Basis Function Maps to Signal Masking
Damiano, B.
1998-01-01
The objective of this research was to develop and demonstrate a technique for encrypting information by using a masking signal that closely approximates local ambient noise. Signal masking techniques developed to date have used nonlinear differential equations, spread spectrum, and various modulation schemes to encode information. While these techniques can effectively hide a signal, the resulting masks may not appear as ambient noise to an observer. The advantage of the proposed technique over commonly used masking methods is that the transmitted signal will appear as normal background noise, thus greatly reducing the probability of detection and exploitation. A promising near-term application of this technology presents itself in the area of clandestine minefield reconnaissance in shallow water areas. Shallow water mine-counter-mine (SWMCM) activity is essential for minefield avoidance, efficient minefield clearance, and effective selection of transit lanes within minefields. A key technology area for SWMCM is the development of special sonar waveforms with low probability of exploitation/intercept (LPE/LPI) attributes. In addition to LPE/LPI sonar, this technology has the potential to enable significant improvements in underwater acoustic communications. For SWMCM, the chaotic waveform research provides a mechanism for encrypted communications between a submarine (SSN) and an unmanned underwater vehicle (UUV) via an acoustic channel. Acoustic SSN/UUV communications would eliminate the need for a fiberoptic link between the two vessels, thus increasing the robustness of SWMCM. Similar applications may exist in the areas of radar masking and secure communications. The original approach called for the use of polynomial maps to generate a masking signal. Because polynomial maps were found to have highly restrictive stability criteria, the approach was modified to use radial basis function (RBF) maps. they have shown that stable RBF maps that closely approximate an
Oyang, Yen-Jen; Hwang, Shien-Ching; Ou, Yu-Yen; Chen, Chien-Yu; Chen, Zhi-Wei
2005-01-01
This paper presents a novel learning algorithm for efficient construction of the radial basis function (RBF) networks that can deliver the same level of accuracy as the support vector machines (SVMs) in data classification applications. The proposed learning algorithm works by constructing one RBF subnetwork to approximate the probability density function of each class of objects in the training data set. With respect to algorithm design, the main distinction of the proposed learning algorithm is the novel kernel density estimation algorithm that features an average time complexity of O(n log n), where n is the number of samples in the training data set. One important advantage of the proposed learning algorithm, in comparison with the SVM, is that the proposed learning algorithm generally takes far less time to construct a data classifier with an optimized parameter setting. This feature is of significance for many contemporary applications, in particular, for those applications in which new objects are continuously added into an already large database. Another desirable feature of the proposed learning algorithm is that the RBF networks constructed are capable of carrying out data classification with more than two classes of objects in one single run. In other words, unlike with the SVM, there is no need to resort to mechanisms such as one-against-one or one-against-all for handling datasets with more than two classes of objects. The comparison with SVM is of particular interest, because it has been shown in a number of recent studies that SVM generally are able to deliver higher classification accuracy than the other existing data classification algorithms. As the proposed learning algorithm is instance-based, the data reduction issue is also addressed in this paper. One interesting observation in this regard is that, for all three data sets used in data reduction experiments, the number of training samples remaining after a naive data reduction mechanism is
Liu, Yan; Lu, Chengyu; Meng, Qingfan; Lu, Jiahui; Fu, Yao; Liu, Botong; Zhou, Yongcan; Guo, Weiliang; Teng, Lesheng
2015-01-01
In our previous work, partial least squares (PLSs) were employed to develop the near infrared spectroscopy (NIRs) models for at-line (fast off-line) monitoring key parameters of Lactococcus lactis subsp. fermentation. In this study, radial basis function neural network (RBFNN) as a non-linear modeling method was investigated to develop NIRs models instead of PLS. A method named moving window radial basis function neural network (MWRBFNN) was applied to select the characteristic wavelength variables by using the degree approximation (Da) as criterion. Next, the RBFNN models with selected wavelength variables were optimized by selecting a suitable constant spread. Finally, the effective spectra pretreatment methods were selected by comparing the robustness of the optimum RBFNN models developed with pretreated spectra. The results demonstrated that the robustness of the optimal RBFNN models were better than the PLS models for at-line monitoring of glucose and pH of L. lactis subsp. fermentation. PMID:26858554
Gonzalez, J; Rojas, I; Ortega, J; Pomares, H; Fernandez, F J; Diaz, A F
2003-01-01
This paper presents a multiobjective evolutionary algorithm to optimize radial basis function neural networks (RBFNNs) in order to approach target functions from a set of input-output pairs. The procedure allows the application of heuristics to improve the solution of the problem at hand by including some new genetic operators in the evolutionary process. These new operators are based on two well-known matrix transformations: singular value decomposition (SVD) and orthogonal least squares (OLS), which have been used to define new mutation operators that produce local or global modifications in the radial basis functions (RBFs) of the networks (the individuals in the population in the evolutionary procedure). After analyzing the efficiency of the different operators, we have shown that the global mutation operators yield an improved procedure to adjust the parameters of the RBFNNs.
NASA Technical Reports Server (NTRS)
Krishnamurthy, Thiagarajan
2005-01-01
Response construction methods using Moving Least Squares (MLS), Kriging and Radial Basis Functions (RBF) are compared with the Global Least Squares (GLS) method in three numerical examples for derivative generation capability. Also, a new Interpolating Moving Least Squares (IMLS) method adopted from the meshless method is presented. It is found that the response surface construction methods using the Kriging and RBF interpolation yields more accurate results compared with MLS and GLS methods. Several computational aspects of the response surface construction methods also discussed.
NASA Astrophysics Data System (ADS)
Paranin, Vyacheslav D.; Karpeev, Sergey V.; Khonina, Svetlana N.
2016-03-01
The calculation and simulation of interference polarizer to generate radially polarized light is made. The method is based on converting the conical wavefront passing through the interference polarizer. The multilayer optical coating can be applied on the surface of the axicon. It is shown that in this way we noticeably reduce both the operating angle of incidence and achieve practically significant degree of polarization of the beam generated at much lower energy losses.
The Molecular Basis of Radial Intercalation during Tissue Spreading in Early Development
Szabó, András; Cobo, Isidoro; Omara, Sharif; McLachlan, Sophie; Keller, Ray; Mayor, Roberto
2016-01-01
Summary Radial intercalation is a fundamental process responsible for the thinning of multilayered tissues during large-scale morphogenesis; however, its molecular mechanism has remained elusive. Using amphibian epiboly, the thinning and spreading of the animal hemisphere during gastrulation, here we provide evidence that radial intercalation is driven by chemotaxis of cells toward the external layer of the tissue. This role of chemotaxis in tissue spreading and thinning is unlike its typical role associated with large-distance directional movement of cells. We identify the chemoattractant as the complement component C3a, a factor normally linked with the immune system. The mechanism is explored by computational modeling and tested in vivo, ex vivo, and in vitro. This mechanism is robust against fluctuations of chemoattractant levels and expression patterns and explains expansion during epiboly. This study provides insight into the fundamental process of radial intercalation and could be applied to a wide range of morphogenetic events. PMID:27165554
NASA Astrophysics Data System (ADS)
Zabihi, F.; Saffarian, M.
2016-07-01
The aim of this article is to obtain the numerical solution of the two-dimensional KdV-Burgers equation. We construct the solution by using a different approach, that is based on using collocation points. The solution is based on using the thin plate splines radial basis function, which builds an approximated solution with discretizing the time and the space to small steps. We use a predictor-corrector scheme to avoid solving the nonlinear system. The results of numerical experiments are compared with analytical solutions to confirm the accuracy and efficiency of the presented scheme.
Cho, Baek Hwan; Yu, Hwanjo; Lee, Jongshill; Chee, Young Joon; Kim, In Young; Kim, Sun I
2008-03-01
Nonlinear classifiers, e.g., support vector machines (SVMs) with radial basis function (RBF) kernels, have been used widely for automatic diagnosis of diseases because of their high accuracies. However, it is difficult to visualize the classifiers, and thus difficult to provide intuitive interpretation of results to physicians. We developed a new nonlinear kernel, the localized radial basis function (LRBF) kernel, and new visualization system visualization for risk factor analysis (VRIFA) that applies a nomogram and LRBF kernel to visualize the results of nonlinear SVMs and improve the interpretability of results while maintaining high prediction accuracy. Three representative medical datasets from the University of California, Irvine repository and Statlog dataset-breast cancer, diabetes, and heart disease datasets-were used to evaluate the system. The results showed that the classification performance of the LRBF is comparable with that of the RBF, and the LRBF is easy to visualize via a nomogram. Our study also showed that the LRBF kernel is less sensitive to noise features than the RBF kernel, whereas the LRBF kernel degrades the prediction accuracy more when important features are eliminated. We demonstrated the VRIFA system, which visualizes the results of linear and nonlinear SVMs with LRBF kernels, on the three datasets. PMID:18348954
The neural basis of conceptualizing the same action at different levels of abstraction.
Spunt, Robert P; Kemmerer, David; Adolphs, Ralph
2016-07-01
People can conceptualize the same action (e.g. 'riding a bike') at different levels of abstraction (LOA), where higher LOAs specify the abstract motives that explain why the action is performed (e.g. 'getting exercise'), while lower LOAs specify the concrete steps that indicate how the action is performed (e.g. 'gripping handlebars'). Prior neuroimaging studies have shown that why and how questions about actions differentially activate two cortical networks associated with mental-state reasoning and action representation, respectively; however, it remains unknown whether this is due to the differential demands of the questions per se or to the shifts in LOA those questions produce. We conducted functional magnetic resonance imaging while participants judged pairs of action phrases that varied in LOA and that could be framed either as a why question (Why ride a bike? Get exercise.) or a how question (How to get exercise? Ride a bike.). Question framing (why vs how) had no effect on activity in regions of the two networks. Instead, these regions uniquely tracked parametric variation in LOA, both across and within trials. This suggests that the human capacity to understand actions at different LOA is based in the relative activity of two cortical networks. PMID:26117505
The neural basis of conceptualizing the same action at different levels of abstraction.
Spunt, Robert P; Kemmerer, David; Adolphs, Ralph
2016-07-01
People can conceptualize the same action (e.g. 'riding a bike') at different levels of abstraction (LOA), where higher LOAs specify the abstract motives that explain why the action is performed (e.g. 'getting exercise'), while lower LOAs specify the concrete steps that indicate how the action is performed (e.g. 'gripping handlebars'). Prior neuroimaging studies have shown that why and how questions about actions differentially activate two cortical networks associated with mental-state reasoning and action representation, respectively; however, it remains unknown whether this is due to the differential demands of the questions per se or to the shifts in LOA those questions produce. We conducted functional magnetic resonance imaging while participants judged pairs of action phrases that varied in LOA and that could be framed either as a why question (Why ride a bike? Get exercise.) or a how question (How to get exercise? Ride a bike.). Question framing (why vs how) had no effect on activity in regions of the two networks. Instead, these regions uniquely tracked parametric variation in LOA, both across and within trials. This suggests that the human capacity to understand actions at different LOA is based in the relative activity of two cortical networks.
Li, Meina; Kwak, Keun-Chang; Kim, Youn Tae
2016-09-22
Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model.
Zhang, Peng; Liu, Keping; Zhao, Bo; Li, Yuanchun
2015-01-01
Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN) is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP). Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm. PMID:26367382
Zhang, Peng; Liu, Keping; Zhao, Bo; Li, Yuanchun
2015-01-01
Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN) is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP). Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm.
Zhang, Peng; Liu, Keping; Zhao, Bo; Li, Yuanchun
2015-01-01
Optimal guidance is essential for the soft landing task. However, due to its high computational complexities, it is hardly applied to the autonomous guidance. In this paper, a computationally inexpensive optimal guidance algorithm based on the radial basis function neural network (RBFNN) is proposed. The optimization problem of the trajectory for soft landing on asteroids is formulated and transformed into a two-point boundary value problem (TPBVP). Combining the database of initial states with the relative initial co-states, an RBFNN is trained offline. The optimal trajectory of the soft landing is determined rapidly by applying the trained network in the online guidance. The Monte Carlo simulations of soft landing on the Eros433 are performed to demonstrate the effectiveness of the proposed guidance algorithm. PMID:26367382
Li, Meina; Kwak, Keun-Chang; Kim, Youn Tae
2016-01-01
Conventionally, indirect calorimetry has been used to estimate oxygen consumption in an effort to accurately measure human body energy expenditure. However, calorimetry requires the subject to wear a mask that is neither convenient nor comfortable. The purpose of our study is to develop a patch-type sensor module with an embedded incremental radial basis function neural network (RBFNN) for estimating the energy expenditure. The sensor module contains one ECG electrode and a three-axis accelerometer, and can perform real-time heart rate (HR) and movement index (MI) monitoring. The embedded incremental network includes linear regression (LR) and RBFNN based on context-based fuzzy c-means (CFCM) clustering. This incremental network is constructed by building a collection of information granules through CFCM clustering that is guided by the distribution of error of the linear part of the LR model. PMID:27669249
Albrecht, S; Busch, J; Kloppenburg, M; Metze, F; Tavan, P
2000-12-01
By adding reverse connections from the output layer to the central layer it is shown how a generalized radial basis functions (GRBF) network can self-organize to form a Bayesian classifier, which is also capable of novelty detection. For this purpose, three stochastic sequential learning rules are introduced from biological considerations which pertain to the centers, the shapes, and the widths of the receptive fields of the neurons and allow ajoint optimization of all network parameters. The rules are shown to generate maximum-likelihood estimates of the class-conditional probability density functions of labeled data in terms of multivariate normal mixtures. Upon combination with a hierarchy of deterministic annealing procedures, which implement a multiple-scale approach, the learning process can avoid the convergence problems hampering conventional expectation-maximization algorithms. Using an example from the field of speech recognition, the stages of the learning process and the capabilities of the self-organizing GRBF classifier are illustrated.
NASA Astrophysics Data System (ADS)
Dou, Ying; Mi, Hong; Zhao, Lingzhi; Ren, Yuqiu; Ren, Yulin
2006-09-01
The application of the second most popular artificial neural networks (ANNs), namely, the radial basis function (RBF) networks, has been developed for quantitative analysis of drugs during the last decade. In this paper, the two components (aspirin and phenacetin) were simultaneously determined in compound aspirin tablets by using near-infrared (NIR) spectroscopy and RBF networks. The total database was randomly divided into a training set (50) and a testing set (17). Different preprocessing methods (standard normal variate (SNV), multiplicative scatter correction (MSC), first-derivative and second-derivative) were applied to two sets of NIR spectra of compound aspirin tablets with different concentrations of two active components and compared each other. After that, the performance of RBF learning algorithm adopted the nearest neighbor clustering algorithm (NNCA) and the criterion for selection used a cross-validation technique. Results show that using RBF networks to quantificationally analyze tablets is reliable, and the best RBF model was obtained by first-derivative spectra.
NASA Astrophysics Data System (ADS)
Dai, Xiangjun; Shao, Xinxing; Yang, Fujun; Yun, Hai
2016-06-01
In-plane electronic speckle pattern interferometry (ESPI) was developed to determine the thickness uniformity of a transparent film. The method is based on the subsequent spatial carrier patterns caused by the change of the rotation angle. Full-field thickness distribution can be obtained according to the relation between the phase difference and optical path difference generated by film rotation. Moreover, radial basis function was applied to improve the image quality of interference patterns. The main principle and experimental procedure of the method were presented. The errors of measurement results were analyzed. It is shown that the thickness uniformity of the thin film can be measured rapidly and accurately. Also, the refractive index can be determined by the developed method simultaneously.
Use of Structure as a Basis for Abstraction in Air Traffic Control
NASA Technical Reports Server (NTRS)
Davison, Hayley J.; Hansman, R. John
2004-01-01
The safety and efficiency of the air traffic control domain is highly dependent on the capabilities and limitations of its human controllers. Past research has indicated that structure provided by the airspace and procedures could aid in simplifying the controllers cognitive tasks. In this paper, observations, interviews, voice command data analyses, and radar analyses were conducted at the Boston Terminal Route Control (TRACON) facility to determine if there was evidence of controllers using structure to simplify their cognitive processes. The data suggest that controllers do use structure-based abstractions to simplify their cognitive processes, particularly the projection task. How structure simplifies the projection task and the implications of understanding the benefits structure provides to the projection task was discussed.
NASA Astrophysics Data System (ADS)
Edmondson, Richard; Rodgers, Michael
2008-04-01
Using matched filters to find targets in cluttered images is an old idea. Human operators can interactively find threshold values to be applied to the correlation surface that will do a good job of binarizing it into signal/non-signal pixel regions. Automating the thresholding process with nine measured image statistics is the goal of this paper. The nine values are the mean, maximum, and standard deviation of three images: the input image presumed to have some signal, an NxN matched filter kernel in the shape of the signal, and the correlation surface generated by convolving the input image with the matched filter kernel. Several thousand input images with known target locations and reference images were run through a correlator with kernels that resembled the targets. The nine numbers referred to above were calculated in addition to a threshold found with a time consuming brutal algorithm. Multidimensional radial basis functions were associated with each nine number set. The bump height corresponded to the threshold value. The bump location was within a nine dimensional hypercube corresponding to the nine numbers scaled so that all the data fell within the interval 0 to 1 on each axis. The sigma (sharpness of the radial basis function) was calculated as a fraction of the squared distance to the closest neighboring bump. A new threshold is calculated as a weighted sum of all the Gaussian bumps in the vicinity of the input 9D vector. The paper will conclude with a table of results using this method compared to other methods.
NASA Astrophysics Data System (ADS)
Dalmasse, Kevin; Nychka, Douglas; Gibson, Sarah; Flyer, Natasha; Fan, Yuhong
2016-07-01
The Coronal Multichannel Polarimeter (CoMP) routinely performs coronal polarimetric measurements using the Fe XIII 10747 Å and 10798 Å lines, which are sensitive to the coronal magnetic field. However, inverting such polarimetric measurements into magnetic field data is a difficult task because the corona is optically thin at these wavelengths and the observed signal is therefore the integrated emission of all the plasma along the line of sight. To overcome this difficulty, we take on a new approach that combines a parameterized 3D magnetic field model with forward modeling of the polarization signal. For that purpose, we develop a new, fast and efficient, optimization method for model-data fitting: the Radial-basis-functions Optimization Approximation Method (ROAM). Model-data fitting is achieved by optimizing a user-specified log-likelihood function that quantifies the differences between the observed polarization signal and its synthetic/predicted analogue. Speed and efficiency are obtained by combining sparse evaluation of the magnetic model with radial-basis-function (RBF) decomposition of the log-likelihood function. The RBF decomposition provides an analytical expression for the log-likelihood function that is used to inexpensively estimate the set of parameter values optimizing it. We test and validate ROAM on a synthetic test bed of a coronal magnetic flux rope and show that it performs well with a significantly sparse sample of the parameter space. We conclude that our optimization method is well-suited for fast and efficient model-data fitting and can be exploited for converting coronal polarimetric measurements, such as the ones provided by CoMP, into coronal magnetic field data.
NASA Astrophysics Data System (ADS)
Tyan, Maxim; Van Nguyen, Nhu; Lee, Jae-Woo
2015-07-01
The global variable-fidelity modelling (GVFM) method presented in this article extends the original variable-complexity modelling (VCM) algorithm that uses a low-fidelity and scaling function to approximate a high-fidelity function for efficiently solving design-optimization problems. GVFM uses the design of experiments to sample values of high- and low-fidelity functions to explore global design space and to initialize a scaling function using the radial basis function (RBF) network. This approach makes it possible to remove high-fidelity-gradient evaluation from the process, which makes GVFM more efficient than VCM for high-dimensional design problems. The proposed algorithm converges with 65% fewer high-fidelity function calls for a one-dimensional problem than VCM and approximately 80% fewer for a two-dimensional numerical problem. The GVFM method is applied for the design optimization of transonic and subsonic aerofoils. Both aerofoil design problems show design improvement with a reasonable number of high- and low-fidelity function evaluations.
NASA Astrophysics Data System (ADS)
Ayala, Helon Vicente Hultmann; Coelho, Leandro dos Santos
2016-02-01
The present work introduces a procedure for input selection and parameter estimation for system identification based on Radial Basis Functions Neural Networks (RBFNNs) models with an improved objective function based on the residuals and its correlation function coefficients. We show the results when the proposed methodology is applied to model a magnetorheological damper, with real acquired data, and other two well-known benchmarks. The canonical genetic and differential evolution algorithms are used in cascade to decompose the problem of defining the lags taken as the inputs of the model and its related parameters based on the simultaneous minimization of the residuals and higher orders correlation functions. The inner layer of the cascaded approach is composed of a population which represents the lags on the inputs and outputs of the system and an outer layer represents the corresponding parameters of the RBFNN. The approach is able to define both the inputs of the model and its parameters. This is interesting as it frees the designer of manual procedures, which are time consuming and prone to error, usually done to define the model inputs. We compare the proposed methodology with other works found in the literature, showing overall better results for the cascaded approach.
Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M
2016-01-01
This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF-FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model's performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF-FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF-FFA model can be applied as an efficient technique for the accurate prediction of vertical handover. PMID:27438600
Ebtehaj, Isa; Bonakdari, Hossein; Zaji, Amir Hossein
2016-01-01
In this study, an expert system with a radial basis function neural network (RBF-NN) based on decision trees (DT) is designed to predict sediment transport in sewer pipes at the limit of deposition. First, sensitivity analysis is carried out to investigate the effect of each parameter on predicting the densimetric Froude number (Fr). The results indicate that utilizing the ratio of the median particle diameter to pipe diameter (d/D), ratio of median particle diameter to hydraulic radius (d/R) and volumetric sediment concentration (C(V)) as the input combination leads to the best Fr prediction. Subsequently, the new hybrid DT-RBF method is presented. The results of DT-RBF are compared with RBF and RBF-particle swarm optimization (PSO), which uses PSO for RBF training. It appears that DT-RBF is more accurate (R(2) = 0.934, MARE = 0.103, RMSE = 0.527, SI = 0.13, BIAS = -0.071) than the two other RBF methods. Moreover, the proposed DT-RBF model offers explicit expressions for use by practicing engineers. PMID:27386995
Liu, Haiqing; Yang, Linghui; Guo, Yin; Guan, Ruifen; Zhu, Jigui
2015-02-01
The linear camera equipped with cylindrical lenses has prominent advantages in high-precision coordinate measurement and dynamic position-tracking. However, the serious distortion of the cylindrical lenses limits the application of this camera. To overcome this obstacle, a precise two-step calibration method is developed. In the first step, a radial basis function-based (RBF-based) mapping technique is employed to recover the projection mapping of the imaging system by interpolating the correspondence between incident rays and image points. For an object point in 3D space, the plane passing through the object point in camera coordinate frame can be calculated accurately by this technique. The second step is the calibration of extrinsic parameters, which realizes the coordinate transformation from the camera coordinate frame to world coordinate frame. The proposed method has three aspects of advantage. Firstly, this method (black box calibration) is still effective even if the distortion is high and asymmetric. Secondly, the coupling between extrinsic parameters and other parameters, which is normally occurred and may lead to the failure of calibration, is avoided because this method simplifies the pinhole model and only extrinsic parameters are concerned in the simplified model. Thirdly, the nonlinear optimization, which is widely used to refine camera parameters, is better conditioned since fewer parameters are needed and more accurate initial iteration value is estimated. Both simulative and real experiments have been carried out and good results have been obtained.
NASA Astrophysics Data System (ADS)
Rai, H. M.; Trivedi, A.; Chatterjee, K.; Shukla, S.
2014-01-01
This paper employed the Daubechies wavelet transform (WT) for R-peak detection and radial basis function neural network (RBFNN) to classify the electrocardiogram (ECG) signals. Five types of ECG beats: normal beat, paced beat, left bundle branch block (LBBB) beat, right bundle branch block (RBBB) beat and premature ventricular contraction (PVC) were classified. 500 QRS complexes were arbitrarily extracted from 26 records in Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database, which are available on Physionet website. Each and every QRS complex was represented by 21 points from p1 to p21 and these QRS complexes of each record were categorized according to types of beats. The system performance was computed using four types of parameter evaluation metrics: sensitivity, positive predictivity, specificity and classification error rate. The experimental result shows that the average values of sensitivity, positive predictivity, specificity and classification error rate are 99.8%, 99.60%, 99.90% and 0.12%, respectively with RBFNN classifier. The overall accuracy achieved for back propagation neural network (BPNN), multilayered perceptron (MLP), support vector machine (SVM) and RBFNN classifiers are 97.2%, 98.8%, 99% and 99.6%, respectively. The accuracy levels and processing time of RBFNN is higher than or comparable with BPNN, MLP and SVM classifiers.
NASA Astrophysics Data System (ADS)
Yan, Zhi-zhong; Wei, Chun-qiu; Zheng, Hui; Zhang, Chuanzeng
2016-05-01
In this paper, a meshless radial basis function (RBF) collocation method is developed to calculate the phononic band structures taking account of different interface models. The present method is validated by using the analytical results in the case of perfect interfaces. The stability is fully discussed based on the types of RBFs, the shape parameters and the node numbers. And the advantages of the proposed RBF method compared to the finite element method (FEM) are also illustrated. In addition, the influences of the spring-interface model and the three-phase model on the wave band gaps are investigated by comparing with the perfect interfaces. For different interface models, the effects of various interface conditions, length ratios and density ratios on the band gap width are analyzed. The comparison results of the two models show that the weakly bonded interface has a significant effect on the properties of phononic crystals. Besides, the band structures of the spring-interface model have certain similarities and differences with those of the three-phase model.
Lee, S; Pan, J J
1996-01-01
This paper presents a new approach to representation and recognition of handwritten numerals. The approach first transforms a two-dimensional (2-D) spatial representation of a numeral into a three-dimensional (3-D) spatio-temporal representation by identifying the tracing sequence based on a set of heuristic rules acting as transformation operators. A multiresolution critical-point segmentation method is then proposed to extract local feature points, at varying degrees of scale and coarseness. A new neural network architecture, referred to as radial-basis competitive and cooperative network (RCCN), is presented especially for handwritten numeral recognition. RCCN is a globally competitive and locally cooperative network with the capability of self-organizing hidden units to progressively achieve desired network performance, and functions as a universal approximator of arbitrary input-output mappings. Three types of RCCNs are explored: input-space RCCN (IRCCN), output-space RCCN (ORCCN), and bidirectional RCCN (BRCCN). Experiments against handwritten zip code numerals acquired by the U.S. Postal Service indicated that the proposed method is robust in terms of variations, deformations, transformations, and corruption, achieving about 97% recognition rate.
NASA Astrophysics Data System (ADS)
Oh, Sung-Kwun; Kim, Wook-Dong; Pedrycz, Witold
2016-05-01
In this paper, we introduce a new architecture of optimized Radial Basis Function neural network classifier developed with the aid of fuzzy clustering and data preprocessing techniques and discuss its comprehensive design methodology. In the preprocessing part, the Linear Discriminant Analysis (LDA) or Principal Component Analysis (PCA) algorithm forms a front end of the network. The transformed data produced here are used as the inputs of the network. In the premise part, the Fuzzy C-Means (FCM) algorithm determines the receptive field associated with the condition part of the rules. The connection weights of the classifier are of functional nature and come as polynomial functions forming the consequent part. The Particle Swarm Optimization algorithm optimizes a number of essential parameters needed to improve the accuracy of the classifier. Those optimized parameters include the type of data preprocessing, the dimensionality of the feature vectors produced by the LDA (or PCA), the number of clusters (rules), the fuzzification coefficient used in the FCM algorithm and the orders of the polynomials of networks. The performance of the proposed classifier is reported for several benchmarking data-sets and is compared with the performance of other classifiers reported in the previous studies.
NASA Astrophysics Data System (ADS)
Meng, Qinggang; Lee, M. H.
2007-03-01
Advanced autonomous artificial systems will need incremental learning and adaptive abilities similar to those seen in humans. Knowledge from biology, psychology and neuroscience is now inspiring new approaches for systems that have sensory-motor capabilities and operate in complex environments. Eye/hand coordination is an important cross-modal cognitive function, and is also typical of many of the other coordinations that must be involved in the control and operation of embodied intelligent systems. This paper examines a biologically inspired approach for incrementally constructing compact mapping networks for eye/hand coordination. We present a simplified node-decoupled extended Kalman filter for radial basis function networks, and compare this with other learning algorithms. An experimental system consisting of a robot arm and a pan-and-tilt head with a colour camera is used to produce results and test the algorithms in this paper. We also present three approaches for adapting to structural changes during eye/hand coordination tasks, and the robustness of the algorithms under noise are investigated. The learning and adaptation approaches in this paper have similarities with current ideas about neural growth in the brains of humans and animals during tool-use, and infants during early cognitive development.
NASA Astrophysics Data System (ADS)
Ai, Yuewei; Shao, Xinyu; Jiang, Ping; Li, Peigen; Liu, Yang; Yue, Chen
2015-11-01
The welded joints of dissimilar materials have been widely used in automotive, ship and space industries. The joint quality is often evaluated by weld seam geometry, microstructures and mechanical properties. To obtain the desired weld seam geometry and improve the quality of welded joints, this paper proposes a process modeling and parameter optimization method to obtain the weld seam with minimum width and desired depth of penetration for laser butt welding of dissimilar materials. During the process, Taguchi experiments are conducted on the laser welding of the low carbon steel (Q235) and stainless steel (SUS301L-HT). The experimental results are used to develop the radial basis function neural network model, and the process parameters are optimized by genetic algorithm. The proposed method is validated by a confirmation experiment. Simultaneously, the microstructures and mechanical properties of the weld seam generated from optimal process parameters are further studied by optical microscopy and tensile strength test. Compared with the unoptimized weld seam, the welding defects are eliminated in the optimized weld seam and the mechanical properties are improved. The results show that the proposed method is effective and reliable for improving the quality of welded joints in practical production.
Goudarzi, Shidrokh; Haslina Hassan, Wan; Abdalla Hashim, Aisha-Hassan; Soleymani, Seyed Ahmad; Anisi, Mohammad Hossein; Zakaria, Omar M.
2016-01-01
This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover. PMID:27438600
Casadio, R; Compiani, M; Fariselli, P; Vivarelli, F
1995-01-01
Radial basis function neural networks are trained on a data base comprising 38 globular proteins of well resolved crystallographic structure and the corresponding free energy contributions to the overall protein stability (as computed partially from chrystallographic analysis and partially with multiple regression from experimental thermodynamic data by Ponnuswamy and Gromiha (1994)). Starting from the residue sequence and using as input code the percentage of each residue and the total residue number of the protein, it is found with a cross-validation method that neural networks can optimally predict the free energy contributions due to hydrogen bonds, hydrophobic interactions and the unfolded state. Terms due to electrostatic and disulfide bonding free energies are poorly predicted. This is so also when other input codes, including the percentage of secondary structure type of the protein and/or residue-pair information are used. Furthermore, trained on the computed and/or experimental delta G values of the data base, neural networks predict a conformational stability ranging from about 10 to 20 kcal mol-1 rather independently of the residue sequence, with an average error per protein of about 9 kcal mol-1.
Kuo, R J.; Cohen, P H.
1999-03-01
On-line tool wear estimation plays a very critical role in industry automation for higher productivity and product quality. In addition, appropriate and timely decision for tool change is significantly required in the machining systems. Thus, this paper is dedicated to develop an estimation system through integration of two promising technologies, artificial neural networks (ANN) and fuzzy logic. An on-line estimation system consisting of five components: (1) data collection; (2) feature extraction; (3) pattern recognition; (4) multi-sensor integration; and (5) tool/work distance compensation for tool flank wear, is proposed herein. For each sensor, a radial basis function (RBF) network is employed to recognize the extracted features. Thereafter, the decisions from multiple sensors are integrated through a proposed fuzzy neural network (FNN) model. Such a model is self-organizing and self-adjusting, and is able to learn from the experience. Physical experiments for the metal cutting process are implemented to evaluate the proposed system. The results show that the proposed system can significantly increase the accuracy of the product profile.
Adetiba, Emmanuel; Olugbara, Oludayo O.
2015-01-01
Lung cancer is one of the diseases responsible for a large number of cancer related death cases worldwide. The recommended standard for screening and early detection of lung cancer is the low dose computed tomography. However, many patients diagnosed die within one year, which makes it essential to find alternative approaches for screening and early detection of lung cancer. We present computational methods that can be implemented in a functional multi-genomic system for classification, screening and early detection of lung cancer victims. Samples of top ten biomarker genes previously reported to have the highest frequency of lung cancer mutations and sequences of normal biomarker genes were respectively collected from the COSMIC and NCBI databases to validate the computational methods. Experiments were performed based on the combinations of Z-curve and tetrahedron affine transforms, Histogram of Oriented Gradient (HOG), Multilayer perceptron and Gaussian Radial Basis Function (RBF) neural networks to obtain an appropriate combination of computational methods to achieve improved classification of lung cancer biomarker genes. Results show that a combination of affine transforms of Voss representation, HOG genomic features and Gaussian RBF neural network perceptibly improves classification accuracy, specificity and sensitivity of lung cancer biomarker genes as well as achieving low mean square error. PMID:26625358
Ou, Yu-Yen; Chen, Shu-An; Gromiha, M Michael
2010-05-15
Transporters are proteins that are involved in the movement of ions or molecules across biological membranes. Transporters are generally classified into channels/pores, electrochemical transporters, and active transporters. Discriminating the specific class of transporters and their subfamilies are essential tasks in computational biology for the advancement of structural and functional genomics. We have systematically analyzed the amino acid composition, residue pair preference and amino acid properties in six different families of transporters. Utilizing the information, we have developed a radial basis function (RBF) network method based on profiles obtained with position specific scoring matrices for discriminating transporters belonging to three different classes and six families. Our method showed a fivefold cross validation accuracy of 76%, 73%, and 69% for discriminating transporters and nontransporters, three different classes and six different families of transporters, respectively. Further, the method was tested with independent datasets, which showed similar level of accuracy. A web server has been developed for discriminating transporters based on three classes and six families, and it is available at http://rbf.bioinfo.tw/ approximately sachen/tcrbf.html. We suggest that our method could be effectively used to identify transporters and discriminating them into different classes and families.
Ou, Yu-Yen; Chen, Shu-An; Chang, Yun-Min; Velmurugan, Devadasan; Fukui, Kazuhiko; Michael Gromiha, M
2013-09-01
Efflux proteins are membrane proteins, which are involved in the transportation of multidrugs. The annotation of efflux proteins in genomic sequences would aid to understand the function. Although the percentage of membrane proteins in genomes is estimated to be 25-30%, there is no information about the content of efflux proteins. For annotating such class of proteins it is necessary to develop a reliable method to identify efflux proteins from amino acid sequence information. In this work, we have developed a method based on radial basis function networks using position specific scoring matrices (PSSM) and amino acid properties. We noticed that the C-terminal domain of efflux proteins contain vital information for discrimination. Our method showed an accuracy of 78 and 92% in discriminating efflux proteins from transporters and membrane proteins, respectively using fivefold cross-validation. We utilized our method for annotating the genomes E. coli and P. aeruginosa and it predicted 8.7 and 9.2% of proteins as efflux proteins in these genomes, respectively. The predicted efflux proteins have been compared with available experimental data and we observed a very good agreement between them. Further, we developed a web server for classifying efflux proteins and it is freely available at http://rbf.bioinfo.tw/∼sachen/EFFLUXpredict/Efflux-RBF.php. We suggest that our method could be an effective tool for annotating efflux proteins in genomic sequences.
Mahdi, Rami N.; Rouchka, Eric C.
2009-01-01
Accurate identification of promoter regions and transcription start sites (TSS) in genomic DNA allows for a more complete understanding of the structure of genes and gene regulation within a given genome. Many recently published methods have achieved high identification accuracy of TSS. However, models providing more accurate modeling of promoters and TSS are needed. A novel identification method for identifying transcription start sites that improves the accuracy of TSS recognition for recently published methods is proposed. This method incorporates a metric feature based on oligonucleotide positional frequencies, taking into account the nature of promoters. A radial basis function neural network for identifying transcription start sites (RBF-TSS) is proposed and employed as a classification algorithm. Using non-overlapping chunks (windows) of size 50 and 500 on the human genome, the proposed method achieves an area under the Receiver Operator Characteristic curve (auROC) of 94.75% and 95.08% respectively, providing increased performance over existing TSS prediction methods. PMID:19287502
Qiu, Wei; Chang, Chunqi; Liu, Wenqing; Poon, Paul W F; Hu, Yong; Lam, F K; Hamernik, Roger P; Wei, Gang; Chan, Francis H Y
2006-02-01
Tracking variations in both the latency and amplitude of evoked potential (EP) is important in quantifying properties of the nervous system. Adaptive filtering is a powerful tool for tracking such variations. In this paper, a data-reusing non-linear adaptive filtering method, based on a radial basis function network (RBFN), is implemented to estimate EP. The RBFN consists of an input layer of source nodes, a single hidden layer of non-linear processing units and an output layer of linear weights. It has built-in nonlinear activation functions that allow learning of function mappings. Moreover, it produces satisfactory estimates of signals against a background noise without a priori knowledge of the signal, provided that the signal and noise are independent. In clinical situations where EP responses change rapidly, the convergence rate of the algorithm becomes a critical factor. A carefully designed data-reusing RBFN can accelerate the convergence rate markedly and, thus, enhance its performance. Both theoretical analysis and simulation results support the improved performance of our new algorithm. PMID:16485751
Qiao, Jun-Fei; Han, Hong-Gui
2010-02-01
This paper presents a repair algorithm for the design of a Radial Basis Function (RBF) neural network. The proposed repair RBF (RRBF) algorithm starts from a single prototype randomly initialized in the feature space. The algorithm has two main phases: an architecture learning phase and a parameter adjustment phase. The architecture learning phase uses a repair strategy based on a sensitivity analysis (SA) of the network's output to judge when and where hidden nodes should be added to the network. New nodes are added to repair the architecture when the prototype does not meet the requirements. The parameter adjustment phase uses an adjustment strategy where the capabilities of the network are improved by modifying all the weights. The algorithm is applied to two application areas: approximating a non-linear function, and modeling the key parameter, chemical oxygen demand (COD) used in the waste water treatment process. The results of simulation show that the algorithm provides an efficient solution to both problems. PMID:20180254
ERIC Educational Resources Information Center
Meghabghab, George
2001-01-01
Discusses the evaluation of search engines and uses neural networks in stochastic simulation of the number of rejected Web pages per search query. Topics include the iterative radial basis functions (RBF) neural network; precision; response time; coverage; Boolean logic; regression models; crawling algorithms; and implications for search engine…
Zhu, Guocheng; Zheng, Huaili; Zhang, Peng; Jiao, Zhaojie; Yin, Jun
2013-01-01
Poly(acrylamide-co-diallyldimethylammonium chloride) (PDA), which is usually prepared by free radical polymerization of acrylamide monomer (AM) onto the cationic monomer dimethyl diallyl ammonium chloride (DMDAAC), has been widely applied to wastewater treatment; however, the free-radical polymerization is always incomplete with residual AM remaining in the PDA. The residual AM affects the PDA's performance while also posing as a potential threat to human health; therefore, during preparation of the PDA, the rapid detection of the residual AM plays an important role in controlling the residual AM while improving the PDA's performance. The objective of this study was to explore the possibilities for applying near-infrared (NIR) spectroscopy as a potential tool for detecting the residual AM in combination with a statistical tool. In this study, the radial basis function (RBF) network model as the statistical tool was combined with NIR spectroscopy for detection of the residual AM. The experimental results showed that five wavelengths in the NIR spectroscopy were the most important characteristic adsorption peaks, particular at 971.95 and 1077 nm. The simulation of the RBF model presented higher performance with R2-value greater than 0.98, RMSEC and RMSEP less than 7.22 x 10(-5) and coefficient of variation (CV) of the predicted residual AM less than 10%, which demonstrated the feasibility of the NIR spectroscopy being a rapid detection tool for prediction of the residual AM using the RBF model. Wavelet de-nosing was used for removing the interference/noise in the NIR spectroscopy and improved the generalization ability of the RBF model.
Prediction of fMRI time series of a single voxel using radial basis function neural network
NASA Astrophysics Data System (ADS)
Song, Sutao; Zhang, Jiacai; Yao, Li
2011-03-01
A great deal of current literature regarding functional neuroimaging has elucidated the relationships of neurons distributed all over the brain. Modern neuroimaging techniques, such as the functional MRI (fMRI), provide a convenient tool for people to study the correlation among different voxels as well as the spatio-temporal patterns of brain activity. In this study, we present a computational model using radial basis function neural network (RBF-NN) to predict the fMRI voxel activation with the activation of other voxels acquired at the same time. The fMRI data from a visual images stimuli presentation experiment was separated into two sets; one was used to train the model, and the other to validate the accuracy or generalizability of the model. In the visual stimuli presentation experiment, the subject did simple one-back-repetition tasks when four categories of stimuli (houses, faces, cars, and cats) were presented. Voxel sets A and B were selected from fMRI data by two different voxel selection criterion: (1) Voxel set A are those activated for any kind of object stronger than the other three objects in regions of interest (ROIs) without correction (P=0.001); (2) Voxel set B are those activated for at least one of the categories of stimuli within the ROIs (FWE correction, P=0.05). RBF-NN regression models construct the nonlinear relationship between the activation of voxels in A and B. Our test results showed that RBF-NN can capture the nonlinear relationship existing in neurons and reveal the relationship between voxel's activation from different brain regions.
Li, Qing-Bo; Huang, Zheng-Wei
2014-02-01
In order to improve the prediction accuracy of quantitative analysis model in the near-infrared spectroscopy of blood glucose, this paper, by combining net analyte preprocessing (NAP) algorithm and radial basis functions partial least squares (RBFPLS) regression, builds a nonlinear model building method which is suitable for glucose measurement of human, named as NAP-RBFPLS. First, NAP is used to pre-process the near-infrared spectroscopy of blood glucose, in order to effectively extract the information which only relates to glucose signal from the original near-infrared spectra, so that it could effectively weaken the occasional correlation problems of the glucose changes and the interference factors which are caused by the absorption of water, albumin, hemoglobin, fat and other components of the blood in human body, the change of temperature of human body, the drift of measuring instruments, the changes of measuring environment, and the changes of measuring conditions; and then a nonlinear quantitative analysis model is built with the near-infrared spectroscopy data after NAP, in order to solve the nonlinear relationship between glucose concentrations and near-infrared spectroscopy which is caused by body strong scattering. In this paper, the new method is compared with other three quantitative analysis models building on partial least squares (PLS), net analyte preprocessing partial least squares (NAP-PLS) and RBFPLS respectively. At last, the experimental results show that the nonlinear calibration model, developed by combining NAP algorithm and RBFPLS regression, which was put forward in this paper, greatly improves the prediction accuracy of prediction sets, and what has been proved in this paper is that the nonlinear model building method will produce practical applications for the research of non-invasive detection techniques on human glucose concentrations.
NASA Astrophysics Data System (ADS)
Dai, Xiaoyan; Guo, Zhongyang; Zhang, Liquan; Xu, Wencheng
2009-12-01
Soft classification methods can be used for mixed-pixel classification on remote sensing imagery by estimating different land cover class fractions of every pixel. However, the spatial distribution and location of these class components within the pixel remain unknown. To map land cover at subpixel scale and increase the spatial resolution of land cover classification maps, in this paper, a prediction model combining wavelet transform and Radial Basis Functions (RBF) neural network, abbreviated as Wavelet-RBFNN, is constructed by predicting high-frequency wavelet coefficients from low-frequency coefficients at the same resolution with RBF network and taking wavelet coefficients at coarser resolution as training samples. According to different land cover class fraction images obtained from mixed-pixel classification, based on the assumption of neighborhood dependence of wavelet coefficients, subpixel mapping on remote sensing imagery can be accomplished through two steps, i.e., prediction of land cover class compositions within subpixels and hard classification. The experimental results obtained with artificial images, QuickBird image and Landsat 7 ETM+ image indicate that the subpixel mapping method proposed in this paper can successfully produce super-resolution land cover classification maps from remote sensing imagery, outperforming cubic B-spline and Kriging interpolation method in visual effect and prediction accuracy. The Wavelet-RBFNN model can also be applied to simulate higher spatial resolution image, and automatically identify and locate land cover targets at the subpixel scales, when the cost and availability of high resolution imagery prohibit its use in many areas of work.
NASA Astrophysics Data System (ADS)
Lin, C. D.; Macek, J. H.
1984-05-01
Doubly-excited-state basis (DESB) functions of Herrick and Sinanoǧlu are compared with the large-scale configuration-interaction (CI) wave functions of Lipsky et al., and with the adiabatic channel functions in hyperspherical coordinates. It is shown that DESB functions will represent those states where the mean value of θ12 is large. Owing to the absence of intershell correlations, and a consequent underestimation of radial correlations, the DESB functions give excessive concentrations near θ12=0 for other, less sharply correlated in angle, states.
Fidêncio, Paulo H; Poppi, Ronei J; de Andrade, João C; de Abreu, Mônica F
2008-07-01
Total nitrogen has been determined by using a model developed between the conventional chemical measurements and diffuse reflectance spectra in the near-infrared region. Samples (244) from different types of soils with total nitrogen contents ranging from 0.20 to 13.60% (m/m) were modeled by partial least-squares regression (PLS), multi-layer perceptron feed-forward networks (MLP) and radial basis function networks (RBFN). The RBFN model produced a better square error of prediction (SEP) of 0.048 and R(2) = 0.93 in a procedure that is simpler, faster and less dependent on the initial conditions.
Heidari, Mohammad; Heidari, Ali; Homaei, Hadi
2014-01-01
The static pull-in instability of beam-type microelectromechanical systems (MEMS) is theoretically investigated. Two engineering cases including cantilever and double cantilever microbeam are considered. Considering the midplane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, capable of capturing the size effect. By selecting a range of geometric parameters such as beam lengths, width, thickness, gaps, and size effect, we identify the static pull-in instability voltage. A MAPLE package is employed to solve the nonlinear differential governing equations to obtain the static pull-in instability voltage of microbeams. Radial basis function artificial neural network with two functions has been used for modeling the static pull-in instability of microcantilever beam. The network has four inputs of length, width, gap, and the ratio of height to scale parameter of beam as the independent process variables, and the output is static pull-in voltage of microbeam. Numerical data, employed for training the network, and capabilities of the model have been verified in predicting the pull-in instability behavior. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 4.55% in predicting pull-in voltage of cantilever microbeam. Further analysis of pull-in instability of beam under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach. The results reveal significant influences of size effect and geometric parameters on the static pull-in instability voltage of MEMS. PMID:24860602
Heidari, Mohammad; Heidari, Ali; Homaei, Hadi
2014-01-01
The static pull-in instability of beam-type microelectromechanical systems (MEMS) is theoretically investigated. Two engineering cases including cantilever and double cantilever microbeam are considered. Considering the midplane stretching as the source of the nonlinearity in the beam behavior, a nonlinear size-dependent Euler-Bernoulli beam model is used based on a modified couple stress theory, capable of capturing the size effect. By selecting a range of geometric parameters such as beam lengths, width, thickness, gaps, and size effect, we identify the static pull-in instability voltage. A MAPLE package is employed to solve the nonlinear differential governing equations to obtain the static pull-in instability voltage of microbeams. Radial basis function artificial neural network with two functions has been used for modeling the static pull-in instability of microcantilever beam. The network has four inputs of length, width, gap, and the ratio of height to scale parameter of beam as the independent process variables, and the output is static pull-in voltage of microbeam. Numerical data, employed for training the network, and capabilities of the model have been verified in predicting the pull-in instability behavior. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 4.55% in predicting pull-in voltage of cantilever microbeam. Further analysis of pull-in instability of beam under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach. The results reveal significant influences of size effect and geometric parameters on the static pull-in instability voltage of MEMS.
Suková, Karolína; Uchytilová, Michaela; Lindová, Jitka
2013-06-01
The formation of the concept of sameness is considered as a crucial cognitive ability which allows for other high cognitive functions in some species, e.g. humans. It is often operationalized as transfer of the matching rule to new stimuli in a matching-to-sample task. Animal species show great differences regarding the number of stimuli needed in training to be able to perform a full transfer to new stimuli. Not only apes appear to master this task, but also corvids among the birds were shown to reach a full transfer using only few stimuli. Using colour, shape and number stimuli in a matching-to-sample design, we tested four grey parrots for their ability to judge identity. Only a limited set of 8 stimulus cards were used in training. Pairs of "same" number stimuli were visually different thus allowing to be matched according to number of elements only. All four parrots successfully transferred to testing phases including testing with completely new stimuli and their performance did not drop with new stimuli. Including number stimuli invalidated some interpretations based on visual non-abstract processes and give evidence for formation of the concept of sameness.
Kong, Chunli; Wang, Huiyi; Li, Dapeng; Zhang, Yuemei; Pan, Jinfeng; Zhu, Beiwei; Luo, Yongkang
2016-06-15
To investigate and predict quality of 2% brined common carp (Cyprinus carpio) fillets during frozen storage, free fatty acids (FFA), salt extractable protein (SEP), total sulfhydryl (SH) content, and Ca(2+)-ATPase activity were determined at 261 K, 253 K, and 245 K, respectively. There was a dramatic increase (P<0.05) in FFA and a sharp decrease (P<0.05) in SH at 261 K during the first 3 weeks. SEP decreased to 67.31% after 17 weeks at 245 K, whereas it took about 7 weeks and 13 weeks to decrease to the same extent at 261 K and 253 K, respectively. Ca(2+)-ATPase activity kept decreasing to 18.28% after 7 weeks at 261 K. Furthermore, radial basis function neural networks (RBFNNs) were developed to predict quality (FFA, SEP, SH, and Ca(2+)-ATPase activity) of brined carp fillets during frozen storage with relative errors all within ±5%. Thus, RBFNN is a promising method to predict quality of carp fillets during storage at 245-261 K. PMID:26868584
NASA Astrophysics Data System (ADS)
Srinivas, Kadivendi; Vundavilli, Pandu R.; Manzoor Hussain, M.; Saiteja, M.
2016-09-01
Welding input parameters such as current, gas flow rate and torch angle play a significant role in determination of qualitative mechanical properties of weld joint. Traditionally, it is necessary to determine the weld input parameters for every new welded product to obtain a quality weld joint which is time consuming. In the present work, the effect of plasma arc welding parameters on mild steel was studied using a neural network approach. To obtain a response equation that governs the input-output relationships, conventional regression analysis was also performed. The experimental data was constructed based on Taguchi design and the training data required for neural networks were randomly generated, by varying the input variables within their respective ranges. The responses were calculated for each combination of input variables by using the response equations obtained through the conventional regression analysis. The performances in Levenberg-Marquardt back propagation neural network and radial basis neural network (RBNN) were compared on various randomly generated test cases, which are different from the training cases. From the results, it is interesting to note that for the above said test cases RBNN analysis gave improved training results compared to that of feed forward back propagation neural network analysis. Also, RBNN analysis proved a pattern of increasing performance as the data points moved away from the initial input values.
NASA Astrophysics Data System (ADS)
Talebpour, Zahra; Tavallaie, Roya; Ahmadi, Seyyed Hamid; Abdollahpour, Assem
2010-09-01
In this study, a new method for the simultaneous determination of penicillin G salts in pharmaceutical mixture via FT-IR spectroscopy combined with chemometrics was investigated. The mixture of penicillin G salts is a complex system due to similar analytical characteristics of components. Partial least squares (PLS) and radial basis function-partial least squares (RBF-PLS) were used to develop the linear and nonlinear relation between spectra and components, respectively. The orthogonal signal correction (OSC) preprocessing method was used to correct unexpected information, such as spectral overlapping and scattering effects. In order to compare the influence of OSC on PLS and RBF-PLS models, the optimal linear (PLS) and nonlinear (RBF-PLS) models based on conventional and OSC preprocessed spectra were established and compared. The obtained results demonstrated that OSC clearly enhanced the performance of both RBF-PLS and PLS calibration models. Also in the case of some nonlinear relation between spectra and component, OSC-RBF-PLS gave satisfactory results than OSC-PLS model which indicated that the OSC was helpful to remove extrinsic deviations from linearity without elimination of nonlinear information related to component. The chemometric models were tested on an external dataset and finally applied to the analysis commercialized injection product of penicillin G salts.
Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J
2015-01-01
In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.
NASA Astrophysics Data System (ADS)
D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel
2016-03-01
We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.
NASA Astrophysics Data System (ADS)
Sabetghadam, Fereidoun; Soltani, Elshan
2015-10-01
The moving boundary conditions are implemented into the Fourier pseudo-spectral solution of the two-dimensional incompressible Navier-Stokes equations (NSE) in the vorticity-velocity form, using the radial basis functions (RBF). Without explicit definition of an external forcing function, the desired immersed boundary conditions are imposed by direct modification of the convection and diffusion terms. At the beginning of each time-step the solenoidal velocities, satisfying the desired moving boundary conditions, along with a modified vorticity are obtained and used in modification of the convection and diffusion terms of the vorticity evolution equation. Time integration is performed by the explicit fourth-order Runge-Kutta method and the boundary conditions are set at the beginning of each sub-step. The method is applied to a couple of moving boundary problems and more than second-order of accuracy in space is demonstrated for the Reynolds numbers up to Re = 550. Moreover, performance of the method is shown in comparison with the classical Fourier pseudo-spectral method.
Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J
2015-01-01
In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483
NASA Astrophysics Data System (ADS)
Owusu-Banson, Derek
In recent times, a variety of industries, applications and numerical methods including the meshless method have enjoyed a great deal of success by utilizing the graphical processing unit (GPU) as a parallel coprocessor. These benefits often include performance improvement over the previous implementations. Furthermore, applications running on graphics processors enjoy superior performance per dollar and performance per watt than implementations built exclusively on traditional central processing technologies. The GPU was originally designed for graphics acceleration but the modern GPU, known as the General Purpose Graphical Processing Unit (GPGPU) can be used for scientific and engineering calculations. The GPGPU consists of massively parallel array of integer and floating point processors. There are typically hundreds of processors per graphics card with dedicated high-speed memory. This work describes an application written by the author, titled GaussianRBF to show the implementation and results of a novel meshless method that in-cooperates the collocation of the Gaussian radial basis function by utilizing the GPU as a parallel co-processor. Key phases of the proposed meshless method have been executed on the GPU using the NVIDIA CUDA software development kit. Especially, the matrix fill and solution phases have been carried out on the GPU, along with some post processing. This approach resulted in a decreased processing time compared to similar algorithm implemented on the CPU while maintaining the same accuracy.
Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J.
2015-01-01
In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron. PMID:25849483
Afkhami, Abbas; Abbasi-Tarighat, Maryam
2008-06-01
In the present study, chemometric analysis of visible spectral data of phospho-and silico-molybdenum blue complexes was used to develop artificial neural networks (ANNs) for the simultaneous determination of the phosphate and silicate. Combinations of principal component analysis (PCA) with feed-forward neural networks (FFNNs) and radial basis function networks (RBFNs) were built and investigated. The structures of the models were simplified by using the corresponding important principal components as input instead of the original spectra. Number of inputs and hidden nodes, learning rate, transfer functions and number of epochs and SPREAD values were optimized. Performances of methods were tested with root mean square errors prediction (RMSEP, %), using synthetic solutions. The obtained satisfactory results indicate the applicability of this ANN approach based on PCA input selection for determination in highly spectral overlapping. The results obtained by FFNNs and by RBF networks were compared. The applicability of methods was investigated for synthetic samples, for detergent formulations, and for a river water sample.
Neelambike, Sumana M.
2016-01-01
Introduction Human Immunodeficiency Virus (HIV) infects and cripples the immune system of the body. The two important marker CD4+T cells and Plasma viral load are crucial not only in understanding the disease progression but also in starting the antiretroviral therapy. A lot of research is going on in understanding the dynamic nature of HIV. Aim To find the correlation between CD4+ count and Plasma Viral Load (PVL) measured by two different technologies; with the help of correlation technique in conjunction with the three dimensional HIV model with a purpose of establishing a mathematical model between the CD4+ cells and PVL using a sinusoidal function as well as Radial Basis Function (RBF) neural network. Materials and Methods Plasma Viral Load were determined by two different methods viz Exavir CavidiTM and Abbott Real time HIV-1 assay and then they were correlated with the CD4+ count with the help of computational intelligence in predicting viral load. Results It was found that there exists a positive correlation between the CD4+ cells and viral loads. A correlation value of 0.4082 and 0.3652 was observed between CD4+ cells and viral measured using Exavir CavidiTM and Abbott Real time HIV-1 assay respectively. Conclusion The existence of positive correlation had helped us to understand the nature and dynamic of the existence of HIV and how the CD4 + and PVL act. PMID:27190799
Huang, Wei; Oh, Sung-Kwun; Pedrycz, Witold
2014-12-01
In this study, we propose Hybrid Radial Basis Function Neural Networks (HRBFNNs) realized with the aid of fuzzy clustering method (Fuzzy C-Means, FCM) and polynomial neural networks. Fuzzy clustering used to form information granulation is employed to overcome a possible curse of dimensionality, while the polynomial neural network is utilized to build local models. Furthermore, genetic algorithm (GA) is exploited here to optimize the essential design parameters of the model (including fuzzification coefficient, the number of input polynomial fuzzy neurons (PFNs), and a collection of the specific subset of input PFNs) of the network. To reduce dimensionality of the input space, principal component analysis (PCA) is considered as a sound preprocessing vehicle. The performance of the HRBFNNs is quantified through a series of experiments, in which we use several modeling benchmarks of different levels of complexity (different number of input variables and the number of available data). A comparative analysis reveals that the proposed HRBFNNs exhibit higher accuracy in comparison to the accuracy produced by some models reported previously in the literature.
NASA Astrophysics Data System (ADS)
Boyd, John P.
2011-02-01
Radial basis function (RBF) interpolants have become popular in computer graphics, neural networks and for solving partial differential equations in many fields of science and engineering. In this article, we compare five different species of RBFs: Gaussians, hyperbolic secant (sech's), inverse quadratics, multiquadrics and inverse multiquadrics. We show that the corresponding cardinal functions for a uniform, unbounded grid are all approximated by the same function: C(X) ∼ (1/(ρ)) sin (πX)/sinh (πX/ρ) for some constant ρ(α) which depends on the inverse width parameter (“shape parameter”) α of the RBF and also on the RBF species. The error in this approximation is exponentially small in 1/α for sech's and inverse quadratics and exponentially small in 1/α2 for Gaussians; the error is proportional to α4 for multiquadrics and inverse multiquadrics. The error in all cases is small even for α ∼ O(1). These results generalize to higher dimensions. The Gaussian RBF cardinal functions in any number of dimensions d are, without approximation, the tensor product of one dimensional Gaussian cardinal functions: Cd(x1,x2…,xd)=∏j=1dC(xj). For other RBF species, we show that the two-dimensional cardinal functions are well approximated by the products of one-dimensional cardinal functions; again the error goes to zero as α → 0. The near-identity of the cardinal functions implies that all five species of RBF interpolants are (almost) the same, despite the great differences in the RBF ϕ's themselves.
Cerveri, P; Forlani, C; Pedotti, A; Ferrigno, G
2003-03-01
Global polynomial (GP) methods have been widely used to correct geometric image distortion of small-size (up to 30 cm) X-ray image intensifiers (XRIIs). This work confirms that this kind of approach is suitable for 40 cm XRIIs (now increasingly used). Nonetheless, two local methods, namely 3rd-order local un-warping polynomials (LUPs) and hierarchical radial basis function (HRBF) networks are proposed as alternative solutions. Extensive experimental tests were carried out to compare these methods with classical low-order local polynomial and GP techniques, in terms of residual error (RMSE) measured at points not used for parameter estimation. Simulations showed that the LUP and HRBF methods had accuracies comparable with that attained using GP methods. In detail, the LUP method (0.353 microm) performed worse than HRBF (0.348 microm) only for small grid spacing (15 x 15 control points); the accuracy of both HRBF (0.157 microm) and LUP (0.160 microm) methods was little affected by local distortions (30 x 30 control points); weak local distortions made the GP method poorer (0.320 microm). Tests on real data showed that LUP and HRBF had accuracies comparable with that of GP for both 30 cm (GP: 0.238 microm; LUP: 0.240 microm; HRBF: 0.238 microm) and 40 cm (GP: 0.164 microm; LUP: 0.164 microm; HRBF: 0.164 microm) XRIIs. The LUP-based distortion correction was implemented in real time for image correction in digital tomography applications.
Luengo, Julián; García, Salvador; Herrera, Francisco
2010-04-01
The presence of Missing Values in a data set can affect the performance of a classifier constructed using that data set as a training sample. Several methods have been proposed to treat missing data and the one used more frequently is the imputation of the Missing Values of an instance. In this paper, we analyze the improvement of performance on Radial Basis Function Networks by means of the use of several imputation methods in the classification task with missing values. The study has been conducted using data sets with real Missing Values, and data sets with artificial Missing Values. The results obtained show that EventCovering offers a very good synergy with Radial Basis Function Networks. It allows us to overcome the negative impact of the presence of Missing Values to a certain degree.
Kmicikiewicz, M.A.
1988-03-01
A radial engine is described comprising: a housing; equally spaced openings disposed in ring-like arrangement on the periphery of the housing; a piston and cylinder arrangement in each of the opening, a piston rod for each arrangement fixed to and extending radially inwardly from its respective piston and through its respective opening; shoe means pivotally attached at the other end of each of the piston rod; radial guide means extending in the housing in line with each of the piston rods, and the shoe means provided with guide means followers to ensure radial reciprocal movement of the piston rods and shoe means; and a connecting ring journaled on a crankshaft for circular translation motion in the housing, the ring including a circular rim. Each shoe means includes an arcuate follower member being slidably connected to the rim of the connecting ring.
Afkhami, Abbas; Abbasi-Tarighat, Maryam; Bahram, Morteza
2008-03-15
In this work feed-forward neural networks and radial basis function networks were used for the determination of enantiomeric composition of alpha-phenylglycine using UV spectra of cyclodextrin host-guest complexes and the data provided by two techniques were compared. Wavelet transformation (WT) and principal component analysis (PCA) were used for data compression prior to neural network construction and their efficiencies were compared. The structures of the wavelet transformation-radial basis function networks (WT-RBFNs) and wavelet transformation-feed-forward neural networks (WT-FFNNs), were simplified by using the corresponding wavelet coefficients of three mother wavelets (Mexican hat, daubechies and symlets). Dilation parameters, number of inputs, hidden nodes, learning rate, transfer functions, number of epochs and SPREAD values were optimized. Performances of the proposed methods were tested with regard to root mean square errors of prediction (RMSE%), using synthetic solutions containing a fixed concentration of beta-cyclodextrin (beta-CD) and fixed concentration of alpha-phenylglycine (alpha-Gly) with different enantiomeric compositions. Although satisfactory results with regard to some statistical parameters were obtained for all the investigated methods but the best results were achieved by WT-RBFNs.
ERIC Educational Resources Information Center
Henkes, Robert
1978-01-01
Abstract art provokes numerous interpretations, and as many misunderstandings. The adolescent reaction is no exception. The procedure described here can help the student to understand the abstract from at least one direction. (Author/RK)
NASA Astrophysics Data System (ADS)
Shahlaei, Mohsen; Bahrami, Gholamreza; Abdolmaleki, Sajjad; Sadrjavadi, Komail; Majnooni, Mohammad Bagher
2015-03-01
This study describes a simple and rapid approach of monitoring celecoxib (CLX). Unfolded principal component analysis-radial basis function neural network (UPCA-RBFNN) and excitation-emission spectra were combined to develop new model in the determination of CLX in human serum samples. Fluorescence landscapes with excitation wavelengths from 250 to 310 nm and emission wavelengths in the range 280-450 nm were obtained. The figures of merit for the developed model were evaluated. High performance liquid chromatography (HPLC) technique was also used as a standard method. Accuracy of the method was investigated by analysis of the serum samples spiked with various concentration of CLX and a recovery of 103.63% was obtained. The results indicated that the proposed method is an interesting alternative to the traditional techniques normally used for determining CLX such as HPLC.
Radial systems of dark globules
Gyul'budagyn, A.L.
1986-03-01
The author gives examples of radial systems consisting of dark globules and ''elephant trunks''. Besides already known systems, which contain hot stars at their center, data are given on three radial systems of a new kind, at the center of which there are stars of spectral types later than B. Data are given on 32 globules of radial systems of the association Cep OB2. On the basis of the observational data, it is concluded that at least some of the isolated Bok globules derive from elephant trunks and dark globules forming radial systems around hot stars. It is also suggested that the two molecular clouds situated near the Rosette nebula and possessing velocities differing by ca 20 km/sec from the velocity of the nebula could have been ejected in opposite directions from the center of the nebula. One of these clouds consists of dark globules forming the radial system of the Rosette nebula.
NASA Technical Reports Server (NTRS)
2005-01-01
[figure removed for brevity, see original site]
The ejecta surrounding the crater (off image to the left) in this image has undergone significant erosion by the wind. The wind has stripped the surface features from the ejecta and has started to winnow away the ejecta blanket. Near the margin of the ejecta the wind is eroding along a radial pattern -- taking advantage of radial emplacement. Note the steep margin of the ejecta blanket. Most, if not all, of the fine ejecta material has been removed and the wind in now working on the more massive continuous ejecta blanket.
Image information: VIS instrument. Latitude 12.5, Longitude 197.4 East (162.6 West). 37 meter/pixel resolution.
Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time.
NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.
Radial-radial single rotor turbine
Platts, David A.
2006-05-16
A rotor for use in turbine applications has a radial compressor/pump having radially disposed spaced apart fins forming passages and a radial turbine having hollow turbine blades interleaved with the fins and through which fluid from the radial compressor/pump flows. The rotor can, in some applications, be used to produce electrical power.
ERIC Educational Resources Information Center
Plotnick, Eric
2001-01-01
Presents research abstracts from the ERIC Clearinghouse on Information and Technology. Topics include: classroom communication apprehension and distance education; outcomes of a distance-delivered science course; the NASA/Kennedy Space Center Virtual Science Mentor program; survey of traditional and distance learning higher education members;…
ERIC Educational Resources Information Center
Pietropola, Anne
1998-01-01
Describes a lesson designed to culminate a year of eighth-grade art classes in which students explore elements of design and space by creating 3-D abstract constructions. Outlines the process of using foam board and markers to create various shapes and optical effects. (DSK)
Radially inhomogeneous bounded plasmas
NASA Astrophysics Data System (ADS)
Zakeri-Khatir, H.; Aghamir, F. M.
2016-07-01
On the basis of kinetic theory along with self-consistent field equations, the expressions for dielectric tensor of radially inhomogeneous magnetized plasma columns are obtained. The study of dielectric tensor characteristics allows the accurate analysis of the inhomogeneous properties, beyond limitations that exist in the conventional method. Through the Bessel-Fourier transformation, the localized form of material equations in a radially inhomogeneous medium are obtained. In order to verify the integrity of the model and reveal the effect of inhomogeneity, a special case of a cylindrical plasma waveguide completely filled with inhomogeneous magnetized cold plasma was considered. The dispersion relation curves for four families of electromagnetic (EH and HE) and electrostatic (SC and C) modes are obtained and compared with the findings of the conventional model. The numerical analysis indicates that the inhomogeneity effect leads to coupling of electromagnetic and electrostatic modes each having different radial eigen numbers. The study also reveals that the electrostatic modes are more sensitive to inhomogeneous effects than the electromagnetic modes.
Radially inhomogeneous bounded plasmas
NASA Astrophysics Data System (ADS)
Zakeri-Khatir, H.; Aghamir, F. M.
2016-07-01
On the basis of kinetic theory along with self-consistent field equations, the expressions for dielectric tensor of radially inhomogeneous magnetized plasma columns are obtained. The study of dielectric tensor characteristics allows the accurate analysis of the inhomogeneous properties, beyond limitations that exist in the conventional method. Through the Bessel–Fourier transformation, the localized form of material equations in a radially inhomogeneous medium are obtained. In order to verify the integrity of the model and reveal the effect of inhomogeneity, a special case of a cylindrical plasma waveguide completely filled with inhomogeneous magnetized cold plasma was considered. The dispersion relation curves for four families of electromagnetic (EH and HE) and electrostatic (SC and C) modes are obtained and compared with the findings of the conventional model. The numerical analysis indicates that the inhomogeneity effect leads to coupling of electromagnetic and electrostatic modes each having different radial eigen numbers. The study also reveals that the electrostatic modes are more sensitive to inhomogeneous effects than the electromagnetic modes.
McKeown, Mark H.; Beason, Steven C.
1991-01-01
The radial arm strike rail assembly is a system for measurement of bearings, directions, and stereophotography for geologic mapping, particularly where magnetic compasses are not appropriate. The radial arm, pivoting around a shaft axis, provides a reference direction determination for geologic mapping and bearing or direction determination. The centerable and levelable pedestal provide a base for the radial arm strike rail and the telescoping camera pedestal. The telescoping feature of the radial arm strike rail allows positioning the end of the rail for strike direction or bearing measurement with a goniometer.
Windmill pitcher's radial neuropathy.
Sinson, G; Zager, E L; Kline, D G
1994-06-01
The authors present two cases of severe radial nerve injury with different sites of pathology but a similar mechanism: the "windmill" pitching motion of competitive softball. Both patients required surgical intervention with neurolysis, and both improved postoperatively. The literature on related radial nerve injuries is briefly reviewed and pathophysiological mechanisms are discussed.
Ebert, Todd A; Carella, John A
2012-03-13
A triple acting radial seal used as an interstage seal assembly in a gas turbine engine, where the seal assembly includes an interstage seal support extending from a stationary inner shroud of a vane ring, the interstage seal support includes a larger annular radial inward facing groove in which an outer annular floating seal assembly is secured for radial displacement, and the outer annular floating seal assembly includes a smaller annular radial inward facing groove in which an inner annular floating seal assembly is secured also for radial displacement. A compliant seal is secured to the inner annular floating seal assembly. The outer annular floating seal assembly encapsulates the inner annular floating seal assembly which is made from a very low alpha material in order to reduce thermal stress.
Kleiner, M T; Ilyas, A M; Jupiter, J B
2010-02-01
In conclusion, radial head fractures with 3 or more fragments have a high incidence of complications when treated with ORIF including hardware failure, malunion, nonunion, and the need for re-operation. Radial head arthroplasty has demonstrated good success in the treatment of complex, comminuted radial head fractures which are not amenable to non-opeative treatment or ORIF. Success can be optimized by diligent surgical dissection, avoiding inadvertent nerve injury, placement of an appropriately sized implant, repair of associated injuries, and early protected motion. PMID:20214854
Radial head fracture - aftercare
Elbow fracture - radial head - aftercare ... to 2 weeks. If you have a small fracture and your bones did not move around much, ... to see a bone doctor (orthopedic surgeon). Some fractures require surgery to: Insert pins and plates to ...
ERIC Educational Resources Information Center
Moessinger, Pierre; Poulin-Dubois, Diane
1981-01-01
Reviews and discusses Piaget's recent work on abstract reasoning. Piaget's distinction between empirical and reflective abstraction is presented; his hypotheses are considered to be metaphorical. (Author/DB)
NASA Astrophysics Data System (ADS)
Roelke, Richard J.
The technology of high temperature cooled radial turbines is reviewed. Aerodynamic performance considerations are described. Heat transfer and structural analysis are addressed, and in doing so the following topics are covered: cooling considerations, hot side convection, coolant side convection, and rotor mechanical analysis. Cooled rotor concepts and fabrication are described, and the following are covered in this context: internally cooled rotor, hot isostatic pressure bonded rotor, laminated rotor, split blade rotor, and the NASA radial turbine program.
NASA Technical Reports Server (NTRS)
Roelke, Richard J.
1992-01-01
The technology of high temperature cooled radial turbines is reviewed. Aerodynamic performance considerations are described. Heat transfer and structural analysis are addressed, and in doing so the following topics are covered: cooling considerations, hot side convection, coolant side convection, and rotor mechanical analysis. Cooled rotor concepts and fabrication are described, and the following are covered in this context: internally cooled rotor, hot isostatic pressure bonded rotor, laminated rotor, split blade rotor, and the NASA radial turbine program.
NASA Astrophysics Data System (ADS)
Boyd, John P.; Yu, Fu
2011-02-01
We compare seven different strategies for computing spectrally-accurate approximations or differential equation solutions in a disk. Separation of variables for the Laplace operator yields an analytic solution as a Fourier-Bessel series, but this usually converges at an algebraic (sub-spectral) rate. The cylindrical Robert functions converge geometrically but are horribly ill-conditioned. The Zernike and Logan-Shepp polynomials span the same space, that of Cartesian polynomials of a given total degree, but the former allows partial factorization whereas the latter basis facilitates an efficient algorithm for solving the Poisson equation. The Zernike polynomials were independently rediscovered several times as the product of one-sided Jacobi polynomials in radius with a Fourier series in θ. Generically, the Zernike basis requires only half as many degrees of freedom to represent a complicated function on the disk as does a Chebyshev-Fourier basis, but the latter has the great advantage of being summed and interpolated entirely by the Fast Fourier Transform instead of the slower matrix multiplication transforms needed in radius by the Zernike basis. Conformally mapping a square to the disk and employing a bivariate Chebyshev expansion on the square is spectrally accurate, but clustering of grid points near the four singularities of the mapping makes this method less efficient than the rest, meritorious only as a quick-and-dirty way to adapt a solver-for-the-square to the disk. Radial basis functions can match the best other spectral methods in accuracy, but require slow non-tensor interpolation and summation methods. There is no single “best” basis for the disk, but we have laid out the merits and flaws of each spectral option.
Bartoníček, J; Naňka, O; Tuček, M
2015-10-01
In the clinical practice, radial shaft may be exposed via two approaches, namely the posterolateral Thompson and volar (anterior) Henry approaches. A feared complication of both of them is the injury to the deep branch of the radial nerve. No consensus has been reached, yet, as to which of the two approaches is more beneficial for the proximal half of radius. According to our anatomical studies and clinical experience, Thompson approach is safe only in fractures of the middle and distal thirds of the radial shaft, but highly risky in fractures of its proximal third. Henry approach may be used in any fracture of the radial shaft and provides a safe exposure of the entire lateral and anterior surfaces of the radius.The Henry approach has three phases. In the first phase, incision is made along the line connecting the biceps brachii tendon and the styloid process of radius. Care must be taken not to damage the lateral cutaneous nerve of forearm.In the second phase, fascia is incised and the brachioradialis identified by the typical transition from the muscle belly to tendon and the shape of the tendon. On the lateral side, the brachioradialis lines the space with the radial artery and veins and the superficial branch of the radial nerve running at its bottom. On the medial side, the space is defined by the pronator teres in the proximal part and the flexor carpi radialis in the distal part. The superficial branch of the radial nerve is retracted together with the brachioradialis laterally, and the radial artery medially.In the third phase, the attachment of the pronator teres is identified by its typical tendon in the middle of convexity of the lateral surface of the radial shaft. The proximal half of the radius must be exposed very carefully in order not to damage the deep branch of the radial nerve. Dissection starts at the insertion of the pronator teres and proceeds proximally along its lateral border in interval between this muscle and insertion of the supinator
NASA Technical Reports Server (NTRS)
Roelke, Richard J.
1992-01-01
Radial turbines have been used extensively in many applications including small ground based electrical power generators, automotive engine turbochargers and aircraft auxiliary power units. In all of these applications the turbine inlet temperature is limited to a value commensurate with the material strength limitations and life requirements of uncooled metal rotors. To take advantage of all the benefits that higher temperatures offer, such as increased turbine specific power output or higher cycle thermal efficiency, requires improved high temperature materials and/or blade cooling. Extensive research is on-going to advance the material properties of high temperature superalloys as well as composite materials including ceramics. The use of ceramics with their high temperature potential and low cost is particularly appealing for radial turbines. However until these programs reach fruition the only way to make significant step increases beyond the present material temperature barriers is to cool the radial blading.
Smith, Karl H.
2002-01-01
A radial wedge flange clamp comprising a pair of flanges each comprising a plurality of peripheral flat wedge facets having flat wedge surfaces and opposed and mating flat surfaces attached to or otherwise engaged with two elements to be joined and including a series of generally U-shaped wedge clamps each having flat wedge interior surfaces and engaging one pair of said peripheral flat wedge facets. Each of said generally U-shaped wedge clamps has in its opposing extremities apertures for the tangential insertion of bolts to apply uniform radial force to said wedge clamps when assembled about said wedge segments.
Radial Nerve Tendon Transfers.
Cheah, Andre Eu-Jin; Etcheson, Jennifer; Yao, Jeffrey
2016-08-01
Radial nerve palsy typically occurs as a result of trauma or iatrogenic injury and leads to the loss of wrist extension, finger extension, thumb extension, and a reduction in grip strength. In the absence of nerve recovery, reconstruction of motor function involves tendon transfer surgery. The most common donor tendons include the pronator teres, wrist flexors, and finger flexors. The type of tendon transfer is classified based on the donor for the extensor digitorum communis. Good outcomes have been reported for most methods of radial nerve tendon transfers as is typical for positional tendon transfers not requiring significant power. PMID:27387076
ERIC Educational Resources Information Center
Dolan, Donna R.
1978-01-01
Discusses particular problems and possible solutions in searching the Psychological Abstracts database, with special reference to its loading on BRS. Included are examples of typical searches, citations (with or without abstract/annotation), a tabulated searchguide to Psychological Abstracts on BRS and specifications for the database. (Author/JD)
ERIC Educational Resources Information Center
Monaghan, John; Ozmantar, Mehmet Fatih
2006-01-01
The framework for this paper is a recently developed theory of abstraction in context. The paper reports on data collected from one student working on tasks concerned with absolute value functions. It examines the relationship between mathematical constructions and abstractions. It argues that an abstraction is a consolidated construction that can…
Abstraction and Problem Reformulation
NASA Technical Reports Server (NTRS)
Giunchiglia, Fausto
1992-01-01
In work done jointly with Toby Walsh, the author has provided a sound theoretical foundation to the process of reasoning with abstraction (GW90c, GWS9, GW9Ob, GW90a). The notion of abstraction formalized in this work can be informally described as: (property 1), the process of mapping a representation of a problem, called (following historical convention (Sac74)) the 'ground' representation, onto a new representation, called the 'abstract' representation, which, (property 2) helps deal with the problem in the original search space by preserving certain desirable properties and (property 3) is simpler to handle as it is constructed from the ground representation by "throwing away details". One desirable property preserved by an abstraction is provability; often there is a relationship between provability in the ground representation and provability in the abstract representation. Another can be deduction or, possibly inconsistency. By 'throwing away details' we usually mean that the problem is described in a language with a smaller search space (for instance a propositional language or a language without variables) in which formulae of the abstract representation are obtained from the formulae of the ground representation by the use of some terminating rewriting technique. Often we require that the use of abstraction results in more efficient .reasoning. However, it might simply increase the number of facts asserted (eg. by allowing, in practice, the exploration of deeper search spaces or by implementing some form of learning). Among all abstractions, three very important classes have been identified. They relate the set of facts provable in the ground space to those provable in the abstract space. We call: TI abstractions all those abstractions where the abstractions of all the provable facts of the ground space are provable in the abstract space; TD abstractions all those abstractions wllere the 'unabstractions' of all the provable facts of the abstract space are
Radial Halbach Magnetic Bearings
NASA Technical Reports Server (NTRS)
Eichenberg, Dennis J.; Gallo, Christopher A.; Thompson, William K.
2009-01-01
Radial Halbach magnetic bearings have been investigated as part of an effort to develop increasingly reliable noncontact bearings for future high-speed rotary machines that may be used in such applications as aircraft, industrial, and land-vehicle power systems and in some medical and scientific instrumentation systems. Radial Halbach magnetic bearings are based on the same principle as that of axial Halbach magnetic bearings, differing in geometry as the names of these two types of bearings suggest. Both radial and axial Halbach magnetic bearings are passive in the sense that unlike most other magnetic bearings that have been developed in recent years, they effect stable magnetic levitation without need for complex active control. Axial Halbach magnetic bearings were described in Axial Halbach Magnetic Bearings (LEW-18066-1), NASA Tech Briefs, Vol. 32, No. 7 (July 2008), page 85. In the remainder of this article, the description of the principle of operation from the cited prior article is recapitulated and updated to incorporate the present radial geometry. In simplest terms, the basic principle of levitation in an axial or radial Halbach magnetic bearing is that of the repulsive electromagnetic force between (1) a moving permanent magnet and (2) an electric current induced in a stationary electrical conductor by the motion of the magnetic field. An axial or radial Halbach bearing includes multiple permanent magnets arranged in a Halbach array ("Halbach array" is defined below) in a rotor and multiple conductors in the form of wire coils in a stator, all arranged so the rotary motion produces an axial or radial repulsion that is sufficient to levitate the rotor. A basic Halbach array (see Figure 1) consists of a row of permanent magnets, each oriented so that its magnetic field is at a right angle to that of the adjacent magnet, and the right-angle turns are sequenced so as to maximize the magnitude of the magnetic flux density on one side of the row while
Variable stator radial turbine
NASA Technical Reports Server (NTRS)
Rogo, C.; Hajek, T.; Chen, A. G.
1984-01-01
A radial turbine stage with a variable area nozzle was investigated. A high work capacity turbine design with a known high performance base was modified to accept a fixed vane stagger angle moveable sidewall nozzle. The nozzle area was varied by moving the forward and rearward sidewalls. Diffusing and accelerating rotor inlet ramps were evaluated in combinations with hub and shroud rotor exit rings. Performance of contoured sidewalls and the location of the sidewall split line with respect to the rotor inlet was compared to the baseline. Performance and rotor exit survey data are presented for 31 different geometries. Detail survey data at the nozzle exit are given in contour plot format for five configurations. A data base is provided for a variable geometry concept that is a viable alternative to the more common pivoted vane variable geometry radial turbine.
Pigino, Gaia; Ishikawa, Takashi
2012-01-01
The radial spoke (RS) is a complex of at least 23 proteins that works as a mechanochemical transducer between the central‐pair apparatus and the peripheral microtubule doublets in eukaryotic flagella and motile cilia. The RS contributes to the regulation of the activity of dynein motors, and thus to flagellar motility. Despite numerous biochemical, physiological and structural studies, the mechanism of the function of the radial spoke remains unclear. Detailed knowledge of the 3D structure of the RS protein complex is needed in order to understand how RS regulates dynein activity. Here we review the most important findings on the structure of the RS, including results of our recent cryo‐electron tomographic analysis of the RS protein complex. PMID:22754630
Radial Inflow Turboexpander Redesign
William G. Price
2001-09-24
Steamboat Envirosystems, LLC (SELC) was awarded a grant in accordance with the DOE Enhanced Geothermal Systems Project Development. Atlas-Copco Rotoflow (ACR), a radial expansion turbine manufacturer, was responsible for the manufacturing of the turbine and the creation of the new computer program. SB Geo, Inc. (SBG), the facility operator, monitored and assisted ACR's activities as well as provided installation and startup assistance. The primary scope of the project is the redesign of an axial flow turbine to a radial inflow turboexpander to provide increased efficiency and reliability at an existing facility. In addition to the increased efficiency and reliability, the redesign includes an improved reduction gear design, and improved shaft seal design, and upgraded control system and a greater flexibility of application
Batzer, Thomas H.; Call, Wayne R.
1989-01-01
This invention provides an all metal seal for vacuum or pressure vessels or systems. This invention does not use gaskets. The invention uses a flange which fits into a matching groove. Fluid pressure is applied in a chamber in the flange causing at least one of the flange walls to radially press against a side of the groove creating the seal between the flange wall and the groove side.
Radial Field Piezoelectric Diaphragms
NASA Technical Reports Server (NTRS)
Bryant, R. G.; Effinger, R. T., IV; Copeland, B. M., Jr.
2002-01-01
A series of active piezoelectric diaphragms were fabricated and patterned with several geometrically defined Inter-Circulating Electrodes "ICE" and Interdigitated Ring Electrodes "ICE". When a voltage potential is applied to the electrodes, the result is a radially distributed electric field that mechanically strains the piezoceramic along the Z-axis (perpendicular to the applied electric field). Unlike other piezoelectric bender actuators, these Radial Field Diaphragms (RFDs) strain concentrically yet afford high displacements (several times that of the equivalent Unimorph) while maintaining a constant circumference. One of the more intriguing aspects is that the radial strain field reverses itself along the radius of the RFD while the tangential strain remains relatively constant. The result is a Z-deflection that has a conical profile. This paper covers the fabrication and characterization of the 5 cm. (2 in.) diaphragms as a function of poling field strength, ceramic thickness, electrode type and line spacing, as well as the surface topography, the resulting strain field and displacement as a function of applied voltage at low frequencies. The unique features of these RFDs include the ability to be clamped about their perimeter with little or no change in displacement, the environmentally insulated packaging, and a highly repeatable fabrication process that uses commodity materials.
ERIC Educational Resources Information Center
Stevens, Lori
2004-01-01
The author describes a lesson she did on abstract art with her high school art classes. She passed out a required step-by-step outline of the project process. She asked each of them to look at abstract art. They were to list five or six abstract artists they thought were interesting, narrow their list down to the one most personally intriguing,…
Antiproton compression and radial measurements
Andresen, G. B.; Bowe, P. D.; Hangst, J. S.; Bertsche, W.; Butler, E.; Charlton, M.; Humphries, A. J.; Jenkins, M. J.; Joergensen, L. V.; Madsen, N.; Werf, D. P. van der; Bray, C. C.; Chapman, S.; Fajans, J.; Povilus, A.; Wurtele, J. S.; Cesar, C. L.; Lambo, R.; Silveira, D. M.; Fujiwara, M. C.
2008-08-08
Control of the radial profile of trapped antiproton clouds is critical to trapping antihydrogen. We report detailed measurements of the radial manipulation of antiproton clouds, including areal density compressions by factors as large as ten, achieved by manipulating spatially overlapped electron plasmas. We show detailed measurements of the near-axis antiproton radial profile, and its relation to that of the electron plasma. We also measure the outer radial profile by ejecting antiprotons to the trap wall using an octupole magnet.
Mathematical Abstraction through Scaffolding
ERIC Educational Resources Information Center
Ozmantar, Mehmet Fatih; Roper, Tom
2004-01-01
This paper examines the role of scaffolding in the process of abstraction. An activity-theoretic approach to abstraction in context is taken. This examination is carried out with reference to verbal protocols of two 17 year-old students working together on a task connected to sketching the graph of |f|x|)|. Examination of the data suggests that…
ERIC Educational Resources Information Center
Kernan, Christine
2011-01-01
For this author, one of the most enjoyable aspects of teaching elementary art is the willingness of students to embrace the different styles of art introduced to them. In this article, she describes a project that allows upper-elementary students to learn about abstract art and the lives of some of the master abstract artists, implement the idea…
Designing for Mathematical Abstraction
ERIC Educational Resources Information Center
Pratt, Dave; Noss, Richard
2010-01-01
Our focus is on the design of systems (pedagogical, technical, social) that encourage mathematical abstraction, a process we refer to as "designing for abstraction." In this paper, we draw on detailed design experiments from our research on children's understanding about chance and distribution to re-present this work as a case study in designing…
ERIC Educational Resources Information Center
Sutley, Jane
2010-01-01
Abstraction is, in effect, a simplification and reduction of shapes with an absence of detail designed to comprise the essence of the more naturalistic images being depicted. Without even intending to, young children consistently create interesting, and sometimes beautiful, abstract compositions. A child's creations, moreover, will always seem to…
ERIC Educational Resources Information Center
Johnson, Larry, Ed.
1995-01-01
The abstracts in this series provide two-page discussions of issues related to leadership, administration, and teaching in community colleges. The 12 abstracts for Volume 8, 1995, are: (1) "Redesigning the System To Meet the Workforce Training Needs of the Nation," by Larry Warford; (2) "The College President, the Board, and the Board Chair: A…
Concept Formation and Abstraction.
ERIC Educational Resources Information Center
Lunzer, Eric A.
1979-01-01
This paper examines the nature of concepts and conceptual processes and the manner of their formation. It argues that a process of successive abstraction and systematization is central to the evolution of conceptual structures. Classificatory processes are discussed and three levels of abstraction outlined. (Author/SJL)
ERIC Educational Resources Information Center
Novak, Gordon S., Jr.
GLISP is a high-level computer language (based on Lisp and including Lisp as a sublanguage) which is compiled into Lisp. GLISP programs are compiled relative to a knowledge base of object descriptions, a form of abstract datatypes. A primary goal of the use of abstract datatypes in GLISP is to allow program code to be written in terms of objects,…
Leadership Abstracts, Volume 10.
ERIC Educational Resources Information Center
Milliron, Mark D., Ed.
1997-01-01
The abstracts in this series provide brief discussions of issues related to leadership, administration, professional development, technology, and education in community colleges. Volume 10 for 1997 contains the following 12 abstracts: (1) "On Community College Renewal" (Nathan L. Hodges and Mark D. Milliron); (2) "The Community College Niche in a…
NASA Technical Reports Server (NTRS)
Owre, Sam; Shankar, Natarajan
1997-01-01
PVS (Prototype Verification System) is a general-purpose environment for developing specifications and proofs. This document deals primarily with the abstract datatype mechanism in PVS which generates theories containing axioms and definitions for a class of recursive datatypes. The concepts underlying the abstract datatype mechanism are illustrated using ordered binary trees as an example. Binary trees are described by a PVS abstract datatype that is parametric in its value type. The type of ordered binary trees is then presented as a subtype of binary trees where the ordering relation is also taken as a parameter. We define the operations of inserting an element into, and searching for an element in an ordered binary tree; the bulk of the report is devoted to PVS proofs of some useful properties of these operations. These proofs illustrate various approaches to proving properties of abstract datatype operations. They also describe the built-in capabilities of the PVS proof checker for simplifying abstract datatype expressions.
Rehder, B; Ross, B H
2001-09-01
Many studies have demonstrated the importance of the knowledge that interrelates features in people's mental representation of categories and that makes our conception of categories coherent. This article focuses on abstract coherent categories, coherent categories that are also abstract because they are defined by relations independently of any features. Four experiments demonstrate that abstract coherent categories are learned more easily than control categories with identical features and statistical structure, and also that participants induced an abstract representation of the category by granting category membership to exemplars with completely novel features. The authors argue that the human conceptual system is heavily populated with abstract coherent concepts, including conceptions of social groups, societal institutions, legal, political, and military scenarios, and many superordinate categories, such as classes of natural kinds. PMID:11550753
NASA Astrophysics Data System (ADS)
Hamid, S.; Elder, R. L.
1992-03-01
The radial inflow turbine is a primary component used both in small gas turbines and turbochargers. Better understanding of the flow processes occurring within the small passages of the machine could well result in the improved design of units. As most of the detailed aerodynamics is still ill-defined, a joint research project with the objective of improving our understanding has been instigated by Cranfield, the US Army and Turbomach (San Diego). This document gives the seventh report on the project and describes progress and measurements taken.
Osterday, Robert M.; Brodman, Richard F.
2013-01-01
The radial artery (RA) has emerged as an important arterial graft for coronary bypass surgery. With improving five-year patency rates and increasing uptake, great attention has been focused on the optimal conduit harvesting technique. We herein present our approach to RA harvesting. Prerequisites of a successful harvest include adherence to important anatomical landmarks, protection of the sensory innervation to the volar forearm, and meticulous handling of the RA branches. Regardless of the harvesting methodology chosen, adherence to a “no-touch” technique will optimize the patency and durability of the RA conduit. PMID:23977633
Robertson, M.C.
1997-01-08
The project`s aim is to complete development of the Radial Cutting Torch, a pyrotechnic cutter, for use in all downhole tubular cutting operations in the petroleum industry. Project objectives are to redesign and pressure test nozzle seals to increase product quality, reliability, and manufacturability; improve the mechanical anchor to increase its temperature tolerance and its ability to function in a wider variety of wellbore fluids; and redesign and pressure test the RCT nozzle for operation at pressures from 10 to 20 ksi. The proposal work statement is included in the statement of work for the grant via this reference.
Radial Reflection diffraction tomorgraphy
Lehman, Sean K
2013-11-19
A wave-based tomographic imaging method and apparatus based upon one or more rotating radially outward oriented transmitting and receiving elements have been developed for non-destructive evaluation. At successive angular locations at a fixed radius, a predetermined transmitting element can launch a primary field and one or more predetermined receiving elements can collect the backscattered field in a "pitch/catch" operation. A Hilbert space inverse wave (HSIW) algorithm can construct images of the received scattered energy waves using operating modes chosen for a particular application. Applications include, improved intravascular imaging, bore hole tomography, and non-destructive evaluation (NDE) of parts having existing access holes.
Radial reflection diffraction tomography
Lehman, Sean K.
2012-12-18
A wave-based tomographic imaging method and apparatus based upon one or more rotating radially outward oriented transmitting and receiving elements have been developed for non-destructive evaluation. At successive angular locations at a fixed radius, a predetermined transmitting element can launch a primary field and one or more predetermined receiving elements can collect the backscattered field in a "pitch/catch" operation. A Hilbert space inverse wave (HSIW) algorithm can construct images of the received scattered energy waves using operating modes chosen for a particular application. Applications include, improved intravascular imaging, bore hole tomography, and non-destructive evaluation (NDE) of parts having existing access holes.
2016-07-01
The peer-reviewed abstracts presented at the 73rd Annual Meeting of the ACPA are published as submitted by the authors. For financial conflict of interest disclosure, please visit http://meeting.acpa-cpf.org/disclosures.html. PMID:27447885
ERIC Educational Resources Information Center
Occupational Mental Health, 1971
1971-01-01
Provides abstracts and citations of journal articles and reports dealing with aspects of mental health. Topics include alcoholism, drug abuse, disadvantaged, mental health programs, rehabilitation, student mental health, and others. (SB)
Automatic Abstraction in Planning
NASA Technical Reports Server (NTRS)
Christensen, J.
1991-01-01
Traditionally, abstraction in planning has been accomplished by either state abstraction or operator abstraction, neither of which has been fully automatic. We present a new method, predicate relaxation, for automatically performing state abstraction. PABLO, a nonlinear hierarchical planner, implements predicate relaxation. Theoretical, as well as empirical results are presented which demonstrate the potential advantages of using predicate relaxation in planning. We also present a new definition of hierarchical operators that allows us to guarantee a limited form of completeness. This new definition is shown to be, in some ways, more flexible than previous definitions of hierarchical operators. Finally, a Classical Truth Criterion is presented that is proven to be sound and complete for a planning formalism that is general enough to include most classical planning formalisms that are based on the STRIPS assumption.
ERIC Educational Resources Information Center
Ciscell, Bob
1973-01-01
A functional approach involving collage, two-dimensional design, three-dimensional construction, and elements of Cubism, is used to teach abstract design in elementary and junior high school art classes. (DS)
ERIC Educational Resources Information Center
Proceedings of the ASIS Annual Meeting, 1991
1991-01-01
Presents abstracts of 36 special interest group (SIG) sessions. Highlights include the Chemistry Online Retrieval Experiment; organizing and retrieving images; intelligent information retrieval using natural language processing; interdisciplinarity; libraries as publishers; indexing hypermedia; cognitive aspects of classification; computer-aided…
1971 Annual Conference Abstracts
ERIC Educational Resources Information Center
Journal of Engineering Education, 1971
1971-01-01
Included are 112 abstracts listed under headings such as: acoustics, continuing engineering studies, educational research and methods, engineering design, libraries, liberal studies, and materials. Other areas include agricultural, electrical, mechanical, mineral, and ocean engineering. (TS)
Paradigms for Abstracting Systems.
ERIC Educational Resources Information Center
Pinto, Maria; Galvez, Carmen
1999-01-01
Discussion of abstracting systems focuses on the paradigm concept and identifies and explains four paradigms: communicational, or information theory; physical, including information retrieval; cognitive, including information processing and artificial intelligence; and systemic, including quality management. Emphasizes multidimensionality and…
Abstracts of contributed papers
Not Available
1994-08-01
This volume contains 571 abstracts of contributed papers to be presented during the Twelfth US National Congress of Applied Mechanics. Abstracts are arranged in the order in which they fall in the program -- the main sessions are listed chronologically in the Table of Contents. The Author Index is in alphabetical order and lists each paper number (matching the schedule in the Final Program) with its corresponding page number in the book.
Radial evolution of the energy density of solar wind fluctuations
NASA Technical Reports Server (NTRS)
Zank, G. P.; Matthaeus, W. H.; Smith, C. W.
1995-01-01
On the basis of transport theories appropriate to a radially expanding solar wind, we describe new results for the radial evolution of the energy density in solar wind fluctuations at MHD scales. These models include the effects of 'mixing' and driving as well as the possibility of non-isotropic MHD turbulence. Implications of these results for solar wind heating, cosmic ray diffusion and interstellar pick-up ions will also be addressed.
Radial Eigenmodes for a Toroidal Waveguide with Rectangular Cross Section
Rui Li
2012-07-01
In applying mode expansion to solve the CSR impedance for a section of toroidal vacuum chamber with rectangular cross section, we identify the eigenvalue problem for the radial eigenmodes which is different from that for cylindrical structures. In this paper, we present the general expressions of the radial eigenmodes, and discuss the properties of the eigenvalues on the basis of the Sturm-Liouville theory.
Grundy, B.R.
1981-09-29
The radial cold trap comprises a housing having a plurality of mesh bands disposed therein. The mesh bands comprise concentrically arranged bands of mesh with the mesh specific surface area of each band increasing from the outermost mesh band to the innermost mesh band. An inlet nozzle is attached to the outside section of the housing while an outlet nozzle is attached to the inner portion of the housing so as to be concentrically connected to the innermost mesh band. An inlet baffle having orifices therein may be disposed around the outermost mesh band and within the housing for directing the flow of the fluid from the inlet nozzle to the outermost mesh band in a uniform manner. The flow of fluid passes through each consecutive mesh band and into the outlet nozzle. The circular pattern of the symmetrically arranged mesh packing allows for better utilization of the entire cold trap volume. 2 figs.
Grundy, Brian R.
1981-01-01
The radial cold trap comprises a housing having a plurality of mesh bands disposed therein. The mesh bands comprise concentrically arranged bands of mesh with the mesh specific surface area of each band increasing from the outermost mesh band to the innermost mesh band. An inlet nozzle is attached to the outside section of the housing while an outlet nozzle is attached to the inner portion of the housing so as to be concentrically connected to the innermost mesh band. An inlet baffle having orifices therein may be disposed around the outermost mesh band and within the housing for directing the flow of the fluid from the inlet nozzle to the outermost mesh band in a uniform manner. The flow of fluid passes through each consecutive mesh band and into the outlet nozzle. The circular pattern of the symmetrically arranged mesh packing allows for better utilization of the entire cold trap volume.
Metacognition and abstract reasoning.
Markovits, Henry; Thompson, Valerie A; Brisson, Janie
2015-05-01
The nature of people's meta-representations of deductive reasoning is critical to understanding how people control their own reasoning processes. We conducted two studies to examine whether people have a metacognitive representation of abstract validity and whether familiarity alone acts as a separate metacognitive cue. In Study 1, participants were asked to make a series of (1) abstract conditional inferences, (2) concrete conditional inferences with premises having many potential alternative antecedents and thus specifically conducive to the production of responses consistent with conditional logic, or (3) concrete problems with premises having relatively few potential alternative antecedents. Participants gave confidence ratings after each inference. Results show that confidence ratings were positively correlated with logical performance on abstract problems and concrete problems with many potential alternatives, but not with concrete problems with content less conducive to normative responses. Confidence ratings were higher with few alternatives than for abstract content. Study 2 used a generation of contrary-to-fact alternatives task to improve levels of abstract logical performance. The resulting increase in logical performance was mirrored by increases in mean confidence ratings. Results provide evidence for a metacognitive representation based on logical validity, and show that familiarity acts as a separate metacognitive cue.
Abstracting and indexing guide
U.S. Department of the Interior; Office of Water Resources Research
1974-01-01
These instructions have been prepared for those who abstract and index scientific and technical documents for the Water Resources Scientific Information Center (WRSIC). With the recent publication growth in all fields, information centers have undertaken the task of keeping the various scientific communities aware of current and past developments. An abstract with carefully selected index terms offers the user of WRSIC services a more rapid means for deciding whether a document is pertinent to his needs and professional interests, thus saving him the time necessary to scan the complete work. These means also provide WRSIC with a document representation or surrogate which is more easily stored and manipulated to produce various services. Authors are asked to accept the responsibility for preparing abstracts of their own papers to facilitate quick evaluation, announcement, and dissemination to the scientific community.
Thyra Abstract Interface Package
2005-09-01
Thrya primarily defines a set of abstract C++ class interfaces needed for the development of abstract numerical atgorithms (ANAs) such as iterative linear solvers, transient solvers all the way up to optimization. At the foundation of these interfaces are abstract C++ classes for vectors, vector spaces, linear operators and multi-vectors. Also included in the Thyra package is C++ code for creating concrete vector, vector space, linear operator, and multi-vector subclasses as well as other utilitiesmore » to aid in the development of ANAs. Currently, very general and efficient concrete subclass implementations exist for serial and SPMD in-core vectors and multi-vectors. Code also currently exists for testing objects and providing composite objects such as product vectors.« less
ERIC Educational Resources Information Center
Engineering Education, 1976
1976-01-01
Presents the abstracts of 158 papers presented at the American Society for Engineering Education's annual conference at Knoxville, Tennessee, June 14-17, 1976. Included are engineering topics covering education, aerospace, agriculture, biomedicine, chemistry, computers, electricity, acoustics, environment, mechanics, and women. (SL)
Seismic Consequence Abstraction
M. Gross
2004-10-25
The primary purpose of this model report is to develop abstractions for the response of engineered barrier system (EBS) components to seismic hazards at a geologic repository at Yucca Mountain, Nevada, and to define the methodology for using these abstractions in a seismic scenario class for the Total System Performance Assessment - License Application (TSPA-LA). A secondary purpose of this model report is to provide information for criticality studies related to seismic hazards. The seismic hazards addressed herein are vibratory ground motion, fault displacement, and rockfall due to ground motion. The EBS components are the drip shield, the waste package, and the fuel cladding. The requirements for development of the abstractions and the associated algorithms for the seismic scenario class are defined in ''Technical Work Plan For: Regulatory Integration Modeling of Drift Degradation, Waste Package and Drip Shield Vibratory Motion and Seismic Consequences'' (BSC 2004 [DIRS 171520]). The development of these abstractions will provide a more complete representation of flow into and transport from the EBS under disruptive events. The results from this development will also address portions of integrated subissue ENG2, Mechanical Disruption of Engineered Barriers, including the acceptance criteria for this subissue defined in Section 2.2.1.3.2.3 of the ''Yucca Mountain Review Plan, Final Report'' (NRC 2003 [DIRS 163274]).
ERIC Educational Resources Information Center
Avraamidou, Antri; Monaghan, John; Walker, Aisha
2012-01-01
This paper examines the computer game play of an 11-year-old boy. In the course of building a virtual house he developed and used, without assistance, an artefact and an accompanying strategy to ensure that his house was symmetric. We argue that the creation and use of this artefact-strategy is a mathematical abstraction. The discussion…
ERIC Educational Resources Information Center
Potter, Lee Ann
2005-01-01
President Ronald Reagan nominated a woman to serve on the United States Supreme Court. He did so through a single-page form letter, completed in part by hand and in part by typewriter, announcing Sandra Day O'Connor as his nominee. While the document serves as evidence of a historic event, it is also a tangible illustration of abstract concepts…
ERIC Educational Resources Information Center
Journal of Engineering Education, 1972
1972-01-01
Includes abstracts of papers presented at the 80th Annual Conference of the American Society for Engineering Education. The broad areas include aerospace, affiliate and associate member council, agricultural engineering, biomedical engineering, continuing engineering studies, chemical engineering, civil engineering, computers, cooperative…
ERIC Educational Resources Information Center
Nwabueze, Kenneth K.
2004-01-01
The current emphasis on flexible modes of mathematics delivery involving new information and communication technology (ICT) at the university level is perhaps a reaction to the recent change in the objectives of education. Abstract algebra seems to be one area of mathematics virtually crying out for computer instructional support because of the…
2002 NASPSA Conference Abstracts.
ERIC Educational Resources Information Center
Journal of Sport & Exercise Psychology, 2002
2002-01-01
Contains abstracts from the 2002 conference of the North American Society for the Psychology of Sport and Physical Activity. The publication is divided into three sections: the preconference workshop, "Effective Teaching Methods in the Classroom;" symposia (motor development, motor learning and control, and sport psychology); and free…
ERIC Educational Resources Information Center
Proceedings of the ASIS Annual Meeting, 1995
1995-01-01
Presents abstracts of 15 special interest group (SIG) sessions. Topics include navigation and information utilization in the Internet, natural language processing, automatic indexing, image indexing, classification, users' models of database searching, online public access catalogs, education for information professions, information services,…
Gortais, Bernard
2003-01-01
In a given social context, artistic creation comprises a set of processes, which relate to the activity of the artist and the activity of the spectator. Through these processes we see and understand that the world is vaster than it is said to be. Artistic processes are mediated experiences that open up the world. A successful work of art expresses a reality beyond actual reality: it suggests an unknown world using the means and the signs of the known world. Artistic practices incorporate the means of creation developed by science and technology and change forms as they change. Artists and the public follow different processes of abstraction at different levels, in the definition of the means of creation, of representation and of perception of a work of art. This paper examines how the processes of abstraction are used within the framework of the visual arts and abstract painting, which appeared during a period of growing importance for the processes of abstraction in science and technology, at the beginning of the twentieth century. The development of digital platforms and new man-machine interfaces allow multimedia creations. This is performed under the constraint of phases of multidisciplinary conceptualization using generic representation languages, which tend to abolish traditional frontiers between the arts: visual arts, drama, dance and music. PMID:12903659
ERIC Educational Resources Information Center
Wilson, Cynthia, Ed.; Milliron, Mark David, Ed.
2002-01-01
This 2002 volume of Leadership Abstracts contains issue numbers 1-12. Articles include: (1) "Skills Certification and Workforce Development: Partnering with Industry and Ourselves," by Jeffrey A. Cantor; (2) "Starting Again: The Brookhaven Success College," by Alice W. Villadsen; (3) "From Digital Divide to Digital Democracy," by Gerardo E. de los…
Middlebrooks, E.J.
1982-01-01
Separate abstracts were prepared for the 31 chapters of this book which deals with all aspects of wastewater reuse. Design data, case histories, performance data, monitoring information, health information, social implications, legal and organizational structures, and background information needed to analyze the desirability of water reuse are presented. (KRM)
ERIC Educational Resources Information Center
Le Grice, Malcolm
A theoretical and historical account of the main preoccupations of makers of abstract films is presented in this book. The book's scope includes discussion of nonrepresentational forms as well as examination of experiments in the manipulation of time in films. The ten chapters discuss the following topics: art and cinematography, the first…
Valenzuela, Javier
2001-01-01
A radial flow heat exchanger (20) having a plurality of first passages (24) for transporting a first fluid (25) and a plurality of second passages (26) for transporting a second fluid (27). The first and second passages are arranged in stacked, alternating relationship, are separated from one another by relatively thin plates (30) and (32), and surround a central axis (22). The thickness of the first and second passages are selected so that the first and second fluids, respectively, are transported with laminar flow through the passages. To enhance thermal energy transfer between first and second passages, the latter are arranged so each first passage is in thermal communication with an associated second passage along substantially its entire length, and vice versa with respect to the second passages. The heat exchangers may be stacked to achieve a modular heat exchange assembly (300). Certain heat exchangers in the assembly may be designed slightly differently than other heat exchangers to address changes in fluid properties during transport through the heat exchanger, so as to enhance overall thermal effectiveness of the assembly.
Radial distribution function in polymers
NASA Astrophysics Data System (ADS)
Przygocki, Wladyslaw
1997-02-01
Radial distribution function is a very useful tool for determination of the polymer structure. The connection between the scattered X-ray intensity and radial distribution function is presented. Some examples of RDF for polyethylene and for poly(ethylene terephtalate).
Resection arthroplasty after failure of a radial head prosthesis: a case report
Vanni, Stefania; Marenco, Stefano; Calò, Michel; Battiston, Bruno
2016-01-01
Abstract Radial head represents a secondary elbow stabilizer for varus-valgus and postero-lateral stress. In complex fractures, that cannot be synthesized, the presence of associated ligament injuries makes radial head replacement necessary to restore elbow stability. This study evaluates how the elbow responds to a prosthetic removal after a complex injury repair. PMID:27583266
NASA Astrophysics Data System (ADS)
Allan, D. J.
The Abstract Data Interface (ADI) is a system within which both abstract data models and their mappings on to file formats can be defined. The data model system is object-oriented and closely follows the Common Lisp Object System (CLOS) object model. Programming interfaces in both C and \\fortran are supplied, and are designed to be simple enough for use by users with limited software skills. The prototype system supports access to those FITS formats most commonly used in the X-ray community, as well as the Starlink NDF data format. New interfaces can be rapidly added to the system---these may communicate directly with the file system, other ADI objects or elsewhere (e.g., a network connection).
Meeting Abstracts - Nexus 2015.
2015-10-01
The AMCP Abstracts program provides a forum through which authors can share their insights and outcomes of advanced managed care practice through publication in AMCP's Journal of Managed Care Specialty Pharmacy (JMCP). Of the abstracts accepted for publication, most are presented as posters, so interested AMCP meeting attendees can review findings and query authors. The main poster presentation is Tuesday, October 27, 2015; posters are also displayed on Wednesday, October 28, 2015. The AMCP Nexus 2015 in Orlando, Florida, is expected to attract more than 3,500 managed care pharmacists and other health care professionals who manage and evaluate drug therapies, develop and manage networks, and work with medical managers and information specialists to improve the care of all individuals enrolled in managed care programs. Abstracts were submitted in the following categories: Research Report: describe completed original research on managed care pharmacy services or health care interventions. Examples include (but are not limited to) observational studies using administrative claims, reports of the impact of unique benefit design strategies, and analyses of the effects of innovative administrative or clinical programs.Economic Model: describe models that predict the effect of various benefit design or clinical decisions on a population. For example, an economic model could be used to predict the budget impact of a new pharmaceutical product on a health care system. Solving Problems in Managed Care: describe the specific steps taken to introduce a needed change, develop and implement a new system or program, plan and organize an administrative function, or solve other types of problems in managed care settings. These abstracts describe a course of events; they do not test a hypothesis, but they may include data.
Generalized Abstract Symbolic Summaries
NASA Technical Reports Server (NTRS)
Person, Suzette; Dwyer, Matthew B.
2009-01-01
Current techniques for validating and verifying program changes often consider the entire program, even for small changes, leading to enormous V&V costs over a program s lifetime. This is due, in large part, to the use of syntactic program techniques which are necessarily imprecise. Building on recent advances in symbolic execution of heap manipulating programs, in this paper, we develop techniques for performing abstract semantic differencing of program behaviors that offer the potential for improved precision.
EBS Radionuclide Transport Abstraction
J. Prouty
2006-07-14
The purpose of this report is to develop and analyze the engineered barrier system (EBS) radionuclide transport abstraction model, consistent with Level I and Level II model validation, as identified in Technical Work Plan for: Near-Field Environment and Transport: Engineered Barrier System: Radionuclide Transport Abstraction Model Report Integration (BSC 2005 [DIRS 173617]). The EBS radionuclide transport abstraction (or EBS RT Abstraction) is the conceptual model used in the total system performance assessment (TSPA) to determine the rate of radionuclide releases from the EBS to the unsaturated zone (UZ). The EBS RT Abstraction conceptual model consists of two main components: a flow model and a transport model. Both models are developed mathematically from first principles in order to show explicitly what assumptions, simplifications, and approximations are incorporated into the models used in the TSPA. The flow model defines the pathways for water flow in the EBS and specifies how the flow rate is computed in each pathway. Input to this model includes the seepage flux into a drift. The seepage flux is potentially split by the drip shield, with some (or all) of the flux being diverted by the drip shield and some passing through breaches in the drip shield that might result from corrosion or seismic damage. The flux through drip shield breaches is potentially split by the waste package, with some (or all) of the flux being diverted by the waste package and some passing through waste package breaches that might result from corrosion or seismic damage. Neither the drip shield nor the waste package survives an igneous intrusion, so the flux splitting submodel is not used in the igneous scenario class. The flow model is validated in an independent model validation technical review. The drip shield and waste package flux splitting algorithms are developed and validated using experimental data. The transport model considers advective transport and diffusive transport
Focal spot analysis of radially polarized femtosecond laser pulses
NASA Astrophysics Data System (ADS)
Sun, Wenchao; Hu, Wenhua; Qi, Junli; Wang, Weiming; Liao, Jiali; Yi, Wenjun; Jia, Hui; Li, Xiujian
2014-09-01
When radially polarized light beams focus through high numerical-aperture lens, there will be a very strong longitudinal component of the light field near the focus. And, under the condition of certain system parameters, they can shape a spot which is over the focusing spot of the diffraction limit, which are the superiorities that linearly polarized light and circularly polarized light do not have. Besides, what we have found in the experiment is that radially polarized femtosecond laser pulses own the same superiorities, which provides the basis for using the focusing characteristics of radially polarized light beams under the condition of shorter and more powerful laser pulses. So far, although people have studied a lot on radially polarized light beams, this kind of light beams' focusing characters are rarely researched. What is worse, most research of its focusing characters still stays in the stage of theoretical simulation，and it seems that none of people have really studied it by the way of experiments. This article is precisely based on this. On the basis of predecessors' a lot of theoretical research, the article pays more attention on analyzing radially polarized light beams' focusing character through experiments. What's more, the article, based on femtosecond laser pulses, compares the differences of the focusing nature among linearly polarized light, circularly polarized light and radially polarized light. And it gets the conclusion that radially polarized femtosecond laser pulses have better focusing character in longitudinal light field, confirming the feasibility that radially polarized light beams can be used in the fields of pulling, catching, and accelerating particles, metal cutting and high-density storage.
EBS Radionuclide Transport Abstraction
J.D. Schreiber
2005-08-25
The purpose of this report is to develop and analyze the engineered barrier system (EBS) radionuclide transport abstraction model, consistent with Level I and Level II model validation, as identified in ''Technical Work Plan for: Near-Field Environment and Transport: Engineered Barrier System: Radionuclide Transport Abstraction Model Report Integration'' (BSC 2005 [DIRS 173617]). The EBS radionuclide transport abstraction (or EBS RT Abstraction) is the conceptual model used in the total system performance assessment for the license application (TSPA-LA) to determine the rate of radionuclide releases from the EBS to the unsaturated zone (UZ). The EBS RT Abstraction conceptual model consists of two main components: a flow model and a transport model. Both models are developed mathematically from first principles in order to show explicitly what assumptions, simplifications, and approximations are incorporated into the models used in the TSPA-LA. The flow model defines the pathways for water flow in the EBS and specifies how the flow rate is computed in each pathway. Input to this model includes the seepage flux into a drift. The seepage flux is potentially split by the drip shield, with some (or all) of the flux being diverted by the drip shield and some passing through breaches in the drip shield that might result from corrosion or seismic damage. The flux through drip shield breaches is potentially split by the waste package, with some (or all) of the flux being diverted by the waste package and some passing through waste package breaches that might result from corrosion or seismic damage. Neither the drip shield nor the waste package survives an igneous intrusion, so the flux splitting submodel is not used in the igneous scenario class. The flow model is validated in an independent model validation technical review. The drip shield and waste package flux splitting algorithms are developed and validated using experimental data. The transport model considers
NASA Astrophysics Data System (ADS)
Cook, M.
2015-12-01
(Abstract only) In 2012, Lowell Observatory launched The Lowell Amateur Research Initiative (LARI) to formally involve amateur astronomers in scientific research by bringing them to the attention of and helping professional astronomers with their astronomical research. One of the LARI projects is the BVRI photometric monitoring of Young Stellar Objects (YSOs), wherein amateurs obtain observations to search for new outburst events and characterize the colour evolution of previously identified outbursters. A summary of the scientific and organizational aspects of this LARI project, including its goals and science motivation, the process for getting involved with the project, a description of the team members, their equipment and methods of collaboration, and an overview of the programme stars, preliminary findings, and lessons learned is presented.
IEEE conference record -- Abstracts
Not Available
1994-01-01
This conference covers the following areas: computational plasma physics; vacuum electronic; basic phenomena in fully ionized plasmas; plasma, electron, and ion sources; environmental/energy issues in plasma science; space plasmas; plasma processing; ball lightning/spherical plasma configurations; plasma processing; fast wave devices; magnetic fusion; basic phenomena in partially ionized plasma; dense plasma focus; plasma diagnostics; basic phenomena in weakly ionized gases; fast opening switches; MHD; fast z-pinches and x-ray lasers; intense ion and electron beams; laser-produced plasmas; microwave plasma interactions; EM and ETH launchers; solid state plasmas and switches; intense beam microwaves; and plasmas for lighting. Separate abstracts were prepared for 416 papers in this conference.
Using radial NMR profiles to characterize pore size distributions
NASA Astrophysics Data System (ADS)
Deriche, Rachid; Treilhard, John
2012-02-01
Extracting information about axon diameter distributions in the brain is a challenging task which provides useful information for medical purposes; for example, the ability to characterize and monitor axon diameters would be useful in diagnosing and investigating diseases like amyotrophic lateral sclerosis (ALS)1 or autism.2 Three families of operators are defined by Ozarslan,3 whose action upon an NMR attenuation signal extracts the moments of the pore size distribution of the ensemble under consideration; also a numerical method is proposed to continuously reconstruct a discretely sampled attenuation profile using the eigenfunctions of the simple harmonic oscillator Hamiltonian: the SHORE basis. The work presented here extends Ozarlan's method to other bases that can offer a better description of attenuation signal behaviour; in particular, we propose the use of the radial Spherical Polar Fourier (SPF) basis. Testing is performed to contrast the efficacy of the radial SPF basis and SHORE basis in practical attenuation signal reconstruction. The robustness of the method to additive noise is tested and analysed. We demonstrate that a low-order attenuation signal reconstruction outperforms a higher-order reconstruction in subsequent moment estimation under noisy conditions. We propose the simulated annealing algorithm for basis function scale parameter estimation. Finally, analytic expressions are derived and presented for the action of the operators on the radial SPF basis (obviating the need for numerical integration, thus avoiding a spectrum of possible sources of error).
Writing a successful research abstract.
Bliss, Donna Z
2012-01-01
Writing and submitting a research abstract provides timely dissemination of the findings of a study and offers peer input for the subsequent development of a quality manuscript. Acceptance of abstracts is competitive. Understanding the expected content of an abstract, the abstract review process and tips for skillful writing will improve the chance of acceptance.
Radial lean direct injection burner
Khan, Abdul Rafey; Kraemer, Gilbert Otto; Stevenson, Christian Xavier
2012-09-04
A burner for use in a gas turbine engine includes a burner tube having an inlet end and an outlet end; a plurality of air passages extending axially in the burner tube configured to convey air flows from the inlet end to the outlet end; a plurality of fuel passages extending axially along the burner tube and spaced around the plurality of air passage configured to convey fuel from the inlet end to the outlet end; and a radial air swirler provided at the outlet end configured to direct the air flows radially toward the outlet end and impart swirl to the air flows. The radial air swirler includes a plurality of vanes to direct and swirl the air flows and an end plate. The end plate includes a plurality of fuel injection holes to inject the fuel radially into the swirling air flows. A method of mixing air and fuel in a burner of a gas turbine is also provided. The burner includes a burner tube including an inlet end, an outlet end, a plurality of axial air passages, and a plurality of axial fuel passages. The method includes introducing an air flow into the air passages at the inlet end; introducing a fuel into fuel passages; swirling the air flow at the outlet end; and radially injecting the fuel into the swirling air flow.
Radial Electromagnetic Press for Ignitor
NASA Astrophysics Data System (ADS)
Pizzuto, A.; Capriccioli, A.; Gasparotto, M.; Palmieri, A.; Rita, C.; Roccella, M.; Coppi, B.
1996-11-01
The active vertical press included so far in the Ignitor design can be substituted advantageously (e.g. in terms of the machine maintenance procedure) by a radial electromagnetic press, without involving modification of the main machine components. Only the bracing ring of the radial mechanical preloading system that is permanently applied requires some changes. The radial press has to compensate for the reduced ring load (from 200 MN to 120 MN) and the original vertical press load of 35 MN. To get an equivalent preloading system, the radial press load has to be 140 MN, which is 25 MN higher, to account for the lower efficiency of the radial load. The current needed to originate the 140 MN force is about 3.2 MA. The press is active for 2 s starting from the plasma current rise. The temperature increase is about 20 ^oC. The stray field at the plasma border is well within the allowable value and can be easily compensated by varying slightly the current of one couple of poloidal coils. The new machine layout is illustrated and the electromagnetic and mechanical analyses carried out for the new configuration are given. Sponsored by ENEA, CNR and ASP, of Italy, and by the US DoE
Stellar Presentations (Abstract)
NASA Astrophysics Data System (ADS)
Young, D.
2015-12-01
(Abstract only) The AAVSO is in the process of expanding its education, outreach and speakers bureau program. powerpoint presentations prepared for specific target audiences such as AAVSO members, educators, students, the general public, and Science Olympiad teams, coaches, event supervisors, and state directors will be available online for members to use. The presentations range from specific and general content relating to stellar evolution and variable stars to specific activities for a workshop environment. A presentation—even with a general topic—that works for high school students will not work for educators, Science Olympiad teams, or the general public. Each audience is unique and requires a different approach. The current environment necessitates presentations that are captivating for a younger generation that is embedded in a highly visual and sound-bite world of social media, twitter and U-Tube, and mobile devices. For educators, presentations and workshops for themselves and their students must support the Next Generation Science Standards (NGSS), the Common Core Content Standards, and the Science Technology, Engineering and Mathematics (STEM) initiative. Current best practices for developing relevant and engaging powerpoint presentations to deliver information to a variety of targeted audiences will be presented along with several examples.
Automated Supernova Discovery (Abstract)
NASA Astrophysics Data System (ADS)
Post, R. S.
2015-12-01
(Abstract only) We are developing a system of robotic telescopes for automatic recognition of Supernovas as well as other transient events in collaboration with the Puckett Supernova Search Team. At the SAS2014 meeting, the discovery program, SNARE, was first described. Since then, it has been continuously improved to handle searches under a wide variety of atmospheric conditions. Currently, two telescopes are used to build a reference library while searching for PSN with a partial library. Since data is taken every night without clouds, we must deal with varying atmospheric and high background illumination from the moon. Software is configured to identify a PSN, reshoot for verification with options to change the run plan to acquire photometric or spectrographic data. The telescopes are 24-inch CDK24, with Alta U230 cameras, one in CA and one in NM. Images and run plans are sent between sites so the CA telescope can search while photometry is done in NM. Our goal is to find bright PSNs with magnitude 17.5 or less which is the limit of our planned spectroscopy. We present results from our first automated PSN discoveries and plans for PSN data acquisition.
Burkhart, Klaus Josef; Wegmann, Kilian; Müller, Lars P; Gohlke, Frank E
2015-11-01
Radial head fractures are the most common fractures around the elbow. Because they are often accompanied by ligamentous injuries, we recommend considering them to be osteoligamentous injuries rather than simple fractures, even in undisplaced or minimally displaced fractures. Surgeons should always suspect and actively exclude concomitant ligament tears. The incidence of these associated injuries increases with greater severity of the radial head fracture. However, the standard Mason classification system does not adequately address this problem, and all attempts to establish a new classification system that provides concise treatment algorithms have failed. This article discusses the current treatment options and the current controversies in nonsurgical therapy, open reduction and internal fixation (ORIF) and radial head replacement. PMID:26498543
J.T. Birkholzer
2004-11-01
This model report documents the abstraction of drift seepage, conducted to provide seepage-relevant parameters and their probability distributions for use in Total System Performance Assessment for License Application (TSPA-LA). Drift seepage refers to the flow of liquid water into waste emplacement drifts. Water that seeps into drifts may contact waste packages and potentially mobilize radionuclides, and may result in advective transport of radionuclides through breached waste packages [''Risk Information to Support Prioritization of Performance Assessment Models'' (BSC 2003 [DIRS 168796], Section 3.3.2)]. The unsaturated rock layers overlying and hosting the repository form a natural barrier that reduces the amount of water entering emplacement drifts by natural subsurface processes. For example, drift seepage is limited by the capillary barrier forming at the drift crown, which decreases or even eliminates water flow from the unsaturated fractured rock into the drift. During the first few hundred years after waste emplacement, when above-boiling rock temperatures will develop as a result of heat generated by the decay of the radioactive waste, vaporization of percolation water is an additional factor limiting seepage. Estimating the effectiveness of these natural barrier capabilities and predicting the amount of seepage into drifts is an important aspect of assessing the performance of the repository. The TSPA-LA therefore includes a seepage component that calculates the amount of seepage into drifts [''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504], Section 6.3.3.1)]. The TSPA-LA calculation is performed with a probabilistic approach that accounts for the spatial and temporal variability and inherent uncertainty of seepage-relevant properties and processes. Results are used for subsequent TSPA-LA components that may handle, for example, waste package corrosion or radionuclide transport.
Liebmann, G H; Wollman, L; Woltmann, A G
1966-09-01
Abstract Eric Berne, M.D.: Games People Play. Grove Press, New York, 1964. 192 pages. Price $5.00. Reviewed by Hugo G. Beigel Finkle, Alex M., Ph.D., M.D. and Prian, Dimitry F. Sexual Potency in Elderly Men before and after Prostatectomy. J.A.M.A., 196: 2, April, 1966. Reviewed by H. George Liebman Calvin C. Hernton: Sex and Racism In America. Grove Press, Inc. Black Cat Edition No. 113 (Paperback), 1966, 180 pp. Price $.95. Reviewed by Gus Woltmann Hans Lehfeldt, M.D., Ernest W. Kulka, M.D., H. George Liebman, M.D.: Comparative Study of Uterine Contraceptive Devices. Obstetrics and Gynecology, 26: 5, 1965, pp. 679-688. Lawrence Lipton. The Erotic Revolution. Sherbourne Press, Los Angeles, 1965. 322 pp., Price $7.50. Masters, William H., M.D. and Johnson, Virginia E. Human Sexual Response. Boston: Little, Brown and Co., 1966. 366 pages. Price $.10.00. Reviewed by Hans Lehfeldt Douglas P. Murphy, M.D. and Editha F. Torrano, M.D. Male Fertility in 3620 Childless Couples. Fertility and Sterility, 16: 3, May-June, 1965. Reviewed by Leo Wollman, M.D. Edwin M. Schur, Editor: The Family and the Sexual Revolution, Indiana University Press, Bloomington, Indiana, 1964. 427 pgs. Weldon, Virginia F., M.D., Blizzard, Robert M., M.D., and Migeon, Claude, M.D. Newborn Girls Misdiagnosed as Bilaterally Chryptorchid Males. The New England Journal of Medicine, April 14, 1966. Reviewed by H. George Liebman.
Accepted scientific research works (abstracts).
2014-01-01
These are the 39 accepted abstracts for IAYT's Symposium on Yoga Research (SYR) September 24-24, 2014 at the Kripalu Center for Yoga & Health and published in the Final Program Guide and Abstracts. PMID:25645134
Not Available
1994-10-01
The increasing scale-up of fast pyrolysis in North America and Europe, as well as the exploration and expansion of markets for the energy use of biocrude oils that now needs to take place, suggested that it was timely to convene an international meeting on the properties and combustion behavior of these oils. A common understanding of the state-of-the-art and technical and other challenges which need to be met during the commercialization of biocrude fuel use, can be achieved. The technical issues and understanding of combustion of these oils are rapidly being advanced through R&D in the United States, Canada, Europe and Scandinavia. It is obvious that for the maximum economic impact of biocrude, it will be necessary to have a common set of specifications so that oils can be used interchangeably with engines and combustors which require minimal modification to use these renewable fuels. Fundamental and applied studies being pursued in several countries are brought together in this workshop so that we can arrive at common strategies. In this way, both the science and the commercialization are advanced to the benefit of all, without detracting from the competitive development of both the technology and its applications. This United States-Canada-Finland collaboration has led to the two and one half day specialists meeting at which the technical basis for advances in biocrude development is discussed. The goal is to arrive at a common agenda on issues that cross national boundaries in this area. Examples of agenda items are combustion phenomena, the behavior of trace components . of the oil (N, alkali metals), the formation of NO{sub x}, in combustion, the need for common standards and environmental safety and health issues in the handling, storage and transportation of biocrudes.
Parachute drag and radial force
Purvis, J.W.
1986-01-01
This paper presents a combination of old and new wind tunnel data in a format which illustrates the effects of inflated diameter, geometric porosity, reefing line length, suspension line length, number of gores, and number of ribbons on parachute drag. A new definition of radial force coefficient is presented, as well as a universal drag curve for flat circular and conical parachutes.
Radial thickness variations of Orientale basin ejecta
NASA Technical Reports Server (NTRS)
Cordell, B. M.
1978-01-01
Moore et al. (1974) measure the thickness of Orientale basin ejecta on the basis of filling of individual prebasin craters and a depth-diameter relation for fresh lunar craters. In the reported investigation the concept of filling of preexisting craters with basin ejecta is utilized somewhat differently to ascertain Orientale basin ejecta thicknesses and volume from the Cordillera ring with a radius of 450 km out to almost 2 radii. Briefly, the approach is to assume a reasonable geometric model for the form of Orientale ejecta, calculate how many pre-Orientale craters would be destroyed by the deposition of the ejecta, and match the model to Orientale crater statistics. The results of the investigation show that a radial ejecta thickness function can be derived from crater statistics.
Outcomes Following Radial Head Arthroplasty.
Fowler, John R; Henry, Sarah E; Xu, Peter; Goitz, Robert J
2016-05-01
Most current series of radial head arthroplasty include small numbers of patients with short- to medium-term follow-up and significant heterogeneity in patients, treatments, and outcome measures. The purpose of this systematic review was to review outcomes for radial head arthroplasty based on injury chronicity, injury pattern, and type of implant used. The authors systematically searched electronic databases for studies containing radial head arthroplasty or radial head replacement and identified 19 studies for inclusion in the analysis. For each included study, a composite mean was obtained for Mayo Elbow Performance Score (MEPS) and range of motion. Outcomes were said to differ significantly if their confidence intervals did not overlap. The MEPS for acute treatment (90) was higher than that for delayed treatment (81). There was no difference in the pooled MEPS between the isolated (89) and complex injury pattern (87) groups or implant material. There was no difference in range of motion between the acute and delayed or isolated and complex groups, but the average degree of pronation was higher in patients treated with titanium implants (76°) compared with cobalt chromium implants (66°). This systematic review suggests that outcomes are improved following acute arthroplasty for treatment of radial head fractures compared with delayed treatment, based on MEPS. The lack of other significant differences detected is likely due to the significant heterogeneity and inadequate power in current studies. Further prospective studies isolating the different variables will be needed to determine their true effect on outcomes. [Orthopedics. 2016; 39(3):153-160.]. PMID:27045484
Gevers, M; Van Genderingen, H R; Van der Mooren, K; Lafeber, H N; Hack, W W; Westerhof, N
1995-06-01
Previously, we found evidence that radial artery pressure wave forms in newborns represent central aortic wave forms, provided that pressure is measured with adequate accuracy. Therefore, we postulated that the neonatal radial artery wave form, like the adult aortic wave form, may contribute to cardiovascular diagnosis. We investigated whether radial artery wave forms in infants suffering from patent ductus arteriosus (PDA) are different from the wave forms as seen without the presence of PDA. We studied 34 newborn infants with a radial artery line and with the possible clinical diagnosis of PDA with left-to-right shunt. On the basis of echocardiographic examination to assess PDA, these infants were divided in two groups: infants with PDA (n = 24) and without PDA (n = 10). In 15 out of 24 infants with PDA, recordings were repeated after ductal closure. Blood pressure measurement was performed with a high fidelity cathetermanometer system using a tip-transducer (natural frequency 95 Hz, damping coefficient 0.15). Contour analysis was performed by describing morphology of the waves during PDA and without PDA. In 23 out of 24 infants with PDA, a pulsus bisferiens was present: two peaks separated by a deep cleft. The average pressure difference between the first pressure peak and the cleft [delta Ppeak1] was 0.35 +/- 0.19 kPa, and the average difference between the cleft and the second pressure peak [delta Ppeak2] was 0.44 +/- 0.23 kPa. the ratio of mean magnitude of delta Ppeak1 and delta Ppeak2 was 0.81 +/- 0.26. None of the 10 infants without PDA showed pulsus bisferiens.(ABSTRACT TRUNCATED AT 250 WORDS)
Using abstract language signals power.
Wakslak, Cheryl J; Smith, Pamela K; Han, Albert
2014-07-01
Power can be gained through appearances: People who exhibit behavioral signals of power are often treated in a way that allows them to actually achieve such power (Ridgeway, Berger, & Smith, 1985; Smith & Galinsky, 2010). In the current article, we examine power signals within interpersonal communication, exploring whether use of concrete versus abstract language is seen as a signal of power. Because power activates abstraction (e.g., Smith & Trope, 2006), perceivers may expect higher power individuals to speak more abstractly and therefore will infer that speakers who use more abstract language have a higher degree of power. Across a variety of contexts and conversational subjects in 7 experiments, participants perceived respondents as more powerful when they used more abstract language (vs. more concrete language). Abstract language use appears to affect perceived power because it seems to reflect both a willingness to judge and a general style of abstract thinking.
Grounding Abstractness: Abstract Concepts and the Activation of the Mouth
Borghi, Anna M.; Zarcone, Edoardo
2016-01-01
One key issue for theories of cognition is how abstract concepts, such as freedom, are represented. According to the WAT (Words As social Tools) proposal, abstract concepts activate both sensorimotor and linguistic/social information, and their acquisition modality involves the linguistic experience more than the acquisition of concrete concepts. We report an experiment in which participants were presented with abstract and concrete definitions followed by concrete and abstract target-words. When the definition and the word matched, participants were required to press a key, either with the hand or with the mouth. Response times and accuracy were recorded. As predicted, we found that abstract definitions and abstract words yielded slower responses and more errors compared to concrete definitions and concrete words. More crucially, there was an interaction between the target-words and the effector used to respond (hand, mouth). While responses with the mouth were overall slower, the advantage of the hand over the mouth responses was more marked with concrete than with abstract concepts. The results are in keeping with grounded and embodied theories of cognition and support the WAT proposal, according to which abstract concepts evoke linguistic-social information, hence activate the mouth. The mechanisms underlying the mouth activation with abstract concepts (re-enactment of acquisition experience, or re-explanation of the word meaning, possibly through inner talk) are discussed. To our knowledge this is the first behavioral study demonstrating with real words that the advantage of the hand over the mouth is more marked with concrete than with abstract concepts, likely because of the activation of linguistic information with abstract concepts. PMID:27777563
Radial coordinates for conformal blocks
NASA Astrophysics Data System (ADS)
Hogervorst, Matthijs; Rychkov, Slava
2013-05-01
We develop the theory of conformal blocks in CFTd expressing them as power series with Gegenbauer polynomial coefficients. Such series have a clear physical meaning when the conformal block is analyzed in radial quantization: individual terms describe contributions of descendants of a given spin. Convergence of these series can be optimized by a judicious choice of the radial quantization origin. We argue that the best choice is to insert the operators symmetrically. We analyze in detail the resulting “ρ-series” and show that it converges much more rapidly than for the commonly used variable z. We discuss how these conformal block representations can be used in the conformal bootstrap. In particular, we use them to derive analytically some bootstrap bounds whose existence was previously found numerically.
Abstract shape analysis of RNA.
Janssen, Stefan; Giegerich, Robert
2014-01-01
Abstract shape analysis abstract shape analysis is a method to learn more about the complete Boltzmann ensemble of the secondary structures of a single RNA molecule. Abstract shapes classify competing secondary structures into classes that are defined by their arrangement of helices. It allows us to compute, in addition to the structure of minimal free energy, a set of structures that represents relevant and interesting structural alternatives. Furthermore, it allows to compute probabilities of all structures within a shape class. This allows to ensure that our representative subset covers the complete Boltzmann ensemble, except for a portion of negligible probability. This chapter explains the main functions of abstract shape analysis, as implemented in the tool RNA shapes. RNA shapes It reports on some other types of analysis that are based on the abstract shapes idea and shows how you can solve novel problems by creating your own shape abstractions.
RADIAL STABILITY IN STRATIFIED STARS
Pereira, Jonas P.; Rueda, Jorge A. E-mail: jorge.rueda@icra.it
2015-03-01
We formulate within a generalized distributional approach the treatment of the stability against radial perturbations for both neutral and charged stratified stars in Newtonian and Einstein's gravity. We obtain from this approach the boundary conditions connecting any two phases within a star and underline its relevance for realistic models of compact stars with phase transitions, owing to the modification of the star's set of eigenmodes with respect to the continuous case.
Velocidades radiales en Collinder 121
NASA Astrophysics Data System (ADS)
Arnal, M.; Morrell, N.
Se han llevado a cabo observaciones espectroscópicas de unas treinta estrellas que son posibles miembros del cúmulo abierto Collinder 121. Las mismas fueron realizadas con el telescopio de 2.15m del Complejo Astronómico El Leoncito (CASLEO). El análisis de las velocidades radiales derivadas del material obtenido, confirma la realidad de Collinder 121, al menos desde el punto de vista cinemático. La velocidad radial baricentral (LSR) del cúmulo es de +17 ± 3 km.s-1. Esta velocidad coincide, dentro de los errores, con la velocidad radial (LSR) de la nebulosa anillo S308, la cual es de ~20 ± 10 km.s-1. Como S308 se encuentra físicamente asociada a la estrella Wolf-Rayet HD~50896, es muy probable que esta última sea un miembro de Collinder 121. Desde un punto de vista cinemático, la supergigante roja HD~50877 (K3Iab) también pertenecería a Collinder 121. Basándonos en la pertenencia de HD~50896 a Collinder 121, y en la interacción encontrada entre el viento de esta estrella y el medio interestelar circundante a la misma, se estima para este cúmulo una distancia del orden de 1 kpc.
Mechanical Engineering Department technical abstracts
Denney, R.M.
1982-07-01
The Mechanical Engineering Department publishes listings of technical abstracts twice a year to inform readers of the broad range of technical activities in the Department, and to promote an exchange of ideas. Details of the work covered by an abstract may be obtained by contacting the author(s). Overall information about current activities of each of the Department's seven divisions precedes the technical abstracts.
New measurements of radial velocities in clusters of galaxies. II
NASA Astrophysics Data System (ADS)
Proust, D.; Mazure, A.; Sodre, L.; Capelato, H.; Lund, G.
1988-03-01
Heliocentric radial velocities are determined for 100 galaxies in five clusters, on the basis of 380-518-nm observations obtained using a CCD detector coupled by optical fibers to the OCTOPUS multiobject spectrograph at the Cassegrain focus of the 3.6-m telescope at ESO La Silla. The data-reduction procedures and error estimates are discussed, and the results are presented in tables and graphs and briefly characterized.
Coevolution of radial glial cells and the cerebral cortex
De Juan Romero, Camino
2015-01-01
Abstract Radial glia cells play fundamental roles in the development of the cerebral cortex, acting both as the primary stem and progenitor cells, as well as the guides for neuronal migration and lamination. These critical functions of radial glia cells in cortical development have been discovered mostly during the last 15 years and, more recently, seminal studies have demonstrated the existence of a remarkable diversity of additional cortical progenitor cell types, including a variety of basal radial glia cells with key roles in cortical expansion and folding, both in ontogeny and phylogeny. In this review, we summarize the main cellular and molecular mechanisms known to be involved in cerebral cortex development in mouse, as the currently preferred animal model, and then compare these with known mechanisms in other vertebrates, both mammal and nonmammal, including human. This allows us to present a global picture of how radial glia cells and the cerebral cortex seem to have coevolved, from reptiles to primates, leading to the remarkable diversity of vertebrate cortical phenotypes. GLIA 2015;63:1303–1319 PMID:25808466
Innovation Abstracts; Volume XIV, 1992.
ERIC Educational Resources Information Center
Roueche, Suanne D., Ed.
1992-01-01
This series of 30 one- to two-page abstracts covering 1992 highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) faculty recognition and orientation; (2) the Amado M. Pena, Jr., Scholarship Program; (3) innovative teaching techniques, with individual abstracts…
Innovation Abstracts, Volume XV, 1993.
ERIC Educational Resources Information Center
Roueche, Suanne D., Ed.
1993-01-01
This volume of 30 one- to two-page abstracts from 1993 highlights a variety of innovative approaches to teaching and learning in the community college. Topics covered in the abstracts include: (1) role-playing to encourage critical thinking; (2) team learning techniques to cultivate business skills; (3) librarian-instructor partnerships to create…
Leadership Abstracts; Volume 4, 1991.
ERIC Educational Resources Information Center
Doucette, Don, Ed.
1991-01-01
"Leadership Abstracts" is published bimonthly and distributed to the chief executive officer of every two-year college in the United States and Canada. This document consists of the 15 one-page abstracts published in 1991. Addressing a variety of topics of interest to the community college administrators, this volume includes: (1) "Delivering the…
Student Success with Abstract Art
ERIC Educational Resources Information Center
Hamidou, Kristine
2009-01-01
An abstract art project can be challenging or not, depending on the objectives the teacher sets up. In this article, the author describes an abstract papier-mache project that is a success for all students, and is a versatile project easily manipulated to suit the classroom of any art teacher.
Abstraction in perceptual symbol systems.
Barsalou, Lawrence W
2003-01-01
After reviewing six senses of abstraction, this article focuses on abstractions that take the form of summary representations. Three central properties of these abstractions are established: ( i ) type-token interpretation; (ii) structured representation; and (iii) dynamic realization. Traditional theories of representation handle interpretation and structure well but are not sufficiently dynamical. Conversely, connectionist theories are exquisitely dynamic but have problems with structure. Perceptual symbol systems offer an approach that implements all three properties naturally. Within this framework, a loose collection of property and relation simulators develops to represent abstractions. Type-token interpretation results from binding a property simulator to a region of a perceived or simulated category member. Structured representation results from binding a configuration of property and relation simulators to multiple regions in an integrated manner. Dynamic realization results from applying different subsets of property and relation simulators to category members on different occasions. From this standpoint, there are no permanent or complete abstractions of a category in memory. Instead, abstraction is the skill to construct temporary online interpretations of a category's members. Although an infinite number of abstractions are possible, attractors develop for habitual approaches to interpretation. This approach provides new ways of thinking about abstraction phenomena in categorization, inference, background knowledge and learning. PMID:12903648
Food Science and Technology Abstracts.
ERIC Educational Resources Information Center
Cohen, Elinor; Federman, Joan
1979-01-01
Introduces the reader to the Food Science and Technology Abstracts, a data file that covers worldwide literature on human food commodities and aspects of food processing. Topics include scope, subject index, thesaurus, searching online, and abstracts; tables provide a comparison of ORBIT and DIALOG versions of the file. (JD)
Technical abstracts: Mechanical engineering, 1990
Broesius, J.Y.
1991-03-01
This document is a compilation of the published, unclassified abstracts produced by mechanical engineers at Lawrence Livermore National Laboratory (LLNL) during the calendar year 1990. Many abstracts summarize work completed and published in report form. These are UCRL-JC series documents, which include the full text of articles to be published in journals and of papers to be presented at meetings, and UCID reports, which are informal documents. Not all UCIDs contain abstracts: short summaries were generated when abstracts were not included. Technical Abstracts also provides descriptions of those documents assigned to the UCRL-MI (miscellaneous) category. These are generally viewgraphs or photographs presented at meetings. An author index is provided at the back of this volume for cross referencing.
Metaphor: Bridging embodiment to abstraction.
Jamrozik, Anja; McQuire, Marguerite; Cardillo, Eileen R; Chatterjee, Anjan
2016-08-01
Embodied cognition accounts posit that concepts are grounded in our sensory and motor systems. An important challenge for these accounts is explaining how abstract concepts, which do not directly call upon sensory or motor information, can be informed by experience. We propose that metaphor is one important vehicle guiding the development and use of abstract concepts. Metaphors allow us to draw on concrete, familiar domains to acquire and reason about abstract concepts. Additionally, repeated metaphoric use drawing on particular aspects of concrete experience can result in the development of new abstract representations. These abstractions, which are derived from embodied experience but lack much of the sensorimotor information associated with it, can then be flexibly applied to understand new situations. PMID:27294425
Gandelman, Kuan; Lamson, Michael; Bramson, Candace; Matschke, Kyle; Salageanu, Joanne; Malhotra, Bimal
2015-09-01
ALO-02 capsules (ALO-02) contain pellets that consist of extended-release oxycodone that surrounds sequestered naltrexone. The primary objective was to characterize the pharmacokinetics (PK) of oxycodone following single- and multiple-dose oral administration of ALO-02 40 mg BID in healthy volunteers. Secondary objectives were to characterize (1) the PK of oxycodone following single- and multiple-dose administration of a comparator OxyContin (OXY-ER) 40 mg BID as well as an alternate regimen of ALO-02 80 mg QD, and (2) the safety and tolerability assessments. Healthy volunteers received three treatments on a background of oral naltrexone (50 mg). Noncompartmental PK parameters were calculated for oxycodone. All 12 subjects were male with a mean age (SD, range) of 44.6 years (7.6, 25-55). Single-dose PK results for ALO-02 indicate that median peak plasma oxycodone concentrations were reached by 12 hours compared to 4 hours for OXY-ER. Compared to OXY-ER, mean dose-normalized, single-dose Cmax values were approximately 27% and 23% lower for ALO-02 40 mg BID and ALO-02 80 mg QD treatments, respectively. Following multiple doses all treatments reached steady state by 3 days. At steady state, oxycodone peak-to-trough fluctuation was significantly lower for ALO-02 BID versus OXY-ER. Adverse events were consistent with opioid therapy. ALO-02 40 mg BID treatment provided a PK profile appropriate for around-the-clock treatment of chronic pain. PMID:27137145
PRECISION RADIAL VELOCITIES WITH CSHELL
Crockett, Christopher J.; Prato, L.; Mahmud, Naved I.; Johns-Krull, Christopher M.; Jaffe, Daniel T.; Beichman, Charles A. E-mail: lprato@lowell.edu E-mail: cmj@rice.edu
2011-07-10
Radial velocity (RV) identification of extrasolar planets has historically been dominated by optical surveys. Interest in expanding exoplanet searches to M dwarfs and young stars, however, has motivated a push to improve the precision of near-infrared RV techniques. We present our methodology for achieving 58 m s{sup -1} precision in the K band on the M0 dwarf GJ 281 using the CSHELL spectrograph at the 3 m NASA Infrared Telescope Facility. We also demonstrate our ability to recover the known 4 M{sub JUP} exoplanet Gl 86 b and discuss the implications for success in detecting planets around 1-3 Myr old T Tauri stars.
Outcome of Radial Head Arthroplasty in Comminuted Radial Head Fractures: Short and Midterm Results
Moghaddam, Arash; Raven, Tim Friedrich; Dremel, Eike; Studier-Fischer, Stefan; Grutzner, Paul Alfred; Biglari, Bahram
2016-01-01
Background: Comminuted radial head fractures are often associated with secondary injuries and elbow instability. Objectives: The aim of this retrospective study was to evaluate how well the modular metallic radial head implant EVOLVE® prosthesis restores functional range of motion (ROM) and stability of the elbow in acute care. Patients and Methods: Eighty-five patients with comminuted radial head fractures and associated injuries received treatment with an EVOLVE® prosthesis between May 2001 and November 2009. Seventy-five patients were available for follow-up. On average, patients were followed for 41.5 months (33.0: 4.0 - 93.0). Outcome assessment was done on the basis of pain, ROM, strength, radiographic findings, and functional rating scores such as Broberg and Morrey, the Mayo elbow performance index (MEPI), and disabilities of the arm, shoulder and hand (DASH). Our study is currently the largest analysis of clinical outcome of a modular radial head replacement in the literature. Results: Overall, there were 2 (2.7%) Mason II fractures, 21 (28%) Mason III fractures, and 52 (69.3%) Mason IV fractures. Arbeitsgemeinschaft fur osteosynthesefragen (AO) classification was also determined. Of the 85 patients in our study, 75 were available for follow-up. Follow-up averaged 41.5 months (range, 4 - 93 months). Average scores for the cohort were as follows: Morrey, 85.7 (median 90.2; range 44.4 - 100); MEPI, 83.3 (85.0; 40.0 - 100); and DASH 26.1 points (22.5; 0.0 - 75.8). Mean flexion/extension in the affected joint was 125.7°/16.5°/0° in comparison to the noninjured side 138.5°/0°/1.2°. Mean pronation/supination was 70.5°/0°/67.1° in comparison to the noninjured side 83.6°/0°/84.3°. Handgrip strength of the injured compared to the non-injured arm was 78.8%. The following complications were also documented: 58 patients had periprosthetic radioluceny shown to be neither clinically significant nor relevant according to evaluated scores; 26 patients had
NASA Technical Reports Server (NTRS)
1982-01-01
Abstracts are cited for 87 patents and applications introduced into the NASA scientific and technical information system during the period of January 1982 through June 1982. Each entry consists of a citation, an abstract, and in mose cases, a key illustration selected from the patent or patent application.
Development and Testing of a Radial Halbach Magnetic Bearing
NASA Technical Reports Server (NTRS)
Eichenberg, Dennis J.; Gallo, Christopher A.; Thompson, William K.
2006-01-01
The NASA John H. Glenn Research Center has developed and tested a revolutionary Radial Halbach Magnetic Bearing. The objective of this work is to develop a viable non-contact magnetic bearing utilizing Halbach arrays for all-electric flight, and many other applications. This concept will help reduce harmful emissions, reduce the Nation s dependence on fossil fuels and mitigate many of the concerns and limitations encountered in conventional axial bearings such as bearing wear, leaks, seals and friction loss. The Radial Halbach Magnetic Bearing is inherently stable and requires no active feedback control system or superconductivity as required in many magnetic bearing designs. The Radial Halbach Magnetic Bearing is useful for very high speed applications including turbines, instrumentation, medical applications, manufacturing equipment, and space power systems such as flywheels. Magnetic fields suspend and support a rotor assembly within a stator. Advanced technologies developed for particle accelerators, and currently under development for maglev trains and rocket launchers, served as the basis for this application. Experimental hardware was successfully designed and developed to validate the basic principles and analyses. The report concludes that the implementation of Radial Halbach Magnetic Bearings can provide significant improvements in rotational system performance and reliability.
Microdrilling in steel using ultrashort pulsed laser beams with radial and azimuthal polarization.
Kraus, Martin; Ahmed, Marwan Abdou; Michalowski, Andreas; Voss, Andreas; Weber, Rudolf; Graf, Thomas
2010-10-11
A linear to radial and/or azimuthal polarization converter (LRAC) has been inserted into the beam delivery of a micromachining station equipped with a picosecond laser system. Percussion drilling and helical drilling in steel have been performed using radially as well as azimuthally polarized infrared radiation at 1030 nm. The presented machining results are discussed on the basis of numerical simulations of the polarization-dependent beam propagation inside the fabricated capillaries.
Deformation Mechanisms in Tube Billets from Zr-1%Nb Alloy under Radial Forging
Perlovich, Yuriy; Isaenkova, Margarita; Fesenko, Vladimir; Krymskaya, Olga; Zavodchikov, Alexander
2011-05-04
Features of the deformation process by cold radial forging of tube billets from Zr-1%Nb alloy were reconstructed on the basis of X-ray data concerning their structure and texture. The cold radial forging intensifies grain fragmentation in the bulk of billet and increases significantly the latent hardening of potentially active slip systems, so that operation only of the single slip system becomes possible. As a result, in radially-forged billets unusual deformation and recrystallization textures arise. These textures differ from usual textures of {alpha}-Zr by the mutual inversion of crystallographic axes, aligned along the axis of tube.
Deformation Mechanisms in Tube Billets from Zr-1%Nb Alloy under Radial Forging
NASA Astrophysics Data System (ADS)
Perlovich, Yuriy; Isaenkova, Margarita; Fesenko, Vladimir; Krymskaya, Olga; Zavodchikov, Alexander
2011-05-01
Features of the deformation process by cold radial forging of tube billets from Zr-1%Nb alloy were reconstructed on the basis of X-ray data concerning their structure and texture. The cold radial forging intensifies grain fragmentation in the bulk of billet and increases significantly the latent hardening of potentially active slip systems, so that operation only of the single slip system becomes possible. As a result, in radially-forged billets unusual deformation and recrystallization textures arise. These textures differ from usual textures of α-Zr by the mutual inversion of crystallographic axes, aligned along the axis of tube.
VanOsdol, John G.
2013-06-25
The disclosure provides a pulse jet mixing vessel for mixing a plurality of solid particles. The pulse jet mixing vessel is comprised of a sludge basin, a flow surface surrounding the sludge basin, and a downcoming flow annulus between the flow surface and an inner shroud. The pulse jet mixing vessel is additionally comprised of an upper vessel pressurization volume in fluid communication with the downcoming flow annulus, and an inner shroud surge volume separated from the downcoming flow annulus by the inner shroud. When the solid particles are resting on the sludge basin and a fluid such as water is atop the particles and extending into the downcoming flow annulus and the inner shroud surge volume, mixing occurs by pressurization of the upper vessel pressurization volume, generating an inward radial flow over the flow surface and an upwash jet at the center of the sludge basin.
Radial superlattices and single nanoreactors
NASA Astrophysics Data System (ADS)
Deneke, Ch.; Jin-Phillipp, N.-Y.; Loa, I.; Schmidt, O. G.
2004-05-01
We investigate the wall structure and thermal stability of individual freestanding rolled-up nanotubes (RUNTs) using micro-Raman spectroscopy, transmission electron microscopy, and selected area electron diffraction. Our studies reveal that the walls of the InAs/GaAs RUNTs consist of a radial superlattice comprising alternating crystalline and noncrystalline layers. Furthermore, we locally heated individual RUNTs with a laser beam, and Raman spectroscopy was used in situ to monitor any structural changes. At about 300 °C the heated part of a RUNT starts to oxidize and eventually transforms into crystalline β-Ga2O3. This result shows that RUNTs can serve as nanoreactors that locally synthesize material at intentional places on a substrate surface.
Stirling Engine With Radial Flow Heat Exchangers
NASA Technical Reports Server (NTRS)
Vitale, N.; Yarr, George
1993-01-01
Conflict between thermodynamical and structural requirements resolved. In Stirling engine of new cylindrical configuration, regenerator and acceptor and rejector heat exchangers channel flow of working gas in radial direction. Isotherms in regenerator ideally concentric cylinders, and gradient of temperature across regenerator radial rather than axial. Acceptor and rejector heat exchangers located radially inward and outward of regenerator, respectively. Enables substantial increase in power of engine without corresponding increase in diameter of pressure vessel.
Hollow Cathode With Multiple Radial Orifices
NASA Technical Reports Server (NTRS)
Brophy, John R.
1992-01-01
Improved hollow cathode serving as source of electrons has multiple radial orifices instead of single axial orifice. Distributes ion current more smoothly, over larger area. Prototype of high-current cathodes for ion engines in spacecraft. On Earth, cathodes used in large-diameter ion sources for industrial processing of materials. Radial orientation of orifices in new design causes current to be dispersed radially in vicinity of cathode. Advantageous where desireable to produce plasma more nearly uniform over wider region around cathode.
Sphericity measurements by the radial method: I. Mathematical fundamentals
NASA Astrophysics Data System (ADS)
Janecki, D.; Stępień, K.; Adamczak, S.
2016-01-01
Traditionally, form errors of spherical components have been assessed on the basis of roundness profiles measured in several randomly selected cross-sections. However, such evaluation is superficial, especially if there are significant local irregularities. A new concept was thus developed at the Kielce University of Technology to enable measurement of spherical specimens along some predefined paths so that the surface is densely covered with a grid of points. This approach assumes that measurements can be performed using a typical radial roundness measuring instrument equipped with a special mechanism for controlled positioning of a measured element. This work discusses the assumptions of the new concept and describes a mathematical model of sphericity measurement by the radial method.
Modelling Metamorphism by Abstract Interpretation
NASA Astrophysics Data System (ADS)
Dalla Preda, Mila; Giacobazzi, Roberto; Debray, Saumya; Coogan, Kevin; Townsend, Gregg M.
Metamorphic malware apply semantics-preserving transformations to their own code in order to foil detection systems based on signature matching. In this paper we consider the problem of automatically extract metamorphic signatures from these malware. We introduce a semantics for self-modifying code, later called phase semantics, and prove its correctness by showing that it is an abstract interpretation of the standard trace semantics. Phase semantics precisely models the metamorphic code behavior by providing a set of traces of programs which correspond to the possible evolutions of the metamorphic code during execution. We show that metamorphic signatures can be automatically extracted by abstract interpretation of the phase semantics, and that regular metamorphism can be modelled as finite state automata abstraction of the phase semantics.
Abstraction and natural language semantics.
Kayser, Daniel
2003-01-01
According to the traditional view, a word prototypically denotes a class of objects sharing similar features, i.e. it results from an abstraction based on the detection of common properties in perceived entities. I explore here another idea: words result from abstraction of common premises in the rules governing our actions. I first argue that taking 'inference', instead of 'reference', as the basic issue in semantics does matter. I then discuss two phenomena that are, in my opinion, particularly difficult to analyse within the scope of traditional semantic theories: systematic polysemy and plurals. I conclude by a discussion of my approach, and by a summary of its main features. PMID:12903662
Abstract communication for coordinated planning
NASA Technical Reports Server (NTRS)
Clement, Bradley J.; Durfee, Edmund H.
2003-01-01
work offers evidence that distributed planning agents can greatly reduce communication costs by reasoning at abstract levels. While it is intuitive that improved search can reduce communication in such cases, there are other decisions about how to communicate plan information that greatly affect communication costs. This paper identifies cases independent of search where communicating at multiple levels of abstraction can exponentially decrease costs and where it can exponentially add costs. We conclude with a process for determining appropriate levels of communication based on characteristics of the domain.
A catalog of rotational and radial velocities for evolved stars
NASA Astrophysics Data System (ADS)
de Medeiros, J. R.; Mayor, M.
1999-11-01
Rotational and radial velocities have been measured for about 2000 evolved stars of luminosity classes IV, III, II and Ib covering the spectral region F, G and K. The survey was carried out with the CORAVEL spectrometer. The precision for the radial velocities is better than 0.30 km s-1, whereas for the rotational velocity measurements the uncertainties are typically 1.0 km s-1 for subgiants and giants and 2.0 km s-1 for class II giants and Ib supergiants. These data will add constraints to studies of the rotational behaviour of evolved stars as well as solid informations concerning the presence of external rotational brakes, tidal interactions in evolved binary systems and on the link between rotation, chemical abundance and stellar activity. In this paper we present the rotational velocity v sin i and the mean radial velocity for the stars of luminosity classes IV, III and II. Based on observations collected at the Haute--Provence Observatory, Saint--Michel, France and at the European Southern Observatory, La Silla, Chile. Table \\ref{tab5} also available in electronic form at CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/Abstract.html
Radial head button holing: a cause of irreducible anterior radial head dislocation.
Shin, Su-Mi; Chai, Jee Won; You, Ja Yeon; Park, Jina; Bae, Kee Jeong
2016-10-01
"Buttonholing" of the radial head through the anterior joint capsule is a known cause of irreducible anterior radial head dislocation associated with Monteggia injuries in pediatric patients. To the best of our knowledge, no report has described an injury consisting of buttonholing of the radial head through the annular ligament and a simultaneous radial head fracture in an adolescent. In the present case, the radiographic findings were a radial head fracture with anterior dislocation and lack of the anterior fat pad sign. Magnetic resonance imaging (MRI) clearly demonstrated anterior dislocation of the fractured radial head through the torn annular ligament. The anterior joint capsule and proximal portion of the annular ligament were interposed between the radial head and capitellum, preventing closed reduction of the radial head. Familiarity with this condition and imaging findings will aid clinicians to make a proper diagnosis and fast decision to perform an open reduction. PMID:27502623
Handedness Shapes Children's Abstract Concepts
ERIC Educational Resources Information Center
Casasanto, Daniel; Henetz, Tania
2012-01-01
Can children's handedness influence how they represent abstract concepts like "kindness" and "intelligence"? Here we show that from an early age, right-handers associate rightward space more strongly with positive ideas and leftward space with negative ideas, but the opposite is true for left-handers. In one experiment, children indicated where on…
Rolloff Roof Observatory Construction (Abstract)
NASA Astrophysics Data System (ADS)
Ulowetz, J. H.
2015-12-01
(Abstract only) Lessons learned about building an observatory by someone with limited construction experience, and the advantages of having one for imaging and variable star studies. Sample results shown of composite light curves for cataclysmic variables UX UMa and V1101 Aql with data from my observatory combined with data from others around the world.
Innovation Abstracts, Volume XX, 1998.
ERIC Educational Resources Information Center
Roueche, Suanne D., Ed.
1998-01-01
The 52 abstracts in these 29 serial issues describe innovative approaches to teaching and learning in the community college. Sample topics include reading motivation, barriers to academic success, the learning environment, writing skills, leadership in the criminal justice profession, role-playing strategies, cooperative education, distance…
ERGONOMICS ABSTRACTS 48347-48982.
ERIC Educational Resources Information Center
Ministry of Technology, London (England). Warren Spring Lab.
IN THIS COLLECTION OF ERGONOMICS ABSTRACTS AND ANNOTATIONS THE FOLLOWING AREAS OF CONCERN ARE REPRESENTED--GENERAL REFERENCES, METHODS, FACILITIES, AND EQUIPMENT RELATING TO ERGONOMICS, SYSTEMS OF MAN AND MACHINES, VISUAL, AUDITORY, AND OTHER SENSORY INPUTS AND PROCESSES (INCLUDING SPEECH AND INTELLIGIBILITY), INPUT CHANNELS, BODY MEASUREMENTS,…
Does "Social Work Abstracts" Work?
ERIC Educational Resources Information Center
Holden, Gary; Barker, Kathleen; Covert-Vail, Lucinda; Rosenberg, Gary; Cohen, Stephanie A.
2008-01-01
Objective: The current study seeks to provide estimates of the adequacy of journal coverage in the Social Work Abstracts (SWA) database. Method: A total of 23 journals listed in the Journal Citation Reports social work category during the 1997 to 2005 period were selected for study. Issue-level coverage estimates were obtained for SWA and…
Abstract Expressionism. Clip and Save.
ERIC Educational Resources Information Center
Hubbard, Guy
2002-01-01
Provides information on the art movement, Abstract Expressionism, and includes learning activities. Focuses on the artist Jackson Pollock, offering a reproduction of his artwork, "Convergence: Number 10." Includes background information on the life and career of Pollock and a description of the included artwork. (CMK)
Conference Abstracts: Microcomputers in Education.
ERIC Educational Resources Information Center
Baird, William E.
1985-01-01
Provides abstracts of five papers presented at the Fourth Annual Microcomputers in Education Conference. Papers considered microcomputers in science laboratories, Apple II Plus/e computer-assisted instruction in chemistry, computer solutions for space mechanics concerns, computer applications to problem solving and hypothesis testing, and…
Metaphoric Images from Abstract Concepts.
ERIC Educational Resources Information Center
Vizmuller-Zocco, Jana
1992-01-01
Discusses children's use of metaphors to create meaning, using as an example the pragmatic and "scientific" ways in which preschool children explain thunder and lightning to themselves. Argues that children are being shortchanged by modern scientific notions of abstractness and that they should be encouraged to create their own explanations of…
What Is It? Elementary Abstraction
ERIC Educational Resources Information Center
Von Sossan, Joanne
2010-01-01
Abstraction can be hard for older students to understand, and it usually involves simplifying or rearranging natural objects to meet the needs of the artist, whether it be for organization or expression. But, in reality, that is what young artists do when they draw from life. They do not have enough experience--and sometimes the patience--to see…
Object Classification via Planar Abstraction
NASA Astrophysics Data System (ADS)
Oesau, Sven; Lafarge, Florent; Alliez, Pierre
2016-06-01
We present a supervised machine learning approach for classification of objects from sampled point data. The main idea consists in first abstracting the input object into planar parts at several scales, then discriminate between the different classes of objects solely through features derived from these planar shapes. Abstracting into planar shapes provides a means to both reduce the computational complexity and improve robustness to defects inherent to the acquisition process. Measuring statistical properties and relationships between planar shapes offers invariance to scale and orientation. A random forest is then used for solving the multiclass classification problem. We demonstrate the potential of our approach on a set of indoor objects from the Princeton shape benchmark and on objects acquired from indoor scenes and compare the performance of our method with other point-based shape descriptors.
Abstraction of Seepage into Drifts
WILSON,MICHAEL L.; HO,CLIFFORD K.
2000-10-16
The abstraction model used for seepage into emplacement drifts in recent TSPA simulations has been presented. This model contributes to the calculation of the quantity of water that might contact waste if it is emplaced at Yucca Mountain. Other important components of that calculation not discussed here include models for climate, infiltration, unsaturated-zone flow, and thermohydrology; drip-shield and waste-package degradation; and flow around and through the drip shield and waste package. The seepage abstraction model is stochastic because predictions of seepage are necessarily quite uncertain. The model provides uncertainty distributions for seepage fraction fraction of waste-package locations flow rate as functions of percolation flux. In addition, effects of intermediate-scale flow with seepage and seep channeling are included by means of a flow-focusing factor, which is also represented by an uncertainty distribution.
An Abstract Plan Preparation Language
NASA Technical Reports Server (NTRS)
Butler, Ricky W.; Munoz, Cesar A.
2006-01-01
This paper presents a new planning language that is more abstract than most existing planning languages such as the Planning Domain Definition Language (PDDL) or the New Domain Description Language (NDDL). The goal of this language is to simplify the formal analysis and specification of planning problems that are intended for safety-critical applications such as power management or automated rendezvous in future manned spacecraft. The new language has been named the Abstract Plan Preparation Language (APPL). A translator from APPL to NDDL has been developed in support of the Spacecraft Autonomy for Vehicles and Habitats Project (SAVH) sponsored by the Explorations Technology Development Program, which is seeking to mature autonomy technology for application to the new Crew Exploration Vehicle (CEV) that will replace the Space Shuttle.
Cooling characteristics of air cooled radial turbine blades
NASA Astrophysics Data System (ADS)
Sato, T.; Takeishi, K.; Matsuura, M.; Miyauchi, J.
The cooling design and the cooling characteristics of air cooled radial turbine wheels, which are designed for use with the gas generator turbine for the 400 horse power truck gas turbine engine, are presented. A high temperature and high speed test was performed under aerodynamically similar conditions to that of the prototype engine in order to confirm the metal temperature of the newly developed integrated casting wheels constructed of the superalloys INCO 713C. The test results compared with the analytical value, which was established on the basis of the results of the heat transfer test and the water flow test, are discussed.
Cryogenic foam insulation: Abstracted publications
NASA Technical Reports Server (NTRS)
Williamson, F. R.
1977-01-01
A group of documents were chosen and abstracted which contain information on the properties of foam materials and on the use of foams as thermal insulation at cryogenic temperatures. The properties include thermal properties, mechanical properties, and compatibility properties with oxygen and other cryogenic fluids. Uses of foams include applications as thermal insulation for spacecraft propellant tanks, and for liquefied natural gas storage tanks and pipelines.
Radial-probe EBUS for the diagnosis of peripheral pulmonary lesions
Jacomelli, Marcia; Demarzo, Sergio Eduardo; Cardoso, Paulo Francisco Guerreiro; Palomino, Addy Lidvina Mejia; Figueiredo, Viviane Rossi
2016-01-01
ABSTRACT Objective: Conventional bronchoscopy has a low diagnostic yield for peripheral pulmonary lesions. Radial-probe EBUS employs a rotating ultrasound transducer at the end of a probe that is passed through the working channel of the bronchoscope. Radial-probe EBUS facilitates the localization of peripheral pulmonary nodules, thus increasing the diagnostic yield. The objective of this study was to present our initial experience using radial-probe EBUS in the diagnosis of peripheral pulmonary lesions at a tertiary hospital. Methods: We conducted a retrospective analysis of 54 patients who underwent radial-probe EBUS-guided bronchoscopy for the investigation of pulmonary nodules or masses between February of 2012 and September of 2013. Radial-probe EBUS was performed with a flexible 20-MHz probe, which was passed through the working channel of the bronchoscope and advanced through the bronchus to the target lesion. For localization of the lesion and for collection procedures (bronchial brushing, transbronchial needle aspiration, and transbronchial biopsy), we used fluoroscopy. Results: Radial-probe EBUS identified 39 nodules (mean diameter, 1.9 ∓ 0.7 cm) and 19 masses (mean diameter, 4.1 ∓ 0.9 cm). The overall sensitivity of the method was 66.7% (79.5% and 25.0%, respectively, for lesions that were visible and not visible by radial-probe EBUS). Among the lesions that were visible by radial-probe EBUS, the sensitivity was 91.7% for masses and 74.1% for nodules. The complications were pneumothorax (in 3.7%) and bronchial bleeding, which was controlled bronchoscopically (in 9.3%). Conclusions: Radial-probe EBUS shows a good safety profile, a low complication rate, and high sensitivity for the diagnosis of peripheral pulmonary lesions.
Current Abstracts Nuclear Reactors and Technology
Bales, J.D.; Hicks, S.C.
1993-01-01
This publication Nuclear Reactors and Technology (NRT) announces on a monthly basis the current worldwide information available from the open literature on nuclear reactors and technology, including all aspects of power reactors, components and accessories, fuel elements, control systems, and materials. This publication contains the abstracts of DOE reports, journal articles, conference papers, patents, theses, and monographs added to the Energy Science and Technology Database during the past month. Also included are US information obtained through acquisition programs or interagency agreements and international information obtained through acquisition programs or interagency agreements and international information obtained through the International Energy Agency`s Energy Technology Data Exchange or government-to-government agreements. The digests in NRT and other citations to information on nuclear reactors back to 1948 are available for online searching and retrieval on the Energy Science and Technology Database and Nuclear Science Abstracts (NSA) database. Current information, added daily to the Energy Science and Technology Database, is available to DOE and its contractors through the DOE Integrated Technical Information System. Customized profiles can be developed to provide current information to meet each user`s needs.
Radial force development during root growth measured by photoelasticity
NASA Astrophysics Data System (ADS)
Kolb, Evelyne; Hartmann, Christian; Genet, Patricia
2012-02-01
The mechanical and topological properties of a soil like the global porosity and the distribution of void sizes greatly affect the development of a plant root, which in turn affects the shoot development. In particular, plant roots growing in heterogeneous medium like sandy soils or cracked substrates have to adapt their morphology and exert radial forces depending on the pore size in which they penetrate. We propose a model experiment in which a pivot root (chick-pea seeds) of millimetric diameter has to grow in a size-controlled gap δ (δ ranging 0.5-2.3 mm) between two photoelastic grains. By time-lapse imaging, we continuously monitored the root growth and the development of optical fringes in the photoelastic neighbouring grains when the root enters the gap. Thus we measured simultaneously and in situ the root morphological changes (length and diameter growth rates, circumnutation) as well as the radial forces the root exerts. Radial forces were increasing in relation with gap constriction and experiment duration but a levelling of the force was not observed, even after 5 days and for narrow gaps. The inferred mechanical stress was consistent with the turgor pressure of compressed cells. Therefore our set-up could be a basis for testing mechanical models of cellular growth.
A dialectical approach to the formation of mathematical abstractions
NASA Astrophysics Data System (ADS)
Ozmantar, Mehmet Fatih; Monaghan, John
2007-09-01
This paper is structured in two sections. The first examines views of mathematical abstraction in two broad categories: empiricist and dialectical accounts. It documents the difficulties involved in and explores the potentialities of both accounts. Then it outlines a recent model which takes a dialectical materialist approach to abstraction in context. This model constitutes the basis of the second section where we describe an empirical study designed to investigate mathematical abstraction in socially rich (e.g., peer-interacted and tutor-assisted) environments. We then present data on two students working with the help of a tutor on tasks concerned with graphs of absolute value functions. On the basis of these data, we discuss four particular themes which are relevant to the purpose of this special issue and are important in the discussion of mathematical abstraction: human and artefact mediation, tutor interventions in assisting the formation of mathematical abstractions, implications of a dialectical view on student development, and the things that are abstracted.
[Primary radial head arthroplasty in trauma : Complications].
Schmidt-Horlohé, K; Buschbeck, S; Wincheringer, D; Weißenberger, M; Hoffmann, R
2016-10-01
Radial head fractures are common injuries in elbow trauma. Non-displaced fractures are best treated conservatively. Simple but displaced fractures require anatomic reduction and fixation, typically using screws. The treatment course for complex fractures with multiple fragments is still being debated, as results are less predictable. Radial head resection is not advised if concomitant injuries of the coronoid process or the collateral ligaments with instability are present. Favorable outcomes following open reduction and fixation using plates were reported recently. However, complication rates are very high. Radial head replacement is a valuable tool in treating complex fractures of the radial head with predominantly good and excellent results. Patients who suffer radial head fractures are typically of a younger age, resulting in high functional demands. Certainly, unspecific and specific complications related to radial head arthroplasty were reported in up to 40 % of cases in an acute fracture setting. This article highlights common complications in radial head arthroplasty and aims to present strategies to avoid them. PMID:27600571
Radial head fractures--an update.
Pike, Jeffrey M; Athwal, George S; Faber, Kenneth J; King, Graham J W
2009-03-01
Radial head fractures are the most common fractures occurring around the elbow. Although radial head fractures can occur in isolation, associated fractures and ligament injuries are common. Assembling the clinical presentation, physical examination, and imaging into an effective treatment plan can be challenging. The characteristics of the radial head fracture influence the technique used to optimize the outcome. Fragment number, displacement, impaction, and bone quality are considered when deciding between early motion, fragment excision, and radial head excision, repair, or replacement. Isolated, minimally displaced fractures without evidence of mechanical block can be treated nonsurgically with early active range of motion (ROM). Partial, displaced radial head fractures without evidence of mechanical block can be treated either nonsurgically or with open reduction internal fixation (ORIF), as current evidence does not prove superiority of either strategy. For displaced fractures with greater than 3 fragments, radial head replacement is recommended. Radial head arthroplasty may be preferred over tenuous fracture fixation in the setting of associated ligament injuries when maintenance of joint stability could be compromised by ineffective fracture fixation. PMID:19258159
Novel Integrated Radial and Axial Magnetic Bearing
NASA Technical Reports Server (NTRS)
Blumenstock, Kenneth A.; Brown, Gary L.; Powers, Edward I. (Technical Monitor)
2000-01-01
Typically, fully active magnetically suspended systems require one axial and two radial magnetic bearings. Combining radial and axial functions into a single device allows for more compact and elegant packaging. Furthermore, in the case of high-speed devices such as energy storage flywheels, it is beneficial to minimize shaft length to keep rotor mode frequencies as high as possible. Attempts have been made to combine radial and axial functionality, but with certain drawbacks. One approach requires magnetic control flux to flow through a bias magnet reducing control effectiveness, thus resulting in increased resistive losses. This approach also requires axial force producing magnetic flux to flow in a direction into the rotor laminate that is undesirable for minimizing eddy-current losses resulting in rotational losses. Another approach applies a conical rotor shape to what otherwise would be a radial heteropolar magnetic bearing configuration. However, positional non-linear effects are introduced with this scheme and the same windings are used for bias, radial, and axial control adding complexity to the controller and electronics. For this approach, the amount of axial capability must be limited. It would be desirable for an integrated radial and axial magnetic bearing to have the following characteristics, separate inputs for radial and axial control for electronics and control simplicity, all magnetic control fluxes should only flow through their respective air gaps and should not flow through any bias magnets for minimal resistive losses, be of a homopolar design to minimize rotational losses, position related non-linear effects should be minimized, and dependent upon the design parameters, be able to achieve any radial/axial force or power ratio as desired. The integrated radial and axial magnetic bearing described in this paper exhibits all these characteristics. Magnetic circuit design, design equations, and analysis results will be presented.
An extensive radial velocity survey towards NGC 6253
NASA Astrophysics Data System (ADS)
Montalto, M.; Melo, C. H. F.; Santos, N. C.; Queloz, D.; Piotto, G.; Desidera, S.; Bedin, L. R.; Momany, Y.; Saviane, I.
2016-04-01
The old and metal-rich open cluster NGC 6253 was observed with the Fibre Large Array Multi Element Spectrograph (FLAMES) multi-object spectrograph during an extensive radial velocity campaign monitoring 317 stars with a median of 15 epochs per object. All the targeted stars are located along the upper main sequence of the cluster between 14.8 < V < 16.5. Fifty nine stars are confirmed cluster members both by radial velocities and proper motions and do not show evidence of variability. We detected 45 variable stars among which 25 belong to NGC 6253. We were able to derive an orbital solution for four cluster members (and for two field stars) yielding minimum masses in between ˜90 MJ and ˜460 MJ and periods between 3 and 220 d. Simulations demonstrated that this survey was sensitive to objects down to 30 MJ at 10 days orbital periods with a detection efficiency equal to 50 per cent. On the basis of these results we concluded that the observed frequency of binaries down to the hydrogen burning limit and up to 20 d orbital period is around (1.5 ± 1.3) per cent in NGC 6253. The overall observed frequency of binaries around the sample of cluster stars is (13 ± 3) per cent. The median radial velocity precision achieved by the GIRAFFE spectrograph in this magnitude range was around ˜240 m s- 1 (˜180 m s- 1 for UVES). Based on a limited follow-up analysis of seven stars in our sample with the High Accuracy Radial velocity Planet Searcher (HARPS) spectrograph we determined that a precision of 35 m s- 1 can be reached in this magnitude range, offering the possibility to further extend the variability analysis into the substellar domain. Prospects are even more favourable once considering the upcoming ESPRESSO spectrograph at VLT.
IEEE conference record--Abstracts
Not Available
1992-01-01
The following topics were covered in this meeting: basic plasma phenomena and plasma waves; plasma diagnostics; space plasma diagnostics; magnetic fusion; electron, ion and plasma sources; intense electron and ion beams; intense beam microwaves; fast wave M/W devices; microwave plasma interactions; plasma focus; ultrafast Z-pinches; plasma processing; electrical gas discharges; fast opening switches; magnetohydrodynamics; electromagnetic and electrothermal launchers; x-ray lasers; computational plasma science; solid state plasmas and switches; environmental/energy issues in plasma science; vacuum electronics; plasmas for lighting; gaseous electronics; and ball lightning and other spherical plasmas. Separate abstracts were prepared for 278 papers of this conference.
Operating System Abstraction Layer (OSAL)
NASA Technical Reports Server (NTRS)
Yanchik, Nicholas J.
2007-01-01
This viewgraph presentation reviews the concept of the Operating System Abstraction Layer (OSAL) and its benefits. The OSAL is A small layer of software that allows programs to run on many different operating systems and hardware platforms It runs independent of the underlying OS & hardware and it is self-contained. The benefits of OSAL are that it removes dependencies from any one operating system, promotes portable, reusable flight software. It allows for Core Flight software (FSW) to be built for multiple processors and operating systems. The presentation discusses the functionality, the various OSAL releases, and describes the specifications.
Building a radial spoke: flagellar radial spoke protein 3 (RSP3) is a dimer.
Wirschell, Maureen; Zhao, Feifei; Yang, Chun; Yang, Pinfen; Diener, Dennis; Gaillard, Anne; Rosenbaum, Joel L; Sale, Winfield S
2008-03-01
Radial spokes are critical multisubunit structures required for normal ciliary and eukaryotic flagellar motility. Experimental evidence indicates the radial spokes are mechanochemical transducers that transmit signals from the central pair apparatus to the outer doublet microtubules for local control of dynein activity. Recently, progress has been made in identifying individual components of the radial spoke, yet little is known about how the radial spoke is assembled or how it performs in signal transduction. Here we focus on radial spoke protein 3 (RSP3), a highly conserved AKAP located at the base of the radial spoke stalk and required for radial spoke assembly on the doublet microtubules. Biochemical approaches were taken to further explore the functional role of RSP3 within the radial spoke structure and for control of motility. Chemical crosslinking, native gel electrophoresis, and epitope-tagged RSP3 proteins established that RSP3 forms a dimer. Analysis of truncated RSP3 proteins indicates the dimerization domain coincides with the previously characterized axoneme binding domain in the N-terminus. We propose a model in which each radial spoke structure is built on an RSP3 dimer, and indicating that each radial spoke can potentially localize multiple PKAs or AKAP-binding proteins in position to control dynein activity and flagellar motility. PMID:18157907
Abstraction of Seepage into Drifts
M.L. Wilson; C.K. Ho
2000-09-26
A total-system performance assessment (TSPA) for a potential nuclear-waste repository requires an estimate of the amount of water that might contact waste. This paper describes the model used for part of that estimation in a recent TSPA for the Yucca Mountain site. The discussion is limited to estimation of how much water might enter emplacement drifts; additional considerations related to flow within the drifts, and how much water might actually contact waste, are not addressed here. The unsaturated zone at Yucca Mountain is being considered for the potential repository, and a drift opening in unsaturated rock tends to act as a capillary barrier and divert much of the percolating water around it. For TSPA, the important questions regarding seepage are how many waste packages might be subjected to water flow and how much flow those packages might see. Because of heterogeneity of the rock and uncertainty about the future (how the climate will evolve, etc.), it is not possible to predict seepage amounts or locations with certainty. Thus, seepage is treated as a stochastic quantity in TSPA simulations, with the magnitude and spatial distribution of seepage sampled from uncertainty distributions. The distillation of the essential components of process modeling into a form suitable for use in TSPA simulations is referred to as abstraction. In the following sections, seepage process models and abstractions will be summarized and then some illustrative results are presented.
Radial Velocity Fluctuations of RZ Psc
NASA Astrophysics Data System (ADS)
Potravnov, I. S.; Gorynya, N. A.; Grinin, V. P.; Minikulov, N. Kh.
2014-12-01
The behavior of the radial velocity of the UX Ori type star RZ Psc is studied. The existence of an inner cavity with a radius of about 0.7 a.u. in the circumstellar disk of this star allows to suggest the presence of a companion. A study of the radial velocity of RZ Psc based on our own measurements and published data yields no periodic component in its variability. The two most accurate measurements of V r , based on high resolution spectra obtained over a period of three months, show that the radial velocity is constant over this time interval to within 0.5 km/s. This imposes a limit of M p ≤10 M Jup on the mass of the hypothetical companion. Possible reasons for the observed strong fluctuations in the radial velocity of this star are discussed.
Finger necrosis after accidental radial artery puncture
Kang, Jun Sik; Lee, Tae Rim; Cha, Won Chul; Shin, Tae Gun; Sim, Min Seob; Jo, Ik Joon; Song, Keun Jeong; Rhee, Joong Eui; Jeong, Yeon Kwon
2014-01-01
Radial artery puncture, an invasive procedure, is frequently used for critical patients. Although considered safe, severe complications such as finger necrosis can occur. Herein, we review the clinical course of finger necrosis after accidental radial artery puncture. A 63-year-old woman visited the emergency department (ED) with left second and third finger pain after undergoing intravenous (IV) access in her wrist for procedural sedation. During the IV access, she experienced wrist pain, which increased during the 12 hours prior to her ED presentation. Emergency angiography revealed a pseudoaneurysm in her left radial artery and absence of blood flow to the proper palmar digital artery. Subsequent angiointervention and urokinase thrombolysis failed. The second finger was eventually amputated owing to gangrene. Radial artery puncture can occur accidentally during IV wrist access, resulting in severe morbidity. Providers should carefully examine the puncture site and collateral flow, followed by multiple examinations to ensure distal circulation.
Aberrant Radial Artery Causing Carpal Tunnel Syndrome
Kokkalis, Zinon T.; Tolis, Konstantinos E.; Megaloikonomos, Panayiotis D.; Panagopoulos, Georgios N.; Igoumenou, Vasilios G.; Mavrogenis, Andreas F.
2016-01-01
Anatomical vascular variations are rare causes of carpal tunnel syndrome. An aberrant medial artery is the most common vascular variation, while an aberrant radial artery causing carpal tunnel syndrome is even more rare, with an incidence ranging less than 3%. This article reports a patient with compression of the median nerve at the carpal tunnel by an aberrant superficial branch of the radial artery. An 80- year- old man presented with a 5-year history of right hand carpal tunnel syndrome; Tinel sign, Phalen test and neurophysiological studies were positive. Open carpal tunnel release showed an aberrant superficial branch of the radial artery with its accompanying veins running from radially to medially, almost parallel to the median nerve, ending at the superficial palmar arterial arch. The median nerve was decompressed without ligating the aberrant artery. At the last follow-up, 2 years after diagnosis and treatment the patient is asymptomatic. PMID:27517078
Aberrant Radial Artery Causing Carpal Tunnel Syndrome.
Kokkalis, Zinon T; Tolis, Konstantinos E; Megaloikonomos, Panayiotis D; Panagopoulos, Georgios N; Igoumenou, Vasilios G; Mavrogenis, Andreas F
2016-06-01
Anatomical vascular variations are rare causes of carpal tunnel syndrome. An aberrant medial artery is the most common vascular variation, while an aberrant radial artery causing carpal tunnel syndrome is even more rare, with an incidence ranging less than 3%. This article reports a patient with compression of the median nerve at the carpal tunnel by an aberrant superficial branch of the radial artery. An 80- year- old man presented with a 5-year history of right hand carpal tunnel syndrome; Tinel sign, Phalen test and neurophysiological studies were positive. Open carpal tunnel release showed an aberrant superficial branch of the radial artery with its accompanying veins running from radially to medially, almost parallel to the median nerve, ending at the superficial palmar arterial arch. The median nerve was decompressed without ligating the aberrant artery. At the last follow-up, 2 years after diagnosis and treatment the patient is asymptomatic.
Aberrant Radial Artery Causing Carpal Tunnel Syndrome.
Kokkalis, Zinon T; Tolis, Konstantinos E; Megaloikonomos, Panayiotis D; Panagopoulos, Georgios N; Igoumenou, Vasilios G; Mavrogenis, Andreas F
2016-06-01
Anatomical vascular variations are rare causes of carpal tunnel syndrome. An aberrant medial artery is the most common vascular variation, while an aberrant radial artery causing carpal tunnel syndrome is even more rare, with an incidence ranging less than 3%. This article reports a patient with compression of the median nerve at the carpal tunnel by an aberrant superficial branch of the radial artery. An 80- year- old man presented with a 5-year history of right hand carpal tunnel syndrome; Tinel sign, Phalen test and neurophysiological studies were positive. Open carpal tunnel release showed an aberrant superficial branch of the radial artery with its accompanying veins running from radially to medially, almost parallel to the median nerve, ending at the superficial palmar arterial arch. The median nerve was decompressed without ligating the aberrant artery. At the last follow-up, 2 years after diagnosis and treatment the patient is asymptomatic. PMID:27517078
Radial transport with perturbed magnetic field
Hazeltine, R. D.
2015-05-15
It is pointed out that the viscosity coefficient describing radial transport of toroidal angular momentum is proportional to the second power of the gyro-radius—like the corresponding coefficients for particle and heat transport—regardless of any geometrical symmetry. The observation is widely appreciated, but worth emphasizing because some literature gives the misleading impression that asymmetry can allow radial moment transport in first-order.
Mathematical interpretation of radial shearing interferometers.
Malacara, D
1974-08-01
The procedure for computing a radial shearing interferometric pattern is given. The interferometric pattern is analyzed to obtain the wavefront shape. Restricting the discussion to wavefronts having rotational symmetry, we give two different methods of finding the wavefront. One approach is to scan along a diameter of the interferometric pattern and the other is to examine the shape of the fringes. The relative sensitivity of a radial shearing interferometer with respect to that of a Twyman-Green interferometer is also analyzed.
Sequential Assembly of Flagellar Radial Spokes
Diener, Dennis R.; Yang, Pinfen; Geimer, Stefan; Cole, Douglas G.; Sale, Winfield S.; Rosenbaum, Joel L.
2013-01-01
The unicellular alga Chlamydomonas can assemble two 10 μm flagella in one hour from proteins synthesized in the cell body. Targeting and transporting these proteins to the flagella are simplified by preassembly of macromolecular complexes in the cell body. Radial spokes are flagellar complexes that are partially assembled in the cell body before entering the flagella. On the axoneme, radial spokes are “T” shaped structures with a head of 5 proteins and a stalk of 18 proteins that sediment together at 20S. In the cell body, radial spokes are partially assembled; about half of the radial spoke proteins (RSPs) form a 12S complex. In mutants lacking a single radial spoke protein, smaller spoke subassemblies were identified. When extracts from two such mutants were mixed in vitro the 12S complex was assembled from several smaller complexes demonstrating that portions of the stepwise assembly of radial spoke assembly can be carried out in vitro to elucidate the order of spoke assembly in the cell body. PMID:21692193
Experience with abstract notation one
NASA Technical Reports Server (NTRS)
Harvey, James D.; Weaver, Alfred C.
1990-01-01
The development of computer science has produced a vast number of machine architectures, programming languages, and compiler technologies. The cross product of these three characteristics defines the spectrum of previous and present data representation methodologies. With regard to computer networks, the uniqueness of these methodologies presents an obstacle when disparate host environments are to be interconnected. Interoperability within a heterogeneous network relies upon the establishment of data representation commonality. The International Standards Organization (ISO) is currently developing the abstract syntax notation one standard (ASN.1) and the basic encoding rules standard (BER) that collectively address this problem. When used within the presentation layer of the open systems interconnection reference model, these two standards provide the data representation commonality required to facilitate interoperability. The details of a compiler that was built to automate the use of ASN.1 and BER are described. From this experience, insights into both standards are given and potential problems relating to this development effort are discussed.
Abstraction Planning in Real Time
NASA Technical Reports Server (NTRS)
Washington, R.
1994-01-01
When a planning agent works in a complex, real-world domain, it is unable to plan for and store all possible contingencies and problem situations ahead of time. This thesis presents a method for planning a run time that incrementally builds up plans at multiple levels of abstraction. The plans are continually updated by information from the world, allowing the planner to adjust its plan to a changing world during the planning process. All the information is represented over intervals of time, allowing the planner to reason about durations, deadlines, and delays within its plan. In addition to the method, the thesis presents a formal model of the planning process and uses the model to investigate planning strategies.
Abstraction Planning in Real Time
NASA Technical Reports Server (NTRS)
Washington, Richard
1994-01-01
When a planning agent works in a complex, real-world domain, it is unable to plan for and store all possible contingencies and problem situations ahead of time. The agent needs to be able to fall back on an ability to construct plans at run time under time constraints. This thesis presents a method for planning at run time that incrementally builds up plans at multiple levels of abstraction. The plans are continually updated by information from the world, allowing the planner to adjust its plan to a changing world during the planning process. All the information is represented over intervals of time, allowing the planner to reason about durations, deadlines, and delays within its plan. In addition to the method, the thesis presents a formal model of the planning process and uses the model to investigate planning strategies. The method has been implemented, and experiments have been run to validate the overall approach and the theoretical model.
Toward Millimagnitude Photometric Calibration (Abstract)
NASA Astrophysics Data System (ADS)
Dose, E.
2014-12-01
(Abstract only) Asteroid roation, exoplanet transits, and similar measurements will increasingly call for photometric precisions better than about 10 millimagnitudes, often between nights and ideally between distant observers. The present work applies detailed spectral simulations to test popular photometric calibration practices, and to test new extensions of these practices. Using 107 synthetic spectra of stars of diverse colors, detailed atmospheric transmission spectra computed by solar-energy software, realistic spectra of popular astronomy gear, and the option of three sources of noise added at realistic millimagnitude levels, we find that certain adjustments to current calibration practices can help remove small systematic errors, especially for imperfect filters, high airmasses, and possibly passing thin cirrus clouds.
Strategies for writing a competitive research abstract.
Lindquist, R A
1993-01-01
This article focuses on the process of preparing research abstracts for submission to scientific meetings of professional organizations. Perspectives on the process of specifying an abstract's focus, choosing a scientific meeting, selecting the type of presentation, developing an abstract, and writing an abstract in its form are presented.
Preprocessor and postprocessor computer programs for a radial-flow finite-element model
Pucci, A.A.; Pope, D.A.
1987-01-01
Preprocessing and postprocessing computer programs that enhance the utility of the U.S. Geological Survey radial-flow model have been developed. The preprocessor program: (1) generates a triangular finite element mesh from minimal data input, (2) produces graphical displays and tabulations of data for the mesh , and (3) prepares an input data file to use with the radial-flow model. The postprocessor program is a version of the radial-flow model, which was modified to (1) produce graphical output for simulation and field results, (2) generate a statistic for comparing the simulation results with observed data, and (3) allow hydrologic properties to vary in the simulated region. Examples of the use of the processor programs for a hypothetical aquifer test are presented. Instructions for the data files, format instructions, and a listing of the preprocessor and postprocessor source codes are given in the appendixes. (Author 's abstract)
Lorenzetti, Fulvio; Giordano, Salvatore; Suominen, Erkki; Asko-Seljavaara, Sirpa; Suominen, Sinikka
2010-02-01
The purpose of this prospective study was to assess the blood flow of the radial and ulnar arteries before and after radial forearm flap raising. Twenty-two patients underwent radial forearm microvascular reconstruction for leg soft tissue defects. Blood flow of the radial, ulnar, and recipient arteries was measured intraoperatively by transit-time and ultrasonic flowmeter. In the in situ radial artery, the mean blood flow was 60.5 +/- 47.7 mL/min before, 6.7 +/- 4.1 mL/min after raising the flap, and 5.8 +/- 2.0 mL/min after end-to-end anastomosis to the recipient artery. In the ulnar artery, the mean blood flow was 60.5 +/- 43.3 mL/min before harvesting the radial forearm flap and significantly increased to 85.7 +/- 57.9 mL/min after radial artery sacrifice. A significant difference was also found between this value and the value of blood flow in the ulnar and radial arteries pooled together ( P < 0.05). The vascular resistance in the ulnar artery decreased significantly after the radial artery flap raising (from 2.7 +/- 3.1 to 1.9 +/- 2.2 peripheral resistance units, P = 0.010). The forearm has a conspicuous arterial vascularization not only through the radial and ulnar arteries but also through the interosseous system. The raising of the radial forearm flap increases blood flow and decreases vascular resistance in the ulnar artery. PMID:19902406
Attracting Girls into Physics (abstract)
NASA Astrophysics Data System (ADS)
Gadalla, Afaf
2009-04-01
A recent international study of women in physics showed that enrollment in physics and science is declining for both males and females and that women are severely underrepresented in careers requiring a strong physics background. The gender gap begins early in the pipeline, from the first grade. Girls are treated differently than boys at home and in society in ways that often hinder their chances for success. They have fewer freedoms, are discouraged from accessing resources or being adventurous, have far less exposure to problem solving, and are not encouraged to choose their lives. In order to motivate more girl students to study physics in the Assiut governorate of Egypt, the Assiut Alliance for the Women and Assiut Education District collaborated in renovating the education of physics in middle and secondary school classrooms. A program that helps in increasing the number of girls in science and physics has been designed in which informal groupings are organized at middle and secondary schools to involve girls in the training and experiences needed to attract and encourage girls to learn physics. During implementation of the program at some schools, girls, because they had not been trained in problem-solving as boys, appeared not to be as facile in abstracting the ideas of physics, and that was the primary reason for girls dropping out of science and physics. This could be overcome by holding a topical physics and technology summer school under the supervision of the Assiut Alliance for the Women.
1986 annual information meeting. Abstracts
Not Available
1986-01-01
Abstracts are presented for the following papers: Geohydrological Research at the Y-12 Plant (C.S. Haase); Ecological Impacts of Waste Disposal Operations in Bear Creek Valley Near the Y-12 Plant (J.M. Loar); Finite Element Simulation of Subsurface Contaminant Transport: Logistic Difficulties in Handling Large Field Problems (G.T. Yeh); Dynamic Compaction of a Radioactive Waste Burial Trench (B.P. Spalding); Comparative Evaluation of Potential Sites for a High-Level Radioactive Waste Repository (E.D. Smith); Changing Priorities in Environmental Assessment and Environmental Compliance (R.M. Reed); Ecology, Ecotoxicology, and Ecological Risk Assessment (L.W. Barnthouse); Theory and Practice in Uncertainty Analysis from Ten Years of Practice (R.H. Gardner); Modeling Landscape Effects of Forest Decline (V.H. Dale); Soil Nitrogen and the Global Carbon Cycle (W.M. Post); Maximizing Wood Energy Production in Short-Rotation Plantations: Effect of Initial Spacing and Rotation Length (L.L. Wright); and Ecological Communities and Processes in Woodland Streams Exhibit Both Direct and Indirect Effects of Acidification (J.W. Elwood).
Ozone Conference II: Abstract Proceedings
1999-11-01
Ozone Conference II: Pre- and Post-Harvest Applications Two Years After Gras, was held September 27-28, 1999 in Tulare, California. This conference, sponsored by EPRI's Agricultural Technology Alliance and Southern California Edison's AgTAC facility, was coordinated and organized by the on-site ATA-AgTAC Regional Center. Approximately 175 people attended the day-and-a-half conference at AgTAC. During the Conference twenty-two presentations were given on ozone food processing and agricultural applications. Included in the presentations were topics on: (1) Ozone fumigation; (2) Ozone generation techniques; (3) System and design applications; (4) Prewater treatment requirements; (5) Poultry water reuse; (6) Soil treatments with ozone gas; and (7) Post-harvest aqueous and gaseous ozone research results. A live videoconference between Tulare and Washington, D.C. was held to discuss the regulators' view from inside the beltway. Attendees participated in two Roundtable Question and Answer sessions and visited fifteen exhibits and demonstrations. The attendees included university and governmental researchers, regulators, consultants and industry experts, technology developers and providers, and corporate and individual end-users. This report is comprised of the Abstracts of each presentation, biographical sketches for each speaker and a registration/attendees list.
Handedness shapes children's abstract concepts.
Casasanto, Daniel; Henetz, Tania
2012-03-01
Can children's handedness influence how they represent abstract concepts like kindness and intelligence? Here we show that from an early age, right-handers associate rightward space more strongly with positive ideas and leftward space with negative ideas, but the opposite is true for left-handers. In one experiment, children indicated where on a diagram a preferred toy and a dispreferred toy should go. Right-handers tended to assign the preferred toy to a box on the right and the dispreferred toy to a box on the left. Left-handers showed the opposite pattern. In a second experiment, children judged which of two cartoon animals looked smarter (or dumber) or nicer (or meaner). Right-handers attributed more positive qualities to animals on the right, but left-handers to animals on the left. These contrasting associations between space and valence cannot be explained by exposure to language or cultural conventions, which consistently link right with good. Rather, right- and left-handers implicitly associated positive valence more strongly with the side of space on which they can act more fluently with their dominant hands. Results support the body-specificity hypothesis (Casasanto, 2009), showing that children with different kinds of bodies think differently in corresponding ways. PMID:21916951
An abstract approach to music.
Kaper, H. G.; Tipei, S.
1999-04-19
In this article we have outlined a formal framework for an abstract approach to music and music composition. The model is formulated in terms of objects that have attributes, obey relationships, and are subject to certain well-defined operations. The motivation for this approach uses traditional terms and concepts of music theory, but the approach itself is formal and uses the language of mathematics. The universal object is an audio wave; partials, sounds, and compositions are special objects, which are placed in a hierarchical order based on time scales. The objects have both static and dynamic attributes. When we realize a composition, we assign values to each of its attributes: a (scalar) value to a static attribute, an envelope and a size to a dynamic attribute. A composition is then a trajectory in the space of aural events, and the complex audio wave is its formal representation. Sounds are fibers in the space of aural events, from which the composer weaves the trajectory of a composition. Each sound object in turn is made up of partials, which are the elementary building blocks of any music composition. The partials evolve on the fastest time scale in the hierarchy of partials, sounds, and compositions. The ideas outlined in this article are being implemented in a digital instrument for additive sound synthesis and in software for music composition. A demonstration of some preliminary results has been submitted by the authors for presentation at the conference.
Radial Tunnel Syndrome, Diagnostic and Treatment Dilemma.
Moradi, Ali; Ebrahimzadeh, Mohammad H; Jupiter, Jess B
2015-07-01
Radial tunnel syndrome is a disease which we should consider it in elbow and forearm pains. It is diagnosed with lateral elbow and dorsal forearm pain may radiate to the wrist and dorsum of the fingers. The disease is more prevalent in women with the age of 30 to 50 years old. It occurs by intermittent compression on the radial nerve from the radial head to the inferior border of the supinator muscle, without obvious extensor muscle weakness. Compression could happen in five different sites but the arcade of Frose is the most common area that radial nerve is compressed. To diagnosis radial tunnel syndrome, clinical examination is more important than paraclinic tests such as electrodiagnsic test and imaging studies. The exact site of the pain which can more specified by rule of nine test and weakness of the third finger and wrist extension are valuable physical exams to diagnosis. MRI studies my show muscle edema or atrophy along the distribution of the posterior interosseous nerve. Although non-surgical treatments such as rest, NSAIDs, injections and physiotherapy do not believe to have permanent relief, but it is justify undergoing them before surgery. Surgery could diminish pain and symptoms in 67 to 93 percents of patients completely.
Radial Tunnel Syndrome, Diagnostic and Treatment Dilemma
Moradi, Ali; Ebrahimzadeh, Mohammad H; Jupiter, Jess B
2015-01-01
Radial tunnel syndrome is a disease which we should consider it in elbow and forearm pains. It is diagnosed with lateral elbow and dorsal forearm pain may radiate to the wrist and dorsum of the fingers. The disease is more prevalent in women with the age of 30 to 50 years old. It occurs by intermittent compression on the radial nerve from the radial head to the inferior border of the supinator muscle, without obvious extensor muscle weakness. Compression could happen in five different sites but the arcade of Frose is the most common area that radial nerve is compressed. To diagnosis radial tunnel syndrome, clinical examination is more important than paraclinic tests such as electrodiagnsic test and imaging studies. The exact site of the pain which can more specified by rule of nine test and weakness of the third finger and wrist extension are valuable physical exams to diagnosis. MRI studies my show muscle edema or atrophy along the distribution of the posterior interosseous nerve. Although non-surgical treatments such as rest, NSAIDs, injections and physiotherapy do not believe to have permanent relief, but it is justify undergoing them before surgery. Surgery could diminish pain and symptoms in 67 to 93 percents of patients completely. PMID:26213698
Helical antimicrobial polypeptides with radial amphiphilicity
Xiong, Menghua; Lee, Michelle W.; Mansbach, Rachael A.; Song, Ziyuan; Bao, Yan; Peek, Richard M.; Yao, Catherine; Chen, Lin-Feng; Ferguson, Andrew L.; Wong, Gerard C. L.; Cheng, Jianjun
2015-01-01
α-Helical antimicrobial peptides (AMPs) generally have facially amphiphilic structures that may lead to undesired peptide interactions with blood proteins and self-aggregation due to exposed hydrophobic surfaces. Here we report the design of a class of cationic, helical homo-polypeptide antimicrobials with a hydrophobic internal helical core and a charged exterior shell, possessing unprecedented radial amphiphilicity. The radially amphiphilic structure enables the polypeptide to bind effectively to the negatively charged bacterial surface and exhibit high antimicrobial activity against both gram-positive and gram-negative bacteria. Moreover, the shielding of the hydrophobic core by the charged exterior shell decreases nonspecific interactions with eukaryotic cells, as evidenced by low hemolytic activity, and protects the polypeptide backbone from proteolytic degradation. The radially amphiphilic polypeptides can also be used as effective adjuvants, allowing improved permeation of commercial antibiotics in bacteria and enhanced antimicrobial activity by one to two orders of magnitude. Designing AMPs bearing this unprecedented, unique radially amphiphilic structure represents an alternative direction of AMP development; radially amphiphilic polypeptides may become a general platform for developing AMPs to treat drug-resistant bacteria. PMID:26460016
Radial velocity studies of cool stars.
Jones, Hugh R A; Barnes, John; Tuomi, Mikko; Jenkins, James S; Anglada-Escude, Guillem
2014-04-28
Our current view of exoplanets is one derived primarily from solar-like stars with a strong focus on understanding our Solar System. Our knowledge about the properties of exoplanets around the dominant stellar population by number, the so-called low-mass stars or M dwarfs, is much more cursory. Based on radial velocity discoveries, we find that the semi-major axis distribution of M dwarf planets appears to be broadly similar to those around more massive stars and thus formation and migration processes might be similar to heavier stars. However, we find that the mass of M dwarf planets is relatively much lower than the expected mass dependency based on stellar mass and thus infer that planet formation efficiency around low-mass stars is relatively impaired. We consider techniques to overcome the practical issue of obtaining good quality radial velocity data for M dwarfs despite their faintness and sustained activity and emphasize (i) the wavelength sensitivity of radial velocity signals, (ii) the combination of radial velocity data from different experiments for robust detection of small amplitude signals, and (iii) the selection of targets and radial velocity interpretation of late-type M dwarfs should consider Hα behaviour.
Radial spoke proteins of Chlamydomonas flagella
Yang, Pinfen; Diener, Dennis R.; Yang, Chun; Kohno, Takahiro; Pazour, Gregory J.; Dienes, Jennifer M.; Agrin, Nathan S.; King, Stephen M.; Sale, Winfield S.; Kamiya, Ritsu; Rosenbaum, Joel L.; Witman, George B.
2007-01-01
Summary The radial spoke is a ubiquitous component of ‘9+2’ cilia and flagella, and plays an essential role in the control of dynein arm activity by relaying signals from the central pair of microtubules to the arms. The Chlamydomonas reinhardtii radial spoke contains at least 23 proteins, only 8 of which have been characterized at the molecular level. Here, we use mass spectrometry to identify 10 additional radial spoke proteins. Many of the newly identified proteins in the spoke stalk are predicted to contain domains associated with signal transduction, including Ca2+-, AKAP- and nucleotide-binding domains. This suggests that the spoke stalk is both a scaffold for signaling molecules and itself a transducer of signals. Moreover, in addition to the recently described HSP40 family member, a second spoke stalk protein is predicted to be a molecular chaperone, implying that there is a sophisticated mechanism for the assembly of this large complex. Among the 18 spoke proteins identified to date, at least 12 have apparent homologs in humans, indicating that the radial spoke has been conserved throughout evolution. The human genes encoding these proteins are candidates for causing primary ciliary dyskinesia, a severe inherited disease involving missing or defective axonemal structures, including the radial spokes. PMID:16507594
Radial velocity studies of cool stars.
Jones, Hugh R A; Barnes, John; Tuomi, Mikko; Jenkins, James S; Anglada-Escude, Guillem
2014-04-28
Our current view of exoplanets is one derived primarily from solar-like stars with a strong focus on understanding our Solar System. Our knowledge about the properties of exoplanets around the dominant stellar population by number, the so-called low-mass stars or M dwarfs, is much more cursory. Based on radial velocity discoveries, we find that the semi-major axis distribution of M dwarf planets appears to be broadly similar to those around more massive stars and thus formation and migration processes might be similar to heavier stars. However, we find that the mass of M dwarf planets is relatively much lower than the expected mass dependency based on stellar mass and thus infer that planet formation efficiency around low-mass stars is relatively impaired. We consider techniques to overcome the practical issue of obtaining good quality radial velocity data for M dwarfs despite their faintness and sustained activity and emphasize (i) the wavelength sensitivity of radial velocity signals, (ii) the combination of radial velocity data from different experiments for robust detection of small amplitude signals, and (iii) the selection of targets and radial velocity interpretation of late-type M dwarfs should consider Hα behaviour. PMID:24664922
Fast Radial Flows in Transition Disk Holes
NASA Astrophysics Data System (ADS)
Rosenfeld, Katherine A.; Chiang, Eugene; Andrews, Sean M.
2014-02-01
Protoplanetary "transition" disks have large, mass-depleted central cavities, yet also deliver gas onto their host stars at rates comparable to disks without holes. The paradox of simultaneous transparency and accretion can be explained if gas flows inward at much higher radial speeds inside the cavity than outside the cavity, since surface density (and by extension optical depth) varies inversely with inflow velocity at fixed accretion rate. Radial speeds within the cavity might even have to approach free-fall values to explain the huge surface density contrasts inferred for transition disks. We identify observational diagnostics of fast radial inflow in channel maps made in optically thick spectral lines. Signatures include (1) twisted isophotes in maps made at low systemic velocities and (2) rotation of structures observed between maps made in high-velocity line wings. As a test case, we apply our new diagnostic tools to archival Atacama Large Millimeter Array data on the transition disk HD 142527 and uncover evidence for free-fall radial velocities inside its cavity. Although the observed kinematics are also consistent with a disk warp, the radial inflow scenario is preferred because it predicts low surface densities that appear consistent with recent observations of optically thin CO isotopologues in this disk. How material in the disk cavity sheds its angular momentum wholesale to fall freely onto the star is an unsolved problem; gravitational torques exerted by giant planets or brown dwarfs are briefly discussed as a candidate mechanism.
Fast radial flows in transition disk holes
Rosenfeld, Katherine A.; Andrews, Sean M.; Chiang, Eugene
2014-02-20
Protoplanetary 'transition' disks have large, mass-depleted central cavities, yet also deliver gas onto their host stars at rates comparable to disks without holes. The paradox of simultaneous transparency and accretion can be explained if gas flows inward at much higher radial speeds inside the cavity than outside the cavity, since surface density (and by extension optical depth) varies inversely with inflow velocity at fixed accretion rate. Radial speeds within the cavity might even have to approach free-fall values to explain the huge surface density contrasts inferred for transition disks. We identify observational diagnostics of fast radial inflow in channel maps made in optically thick spectral lines. Signatures include (1) twisted isophotes in maps made at low systemic velocities and (2) rotation of structures observed between maps made in high-velocity line wings. As a test case, we apply our new diagnostic tools to archival Atacama Large Millimeter Array data on the transition disk HD 142527 and uncover evidence for free-fall radial velocities inside its cavity. Although the observed kinematics are also consistent with a disk warp, the radial inflow scenario is preferred because it predicts low surface densities that appear consistent with recent observations of optically thin CO isotopologues in this disk. How material in the disk cavity sheds its angular momentum wholesale to fall freely onto the star is an unsolved problem; gravitational torques exerted by giant planets or brown dwarfs are briefly discussed as a candidate mechanism.
Annotating user-defined abstractions for optimization
Quinlan, D; Schordan, M; Vuduc, R; Yi, Q
2005-12-05
This paper discusses the features of an annotation language that we believe to be essential for optimizing user-defined abstractions. These features should capture semantics of function, data, and object-oriented abstractions, express abstraction equivalence (e.g., a class represents an array abstraction), and permit extension of traditional compiler optimizations to user-defined abstractions. Our future work will include developing a comprehensive annotation language for describing the semantics of general object-oriented abstractions, as well as automatically verifying and inferring the annotated semantics.
Abstraction and reformulation in artificial intelligence.
Holte, Robert C.; Choueiry, Berthe Y.
2003-01-01
This paper contributes in two ways to the aims of this special issue on abstraction. The first is to show that there are compelling reasons motivating the use of abstraction in the purely computational realm of artificial intelligence. The second is to contribute to the overall discussion of the nature of abstraction by providing examples of the abstraction processes currently used in artificial intelligence. Although each type of abstraction is specific to a somewhat narrow context, it is hoped that collectively they illustrate the richness and variety of abstraction in its fullest sense. PMID:12903653
Radial flow nuclear thermal rocket (RFNTR)
Leyse, Carl F.
1995-11-07
A radial flow nuclear thermal rocket fuel assembly includes a substantially conical fuel element having an inlet side and an outlet side. An annular channel is disposed in the element for receiving a nuclear propellant, and a second, conical, channel is disposed in the element for discharging the propellant. The first channel is located radially outward from the second channel, and separated from the second channel by an annular fuel bed volume. This fuel bed volume can include a packed bed of loose fuel beads confined by a cold porous inlet frit and a hot porous exit frit. The loose fuel beads include ZrC coated ZrC-UC beads. In this manner, nuclear propellant enters the fuel assembly axially into the first channel at the inlet side of the element, flows axially across the fuel bed volume, and is discharged from the assembly by flowing radially outward from the second channel at the outlet side of the element.
Radial flow nuclear thermal rocket (RFNTR)
Leyse, Carl F.
1995-01-01
A radial flow nuclear thermal rocket fuel assembly includes a substantially conical fuel element having an inlet side and an outlet side. An annular channel is disposed in the element for receiving a nuclear propellant, and a second, conical, channel is disposed in the element for discharging the propellant. The first channel is located radially outward from the second channel, and separated from the second channel by an annular fuel bed volume. This fuel bed volume can include a packed bed of loose fuel beads confined by a cold porous inlet frit and a hot porous exit frit. The loose fuel beads include ZrC coated ZrC-UC beads. In this manner, nuclear propellant enters the fuel assembly axially into the first channel at the inlet side of the element, flows axially across the fuel bed volume, and is discharged from the assembly by flowing radially outward from the second channel at the outlet side of the element.
Manufacturing of Precision Forgings by Radial Forging
Wallner, S.; Harrer, O.; Buchmayr, B.; Hofer, F.
2011-01-17
Radial forging is a multi purpose incremental forging process using four tools on the same plane. It is widely used for the forming of tool steels, super alloys as well as titanium- and refractory metals. The range of application goes from reducing the diameters of shafts, tubes, stepped shafts and axels, as well as for creating internal profiles for tubes in Near-Net-Shape and Net-Shape quality. Based on actual development of a weight optimized transmission input shaft, the specific features of radial forging technology is demonstrated. Also a Finite Element Model for the simulation of the process is shown which leads to reduced pre-processing effort and reduced computing time compared to other published simulation methods for radial forging. The finite element model can be applied to quantify the effects of different forging strategies.
Generalized radially self-accelerating helicon beams.
Vetter, Christian; Eichelkraut, Toni; Ornigotti, Marco; Szameit, Alexander
2014-10-31
We report, in theory and experiment, on a new class of optical beams that are radially self-accelerating and nondiffracting. These beams continuously evolve on spiraling trajectories while maintaining their amplitude and phase distribution in their rotating rest frame. We provide a detailed insight into the theoretical origin and characteristics of radial self-acceleration and prove our findings experimentally. As radially self-accelerating beams are nonparaxial and a solution to the full scalar Helmholtz equation, they can be implemented in many linear wave systems beyond optics, from acoustic and elastic waves to surface waves in fluids and soft matter. Our work generalized the study of classical helicon beams to a complete set of solutions for rotating complex fields. PMID:25396370
Radial anisotropy ambient noise tomography of volcanoes
NASA Astrophysics Data System (ADS)
Mordret, Aurélien; Rivet, Diane; Shapiro, Nikolai; Jaxybulatov, Kairly; Landès, Matthieu; Koulakov, Ivan; Sens-Schönfelder, Christoph
2016-04-01
The use of ambient seismic noise allows us to perform surface-wave tomography of targets which could hardly be imaged by other means. The frequencies involved (~ 0.5 - 20 s), somewhere in between active seismic and regular teleseismic frequency band, make possible the high resolution imaging of intermediate-size targets like volcanic edifices. Moreover, the joint inversion of Rayleigh and Love waves dispersion curves extracted from noise correlations allows us to invert for crustal radial anisotropy. We present here the two first studies of radial anisotropy on volcanoes by showing results from Lake Toba Caldera, a super-volcano in Indonesia, and from Piton de la Fournaise volcano, a hot-spot effusive volcano on the Réunion Island (Indian Ocean). We will see how radial anisotropy can be used to infer the main fabric within a magmatic system and, consequently, its dominant type of intrusion.
Dispersion-free radial transmission lines
Caporaso, George J.; Nelson, Scott D.
2011-04-12
A dispersion-free radial transmission line ("DFRTL") preferably for linear accelerators, having two plane conductors each with a central hole, and an electromagnetically permeable material ("EPM") between the two conductors and surrounding a channel connecting the two holes. At least one of the material parameters of relative magnetic permeability, relative dielectric permittivity, and axial width of the EPM is varied as a function of radius, so that the characteristic impedance of the DFRTL is held substantially constant, and pulse transmission therethrough is substantially dispersion-free. Preferably, the EPM is divided into concentric radial sections, with the varied material parameters held constant in each respective section but stepwise varied between sections as a step function of the radius. The radial widths of the concentric sections are selected so that pulse traversal time across each section is the same, and the varied material parameters of the concentric sections are selected to minimize traversal error.
Precise Near-Infrared Radial Velocities
NASA Astrophysics Data System (ADS)
Plavchan, Peter; Gao, P.; Bottom, M.; Davison, C.; Mills, S.; Ciardi, D. R.; Brinkworth, C.; Tanner, A. M.; Beichman, C. A.; Catanzarite, J.; Crawford, S.; Wallace, J.; Mennesson, B.; Johnson, J. A.; White, R. J.; Anglada-Escudé, G.; von Braun, K.; Walp, B.; Vasisht, G.; Kane, S. R.; Prato, L. A.; NIRRVs
2014-01-01
We present precise radial velocity time-series from a 2.3 micron pilot survey to detect exoplanets around red, low mass, and young stars. We use the CSHELL spectrograph with an isotopic methane absorption gas cell for common optical path relative wavelength calibration at the NASA InfraRed Telescope Facility. We present an overview of our Nelder-Mead simplex optimization pipeline for extracting radial velocities. We will also present first light data at 1.6 microns from a near-infrared fiber scrambler used in tandem with our gas cell and CSHELL at IRTF. The fiber scrambler makes use of non-circular core fibers to stabilize the illumination of the slit and echelle grating against changes in seeing, focus, guiding and other sources of systematic radial velocity noise, complementing the wavelength calibration of a gas cell.
DOE-NABIR PI Workshop: Abstracts 2003
Various
2003-01-28
The mission of the NABIR program is to provide the fundamental science that will serve as the basis for the development of cost-effective bioremediation and long-term stewardship of radionuclides and metals in the subsurface at DOE sites. The focus of the program is on strategies leading to long-term immobilization of contaminants in situ to reduce the risk to humans and the environment. Contaminants of special interest are uranium, technetium, plutonium, chromium, and mercury. The focus of the NABIR program is on the bioremediation of these contaminants in the subsurface below the root zone, including both vadose and saturated zones. The program consists of four interrelated Science Elements (Biotransformation, Community Dynamics/Microbial Ecology, Biomolecular Science and Engineering, and Biogeochemistry). The program also has a cross-cutting Assessment Element that supports development of innovative approaches and technologies to support the science elements. An element called Bioremediation and its Societal Implications and Concerns (BASIC) addresses potential societal issues of implementing NABIR scientific findings. The material presented at this year's workshop focuses on approximately 60 research projects funded in FY 2000-2003 by the Environmental Remediation Sciences Division in DOE's Office of Biological and Environmental Research (BER) in the Office of Science. Abstracts of NABIR research projects are provided in this book.
DOE NABIR PI Workshop: Abstracts 2002
Hawkes , Dan
2002-01-09
The mission of the NABIR program is to provide the fundamental science that will serve as the basis for the development of cost-effective bioremediation and long-term stewardship of radionuclides and metals in the subsurface at DOE sites. The focus of the program is on strategies leading to long-term immobilization of contaminants in place to reduce the risk to humans and the environment. Contaminants of special interest are uranium, technetium, plutonium, chromium, and mercury. The focus of the NABIR program is on the bioremediation of these contaminants in the subsurface below the root zone, including both vadose and saturated zones. The program is implemented through four interrelated scientific research elements (Biogeochemistry, Biomolecular Science and Engineering, Biotransformation, and Community Dynamics/Microbial Ecology); and through an element called Bioremediation and its Societal Implications and Concerns (BASIC), which addresses societal issues and potential concerns of stakeholders. The material presented at this year's workshop focuses on approximately 60 research projects funded in FY 2000-2002 by DOE's Office of Biological and Environmental Research (BER). Abstracts of NABIR research projects are provided in this book.
Scientific meeting abstracts: significance, access, and trends.
Kelly, J A
1998-01-01
Abstracts of scientific papers and posters that are presented at annual scientific meetings of professional societies are part of the broader category of conference literature. They are an important avenue for the dissemination of current data. While timely and succinct, these abstracts present problems such as an abbreviated peer review and incomplete bibliographic access. METHODS: Seventy societies of health sciences professionals were surveyed about the publication of abstracts from their annual meetings. Nineteen frequently cited journals also were contacted about their policies on the citation of meeting abstracts. Ten databases were searched for the presence of meetings abstracts. RESULTS: Ninety percent of the seventy societies publish their abstracts, with nearly half appearing in the society's journal. Seventy-seven percent of the societies supply meeting attendees with a copy of each abstract, and 43% make their abstracts available in an electronic format. Most of the journals surveyed allow meeting abstracts to be cited. Bibliographic access to these abstracts does not appear to be widespread. CONCLUSIONS: Meeting abstracts play an important role in the dissemination of scientific knowledge. Bibliographic access to meeting abstracts is very limited. The trend toward making meeting abstracts available via the Internet has the potential to give a broader audience access to the information they contain. PMID:9549015
From Abstract to Concrete Norms in Agent Institutions
NASA Technical Reports Server (NTRS)
Grossi, Davide; Dignum, Frank
2004-01-01
Norms specifying constraints over institutions are stated in such a form that allows them to regulate a wide range of situations over time without need for modification. To guarantee this stability, the formulation of norms need to abstract from a variety of concrete aspects, which are instead relevant for the actual operationalization of institutions. If agent institutions are to be built, which comply with a set of abstract requirements, how can those requirements be translated in more concrete constraints the impact of which can be described directly in the institution? In this work we make use of logical methods in order to provide a formal characterization of the translation rules that operate the connection between abstract and concrete norms. On the basis of this characterization, a comprehensive formalization of the notion of institution is also provided.
Reconstruction for Type IV Radial Polydactyly.
Wall, Lindley B; Goldfarb, Charles A
2015-09-01
Type IV radial polydactyly represents a thumb with an extra proximal and distal phalanx. Assessment of the thumb for surgical reconstruction includes observing thumb function, evaluating thumb size and stability, and assessing the first web space. Reconstruction includes excision of the smaller thumb, typically the radial thumb, and re-creating thumb stability and alignment by addressing tendon insertion and joint orientation. Although surgical results are satisfying and complications are uncommon, additional surgical intervention may be required over time owing to thumb malalignment or instability.
Radial elasticity of multiwalled carbon nanotubes.
Palaci, I; Fedrigo, S; Brune, H; Klinke, C; Chen, M; Riedo, E
2005-05-01
We report an experimental and a theoretical study of the radial elasticity of multiwalled carbon nanotubes as a function of external radius. We use atomic force microscopy and apply small indentation amplitudes in order to stay in the linear elasticity regime. The number of layers for a given tube radius is inferred from transmission electron microscopy, revealing constant ratios of external to internal radii. This enables a comparison with molecular dynamics results, which also shed some light onto the applicability of Hertz theory in this context. Using this theory, we find a radial Young modulus strongly decreasing with increasing radius and reaching an asymptotic value of 30+/-10 GPa.
The radial velocity search for extrasolar planets
NASA Technical Reports Server (NTRS)
Mcmillan, Robert S.
1991-01-01
Radial velocity measurements are being made to search for planets orbiting stars other than the Sun. The reflex acceleration induced on stars by planets can be sensed by measuring the small, slow changes in the line-of-site velocities of stars. To detect these planetary perturbations, the data series must be made on a uniform instrumental scale for as long as it takes a planet to orbit its star. A spectrometer of extreme stability and unprecedented sensitivity to changes in stellar radial velocities was operated.
Plasma Signatures of Radial Field Power Dropouts
Lucek, E.A.; Horbury, T.S.; Balogh, A.; McComas, D.J.
1998-10-04
A class of small scale structures, with a near-radial magnetic field and a drop in magnetic field fluctuation power, have recently been identified in the polar solar wind. An earlier study of 24 events, each lasting for 6 hours or more, identified no clear plasma signature. In an extension of that work, radial intervals lasting for 4 hours or more (89 in total), have been used to search for a statistically significant plasma signature. It was found that, despite considerable variations between intervals, there was a small but significant drop, on average, in plasma temperature, density and {beta} during these events.
An algorithm for generating abstract syntax trees
NASA Technical Reports Server (NTRS)
Noonan, R. E.
1985-01-01
The notion of an abstract syntax is discussed. An algorithm is presented for automatically deriving an abstract syntax directly from a BNF grammar. The implementation of this algorithm and its application to the grammar for Modula are discussed.
Abstracted model for ceramic coating
Farmer, J C; Stockman, C
1998-11-14
Engineers are exploring several mechanisms to delay corrosive attack of the CAM (corrosion allowance material) by dripping water, including drip shields and ceramic coatings. Ceramic coatings deposited with high-velocity oxyfuels (HVOF's) have exhibited a porosity of only 2% at a thickness of 0.15 cm. The primary goal of this document is to provide a detailed description of an abstracted process-level model for Total System Performance Assessment (TSPA) that has been developed to account for the inhibition of corrosion by protective ceramic coatings. A second goal was to address as many of the issues raised during a recent peer review as possible (direct reaction of liquid water with carbon steel, stress corrosion cracking of the ceramic coating, bending stresses in coatings of finite thickness, limitations of simple correction factors, etc.). During the periods of dry oxidation (T ≥ 100°C) and humid-air corrosion (T ≤ 100°C & RH < 8O%), it is assumed that the growth rate of oxide on the surface is diminished in proportion to the surface covered by solid ceramic. The mass transfer impedance imposed by a ceramic coating with gas-filled pores is assumed to be negligible. During the period of aqueous phase corrosion (T ≤ 100°C & RH ≥ 80%), it is assumed that the overall mass transfer resistance governing the corrosion rate is due to the combined resistance of ceramic coating & interfacial corrosion products. Two porosity models (simple cylinder & cylinder-sphere chain) are considered in estimation of the mass transfer resistance of the ceramic coating. It is evident that substantial impedance to 0₂ transport is encountered if pores are filled with liquid water. It may be possible to use a sealant to eliminate porosity. Spallation (rupture) of the ceramic coating is assumed to occur if the stress introduced by the expanding corrosion products at the ceramic- CAM interface exceeds fracture stress. Since this model does not account for the possibility of
Automatic Black-Box Model Order Reduction using Radial Basis Functions
Stephanson, M B; Lee, J F; White, D A
2011-07-15
Finite elements methods have long made use of model order reduction (MOR), particularly in the context of fast freqeucny sweeps. In this paper, we discuss a black-box MOR technique, applicable to a many solution methods and not restricted only to spectral responses. We also discuss automated methods for generating a reduced order model that meets a given error tolerance. Numerical examples demonstrate the effectiveness and wide applicability of the method. With the advent of improved computing hardware and numerous fast solution techniques, the field of computational electromagnetics are progressed rapidly in terms of the size and complexity of problems that can be solved. Numerous applications, however, require the solution of a problem for many different configurations, including optimization, parameter exploration, and uncertainly quantification, where the parameters that may be changed include frequency, material properties, geometric dimensions, etc. In such cases, thousands of solutions may be needed, so solve times of even a few minutes can be burdensome. Model order reduction (MOR) may alleviate this difficulty by creating a small model that can be evaluated quickly. Many MOR techniques have been applied to electromagnetic problems over the past few decades, particularly in the context of fast frequency sweeps. Recent works have extended these methods to allow more than one parameter and to allow the parameters to represent material and geometric properties. There are still limitations with these methods, however. First, they almost always assume that the finite element method is used to solve the problem, so that the system matrix is a known function of the parameters. Second, although some authors have presented adaptive methods (e.g., [2]), the order of the model is often determined before the MOR process begins, with little insight about what order is actually needed to reach the desired accuracy. Finally, it not clear how to efficiently extend most methods to the multiparameter case. This paper address the above shortcomings be developing a method that uses a block-box approach to the solution method, is adaptive, and is easily extensible to many parameters.
Falat, Lukas; Marcek, Dusan; Durisova, Maria
2016-01-01
This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450
Falat, Lukas; Marcek, Dusan; Durisova, Maria
2016-01-01
This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.
NASA Astrophysics Data System (ADS)
Wei, H. L.; Zhu, D. Q.; Billings, S. A.; Balikhin, M. A.
The Dst index is a key parameter which characterises the disturbance of the geomagnetic field in magnetic storms. Modelling of the Dst index is thus very important for the analysis of the geomagnetic field. A data-based modelling approach, aimed at obtaining efficient models from limited input-output observational data, provides a powerful tool for analysing and forecasting geomagnetic activities including the prediction of the Dst index. In this study, the process of the Dst index is treated to be a structure-unknown system, where the solar wind parameter ( VBs) and the solar wind dynamic pressure ( P) are the system inputs, and the Dst index is the system output. A novel multiscale RBF (MSRBF) network is introduced to represent such a two-input and single-output system, where the Dst index is related to the solar wind parameter and the dynamic pressure, via a hybrid network model consisting of two submodels: a linear part that reflects the linear relationship between the output and the inputs, and a nonlinear part that captures the effect of the interacting contribution of past observations of the inputs and the output, on the current output. The proposed MSRBF network can easily be converted into a linear-in-the-parameters form and the training of the linear network model can easily be implemented using a forward orthogonal regression (FOR) algorithm. One advantage of the new MSRBF network, compared with traditional single scale RBF networks, is that the new network is more flexible for describing complex nonlinear dynamical systems.
A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions
Pan, Guang; Ye, Pengcheng; Yang, Zhidong
2014-01-01
Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is strongly affected by the sampling methods. In this paper, a new sequential optimization sampling method is proposed. Based on the new sampling method, metamodels can be constructed repeatedly through the addition of sampling points, namely, extrema points of metamodels and minimum points of density function. Afterwards, the more accurate metamodels would be constructed by the procedure above. The validity and effectiveness of proposed sampling method are examined by studying typical numerical examples. PMID:25133206
Marcek, Dusan; Durisova, Maria
2016-01-01
This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450
Writing a Structured Abstract for the Thesis
ERIC Educational Resources Information Center
Hartley, James
2010-01-01
This article presents the author's suggestions on how to improve thesis abstracts. The author describes two books on writing abstracts: (1) "Creating Effective Conference Abstracts and Posters in Biomedicine: 500 tips for Success" (Fraser, Fuller & Hutber, 2009), a compendium of clear advice--a must book to have in one's hand as one prepares a…
Code of Federal Regulations, 2011 CFR
2011-07-01
... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...
Code of Federal Regulations, 2013 CFR
2013-07-01
... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false The abstract. 1.438 Section 1... COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES International Processing Provisions The International Application § 1.438 The abstract. (a) Requirements as to the content and form of the abstract are set forth...
On abstract degenerate neutral differential equations
NASA Astrophysics Data System (ADS)
Hernández, Eduardo; O'Regan, Donal
2016-10-01
We introduce a new abstract model of functional differential equations, which we call abstract degenerate neutral differential equations, and we study the existence of strict solutions. The class of problems and the technical approach introduced in this paper allow us to generalize and extend recent results on abstract neutral differential equations. Some examples on nonlinear partial neutral differential equations are presented.
ERIC Educational Resources Information Center
Berdit, Nancy
2006-01-01
Abstraction has long been a concept difficult to define for students. Students often feel the pressure of making their artwork "look real" and frustration can often lead to burnout in the classroom. In this article, the author describes how her lesson on abstraction has alleviated much of that pressure as students created an abstract acrylic…
Impact of radial migration on stellar and gas radial metallicity distribution
NASA Astrophysics Data System (ADS)
Grand, Robert J. J.; Kawata, Daisuke; Cropper, Mark
2015-03-01
Radial migration is defined as the change in guiding centre radius of stars and gas caused by gains or losses of angular momentum that result from gravitational interaction with non-axisymmetric structure. This has been shown to have significant impact on the metallicity distribution in galactic discs, and therefore affects the interpretation of Galactic archaeology. We use a simulation of a Milky Way-sized galaxy to examine the effect of radial migration on the star and gas radial metallicity distribution. We find that both the star and gas component show significant radial migration. The stellar radial metallicity gradient remains almost unchanged but the radial metallicity distribution of the stars is broadened to produce a greater dispersion at all radii. However, the metallicity dispersion of the gas remains narrow. We find that the main drivers of the gas metallicity distribution evolution are metal enrichment and mixing: more efficient metal enrichment in the inner region maintains a negative slope in the radial metallicity distribution, and the metal mixing ensures the tight relationship of the gas metallicity with the radius. The metallicity distribution function reproduces the trend in the age-metallicity relation found from observations for stars younger than 1.0 Gyr in the Milky Way.
Abstract models of molecular walkers
NASA Astrophysics Data System (ADS)
Semenov, Oleg
Recent advances in single-molecule chemistry have led to designs for artificial multi-pedal walkers that follow tracks of chemicals. The walkers, called molecular spiders, consist of a rigid chemically inert body and several flexible enzymatic legs. The legs can reversibly bind to chemical substrates on a surface, and through their enzymatic action convert them to products. We study abstract models of molecular spiders to evaluate how efficiently they can perform two tasks: molecular transport of cargo over tracks and search for targets on finite surfaces. For the single-spider model our simulations show a transient behavior wherein certain spiders move superdiffusively over significant distances and times. This gives the spiders potential as a faster-than-diffusion transport mechanism. However, analysis shows that single-spider motion eventually decays into an ordinary diffusive motion, owing to the ever increasing size of the region of products. Inspired by cooperative behavior of natural molecular walkers, we propose a symmetric exclusion process (SEP) model for multiple walkers interacting as they move over a one-dimensional lattice. We show that when walkers are sequentially released from the origin, the collective effect is to prevent the leading walkers from moving too far backwards. Hence, there is an effective outward pressure on the leading walkers that keeps them moving superdiffusively for longer times. Despite this improvement the leading spider eventually slows down and moves diffusively, similarly to a single spider. The slowdown happens because all spiders behind the leading spiders never encounter substrates, and thus they are never biased. They cannot keep up with leading spiders, and cannot put enough pressure on them. Next, we investigate search properties of a single and multiple spiders moving over one- and two-dimensional surfaces with various absorbing and reflecting boundaries. For the single-spider model we evaluate by how much the
Determining Enzyme Activity by Radial Diffusion
ERIC Educational Resources Information Center
Davis, Bill D.
1977-01-01
Discusses advantages of radial diffusion assay in determining presence of enzyme and/or rough approximation of amount of enzyme activities. Procedures are included for the preparation of starch-agar plates, and the application and determination of enzyme. Techniques using plant materials (homogenates, tissues, ungerminated embryos, and seedlings)…
Radial velocities of Planetary Nebulae revisited
NASA Astrophysics Data System (ADS)
Vázquez, Roberto; Ayala, Sandra A.; Wendolyn Blanco Cárdenas, Mónica; Contreras, María E.; Gómez-Muñoz, Marco Antonio; Guillén, Pedro F.; Olguín, Lorenzo; Ramos-Larios, Gerardo; Sabin, Laurence; Zavala, Saúl A.
2015-08-01
We present a new determination of radial velocities of a sample of Galactic Planetary Nebulae (PNe) using a systematic method and the same instrumental setting: the long-slit high-dispersion Manchester Echelle Spectrograph (MES) on the 2.1-m telescope at the San Pedro Mártir Observatory (OAN-SPM; Mexico). This project was inspired by the work of Schneider et al. (1983, A&AS, 52, 399), which has been an important reference during the last decades. Radial velocities of gaseous nebulae can be obtained using the central wavelength of a Gaussian fit, even when there is an expansion velocity, as expected in PNe, but with not enough resolution to see a spectral line splitting. We have used the software SHAPE, a morpho-kinematic modeling and reconstruction tool for astrophysical objects (Steffen et al. 2011, IEEE Trans. Vis. Comput. Graphics, 17, 454), to prove that non-uniform density or brightness, on an expanding shell, can lead to mistaken conclusions about the radial velocity. To determine radial velocities, we only use the spectral data in which a spectral line-splitting is seen, avoiding thus the problem of the possible biased one-Gaussian fit. Cases when this method is not recommended are discussed.This project has been supported by grant PAPIIT-DGAPA-UNAM IN107914. MWB is in grateful receipt of a DGAPA-UNAM postdoctoral scholarship. MAG acknowledges CONACYT for his graduate scholarship.
NASA contributions to radial turbine aerodynamic analyses
NASA Technical Reports Server (NTRS)
Glassman, A. J.
1980-01-01
A brief description of the radial turbine and its analysis needs is followed by discussions of five analytical areas; design geometry and performance, off design performance, blade row flow, scroll flow, and duct flow. The functions of the programs, areas of applicability, and limitations and uncertainties are emphasized. Both past contributions and current activities are discussed.
Research & writing basics: elements of the abstract.
Krasner, D; Van Rijswijk, L
1995-04-01
Writing an abstract is a challenging skill that requires precision and care. Criteria for well-formulated abstracts and abstract guidelines for 2 types of articles (empirical studies and reviews or theoretical articles) as well as a description of the content of a structured abstract are presented. Details were gleaned from a review of the literature including the American Medical Association Manual of Style, Eighth Edition and the Publication Manual of the American Psychological Association, Fourth Edition. A good abstract is like a crystal: it is a clear, sharp synthesis that elucidates meaning for the reader.
Research & writing basics: elements of the abstract.
Krasner, D; Van Rijswijk, L
1995-04-01
Writing an abstract is a challenging skill that requires precision and care. Criteria for well-formulated abstracts and abstract guidelines for 2 types of articles (empirical studies and reviews or theoretical articles) as well as a description of the content of a structured abstract are presented. Details were gleaned from a review of the literature including the American Medical Association Manual of Style, Eighth Edition and the Publication Manual of the American Psychological Association, Fourth Edition. A good abstract is like a crystal: it is a clear, sharp synthesis that elucidates meaning for the reader. PMID:7546111
Torrent, Daniel; Sánchez-Dehesa, José
2009-08-01
We demonstrate that metamaterials with anisotropic properties can be used to develop a new class of periodic structures that has been named radial wave crystals. They can be sonic or photonic, and wave propagation along the radial directions is obtained through Bloch states like in usual sonic or photonic crystals. The band structure of the proposed structures can be tailored in a large amount to get exciting novel wave phenomena. For example, it is shown that acoustical cavities based on radial sonic crystals can be employed as passive devices for beam forming or dynamically orientated antennas for sound localization.
NASA Astrophysics Data System (ADS)
Kriswanto, Jamari
2016-04-01
Permanent magnet bearings (PMB) are contact free bearings which utilize the forces generated by the magnets. PMB in this work is a type of radial PMB, which functions as the radial bearings of the Horizontal Axis Wind Turbine (HAWT) rotor shaft. Radial PMB should have a greater radial force than the radial force HAWT rotor shaft (bearing load). This paper presents a modeling and experiments to calculate the radial force of the radial PMB. This paper also presents rotational speed test of the radial PMB compared to conventional bearings for HAWT applications. Modeling using COMSOL Multiphysics 4.3b with the magnetic fields physics models. Experiments were conducted by measuring the displacement of the rotor to the stator for a given load variation. Results of the two methods showed that the large displacement then the radial force would be greater. Radial forces of radial PMB is greater than radial forces of HAWT rotor shaft. The rotational speed test results of HAWT that used radial PMB produced higher rotary than conventional bearings with an average increase of 87.4%. Increasing rotational speed occured because radial PMB had no friction. HAWT that used radial PMB rotated at very low wind speeds are 1.4 m/s with a torque of 0.043 Nm, while the HAWT which uses conventional bearing started rotating at a wind speed of 4.4 m/s and required higher torque of 0.104 N.
2013 SYR Accepted Poster Abstracts.
2013-01-01
SYR 2013 Accepted Poster abstracts: 1. Benefits of Yoga as a Wellness Practice in a Veterans Affairs (VA) Health Care Setting: If You Build It, Will They Come? 2. Yoga-based Psychotherapy Group With Urban Youth Exposed to Trauma. 3. Embodied Health: The Effects of a Mind�Body Course for Medical Students. 4. Interoceptive Awareness and Vegetable Intake After a Yoga and Stress Management Intervention. 5. Yoga Reduces Performance Anxiety in Adolescent Musicians. 6. Designing and Implementing a Therapeutic Yoga Program for Older Women With Knee Osteoarthritis. 7. Yoga and Life Skills Eating Disorder Prevention Among 5th Grade Females: A Controlled Trial. 8. A Randomized, Controlled Trial Comparing the Impact of Yoga and Physical Education on the Emotional and Behavioral Functioning of Middle School Children. 9. Feasibility of a Multisite, Community based Randomized Study of Yoga and Wellness Education for Women With Breast Cancer Undergoing Chemotherapy. 10. A Delphi Study for the Development of Protocol Guidelines for Yoga Interventions in Mental Health. 11. Impact Investigation of Breathwalk Daily Practice: Canada�India Collaborative Study. 12. Yoga Improves Distress, Fatigue, and Insomnia in Older Veteran Cancer Survivors: Results of a Pilot Study. 13. Assessment of Kundalini Mantra and Meditation as an Adjunctive Treatment With Mental Health Consumers. 14. Kundalini Yoga Therapy Versus Cognitive Behavior Therapy for Generalized Anxiety Disorder and Co-Occurring Mood Disorder. 15. Baseline Differences in Women Versus Men Initiating Yoga Programs to Aid Smoking Cessation: Quitting in Balance Versus QuitStrong. 16. Pranayam Practice: Impact on Focus and Everyday Life of Work and Relationships. 17. Participation in a Tailored Yoga Program is Associated With Improved Physical Health in Persons With Arthritis. 18. Effects of Yoga on Blood Pressure: Systematic Review and Meta-analysis. 19. A Quasi-experimental Trial of a Yoga based Intervention to Reduce Stress and
2013 SYR Accepted Poster Abstracts.
2013-01-01
SYR 2013 Accepted Poster abstracts: 1. Benefits of Yoga as a Wellness Practice in a Veterans Affairs (VA) Health Care Setting: If You Build It, Will They Come? 2. Yoga-based Psychotherapy Group With Urban Youth Exposed to Trauma. 3. Embodied Health: The Effects of a Mind�Body Course for Medical Students. 4. Interoceptive Awareness and Vegetable Intake After a Yoga and Stress Management Intervention. 5. Yoga Reduces Performance Anxiety in Adolescent Musicians. 6. Designing and Implementing a Therapeutic Yoga Program for Older Women With Knee Osteoarthritis. 7. Yoga and Life Skills Eating Disorder Prevention Among 5th Grade Females: A Controlled Trial. 8. A Randomized, Controlled Trial Comparing the Impact of Yoga and Physical Education on the Emotional and Behavioral Functioning of Middle School Children. 9. Feasibility of a Multisite, Community based Randomized Study of Yoga and Wellness Education for Women With Breast Cancer Undergoing Chemotherapy. 10. A Delphi Study for the Development of Protocol Guidelines for Yoga Interventions in Mental Health. 11. Impact Investigation of Breathwalk Daily Practice: Canada�India Collaborative Study. 12. Yoga Improves Distress, Fatigue, and Insomnia in Older Veteran Cancer Survivors: Results of a Pilot Study. 13. Assessment of Kundalini Mantra and Meditation as an Adjunctive Treatment With Mental Health Consumers. 14. Kundalini Yoga Therapy Versus Cognitive Behavior Therapy for Generalized Anxiety Disorder and Co-Occurring Mood Disorder. 15. Baseline Differences in Women Versus Men Initiating Yoga Programs to Aid Smoking Cessation: Quitting in Balance Versus QuitStrong. 16. Pranayam Practice: Impact on Focus and Everyday Life of Work and Relationships. 17. Participation in a Tailored Yoga Program is Associated With Improved Physical Health in Persons With Arthritis. 18. Effects of Yoga on Blood Pressure: Systematic Review and Meta-analysis. 19. A Quasi-experimental Trial of a Yoga based Intervention to Reduce Stress and
R.J. Garrett
2002-01-14
As part of the internal Integrated Safety Management Assessment verification process, it was determined that there was a lack of documentation that summarizes the safety basis of the current Yucca Mountain Project (YMP) site characterization activities. It was noted that a safety basis would make it possible to establish a technically justifiable graded approach to the implementation of the requirements identified in the Standards/Requirements Identification Document. The Standards/Requirements Identification Documents commit a facility to compliance with specific requirements and, together with the hazard baseline documentation, provide a technical basis for ensuring that the public and workers are protected. This Safety Basis Report has been developed to establish and document the safety basis of the current site characterization activities, establish and document the hazard baseline, and provide the technical basis for identifying structures, systems, and components (SSCs) that perform functions necessary to protect the public, the worker, and the environment from hazards unique to the YMP site characterization activities. This technical basis for identifying SSCs serves as a grading process for the implementation of programs such as Conduct of Operations (DOE Order 5480.19) and the Suspect/Counterfeit Items Program. In addition, this report provides a consolidated summary of the hazards analyses processes developed to support the design, construction, and operation of the YMP site characterization facilities and, therefore, provides a tool for evaluating the safety impacts of changes to the design and operation of the YMP site characterization activities.
Allsman, R.; Barrett, K.; Busby, L.; Chiu, Y.; Crotinger, J.; Dubois, B.; Dubois, P.F.; Langdon, B.; Motteler, Z.C.; Takemoto, J.; Taylor, S.; Willmann, P.; Wilson, S. )
1993-08-01
BASIS9.4 is a system for developing interactive computer programs in Fortran, with some support for C and C++ as well. Using BASIS9.4 you can create a program that has a sophisticated programming language as its user interface so that the user can set, calculate with, and plot, all the major variables in the program. The program author writes only the scientific part of the program; BASIS9.4 supplies an environment in which to exercise that scientific programming which includes an interactive language, an interpreter, graphics, terminal logs, error recovery, macros, saving and retrieving variables, formatted I/O, and online documentation.
Entropy generation of radial rotation convective channels
NASA Astrophysics Data System (ADS)
Alić, Fikret
2012-03-01
The exchange of heat between two fluids is established by radial rotating pipe or a channel. The hotter fluid flows through the pipe, while the cold fluid is ambient air. Total length of pipe is made up of multiple sections of different shape and position in relation to the common axis of rotation. In such heat exchanger the hydraulic and thermal irreversibility of the hotter and colder fluid occur. Therefore, the total entropy generated within the radial rotating pipe consists of the total entropy of hotter and colder fluid, taking into account all the hydraulic and thermal irreversibility of both fluids. Finding a mathematical model of the total generated entropy is based on coupled mathematical expressions that combine hydraulic and thermal effects of both fluids with the complex geometry of the radial rotating pipe. Mathematical model follows the each section of the pipe and establishes the function between the sections, so the total generated entropy is different from section to section of the pipe. In one section of the pipe thermal irreversibility may dominate over the hydraulic irreversibility, while in another section of the pipe the situation may be reverse. In this paper, continuous analytic functions that connect sections of pipe in geometric meaning are associated with functions that describe the thermo-hydraulic effects of hotter and colder fluid. In this way, the total generated entropy of the radial rotating pipe is a continuous analytic function of any complex geometry of the rotating pipe. The above method of establishing a relationship between the continuous function of entropy with the complex geometry of the rotating pipe enables indirect monitoring of unnecessary hydraulic and thermal losses of both fluids. Therefore, continuous analytic functions of generated entropy enable analysis of hydraulic and thermal irreversibility of individual sections of pipe, as well as the possibility of improving the thermal-hydraulic performance of the rotating
Radial tunnel syndrome. A retrospective review of 30 decompressions of the radial nerve.
Lawrence, T; Mobbs, P; Fortems, Y; Stanley, J K
1995-08-01
Radial tunnel syndrome results from compression of the radial nerve by the free edge of the supinator muscle or closely related structures in the vicinity of the elbow joint. Despite numerous reports on the surgical management of this disorder, it remains largely unrecognized and often neglected. The symptoms of radial tunnel syndrome can resemble those of tennis elbow, chronic wrist pain or tenosynovitis. Reliable objective criteria are not available to differentiate between these pathologies. These difficulties are discussed in relation to 29 patients who underwent 30 primary explorations and proximal decompressions of the radial nerve. Excellent or good results were obtained in 70%, fair results in 13% and poor results in 17% of patients. The results can be satisfactory despite the prolonged duration of symptoms. We believe that a diagnosis of radial tunnel syndrome should always be born in mind when dealing with patients with forearm and wrist pain that has not responded to more conventional treatment. Patients with occupations requiring repetitive manual tasks seem to be particularly at risk of developing radial tunnel syndrome and it is also interesting to note that 66% of patients with on-going medico-legal claims had successful outcomes following surgery. PMID:7594982
Radial spline assembly for antifriction bearings
NASA Technical Reports Server (NTRS)
Moore, Jerry H. (Inventor)
1993-01-01
An outer race carrier is constructed for receiving an outer race of an antifriction bearing assembly. The carrier in turn is slidably fitted in an opening of a support wall to accommodate slight axial movements of a shaft. A plurality of longitudinal splines on the carrier are disposed to be fitted into matching slots in the opening. A deadband gap is provided between sides of the splines and slots, with a radial gap at ends of the splines and slots and a gap between the splines and slots sized larger than the deadband gap. With this construction, operational distortions (slope) of the support wall are accommodated by the larger radial gaps while the deadband gaps maintain a relatively high springrate of the housing. Additionally, side loads applied to the shaft are distributed between sides of the splines and slots, distributing such loads over a larger surface area than a race carrier of the prior art.
NASA Astrophysics Data System (ADS)
Douma, M.; Ligierko, G.; Angelov, I.
2008-10-01
The need for information has increased exponentially over the past decades. The current systems for constructing, exploring, classifying, organizing, and searching information face the growing challenge of enabling their users to operate efficiently and intuitively in knowledge-heavy environments. This paper presents SpicyNodes, an advanced user interface for difficult interaction contexts. It is based on an underlying structure known as a radial map, which allows users to manipulate and interact in a natural manner with entities called nodes. This technology overcomes certain limitations of existing solutions and solves the problem of browsing complex sets of linked information. SpicyNodes is also an organic system that projects users into a living space, stimulating exploratory behavior and fostering creative thought. Our interactive radial layout is used for educational purposes and has the potential for numerous other applications.
Development of large radial turbine turbochargers
Winn, K.R.; Hirst, P.; Kay, P.
1996-12-31
The use of fully radial turbochargers for medium speed diesel engines have largely been restricted to distillate fuel operation at relatively modest pressure ratios. Pressures on costs per kW have forced the industry to push for increases in rating and range of operation for these machines. The development of a high pressure ratio radial turbocharger with the capability to operate reliably on heavy fuel has become a high priority. This paper discusses the development of a range of such machines to cover engine output of between 500 kW and 1.6 MW. The original design of the first turbocharger in the range, the NAPIER 047, is reviewed together with the development and operational experiences gained to date. These have been incorporated into the latest two turbochargers in the range, the NAPIER 057 and 067. The paper includes descriptions of the means taken to achieve minimum time to market and low cost of manufacture.
Abstract Object Creation in Dynamic Logic
NASA Astrophysics Data System (ADS)
Ahrendt, Wolfgang; de Boer, Frank S.; Grabe, Immo
In this paper we give a representation of a weakest precondition calculus for abstract object creation in dynamic logic, the logic underlying the KeY theorem prover. This representation allows to both specify and verify properties of objects at the abstraction level of the (object-oriented) programming language. Objects which are not (yet) created never play any role, neither in the specification nor in the verification of properties. Further, we show how to symbolically execute abstract object creation.
Abstract and concrete sentences, embodiment, and languages.
Scorolli, Claudia; Binkofski, Ferdinand; Buccino, Giovanni; Nicoletti, Roberto; Riggio, Lucia; Borghi, Anna Maria
2011-01-01
One of the main challenges of embodied theories is accounting for meanings of abstract words. The most common explanation is that abstract words, like concrete ones, are grounded in perception and action systems. According to other explanations, abstract words, differently from concrete ones, would activate situations and introspection; alternatively, they would be represented through metaphoric mapping. However, evidence provided so far pertains to specific domains. To be able to account for abstract words in their variety we argue it is necessary to take into account not only the fact that language is grounded in the sensorimotor system, but also that language represents a linguistic-social experience. To study abstractness as a continuum we combined a concrete (C) verb with both a concrete and an abstract (A) noun; and an abstract verb with the same nouns previously used (grasp vs. describe a flower vs. a concept). To disambiguate between the semantic meaning and the grammatical class of the words, we focused on two syntactically different languages: German and Italian. Compatible combinations (CC, AA) were processed faster than mixed ones (CA, AC). This is in line with the idea that abstract and concrete words are processed preferentially in parallel systems - abstract in the language system and concrete more in the motor system, thus costs of processing within one system are the lowest. This parallel processing takes place most probably within different anatomically predefined routes. With mixed combinations, when the concrete word preceded the abstract one (CA), participants were faster, regardless of the grammatical class and the spoken language. This is probably due to the peculiar mode of acquisition of abstract words, as they are acquired more linguistically than perceptually. Results confirm embodied theories which assign a crucial role to both perception-action and linguistic experience for abstract words. PMID:21954387
Writing an abstract for a scientific conference.
Simkhada, P; van Teijlingen, E; Hundley, V; Simkhada, B D
2013-01-01
For most students and junior researchers, writing an abstract for a poster or oral presentation at a conference is the first piece they may write for an audience other than their university tutors or examiners. Since some researchers struggle with this process we have put together some advice on issues to consider when writing a conference abstract. We highlight a number of issues to bear in mind when constructing one's abstract.
Radial rib antenna surface deviation analysis program
NASA Technical Reports Server (NTRS)
Coyner, J. V., Jr.
1971-01-01
A digital computer program was developed which analyzes any radial rib antenna with ribs radiating from a central hub. The program has the capability for calculating the antenna surface contour (reversed pillowing effect), the optimum rib shape for minimizing the rms surface error, and the actual rms surface error. Rib deflection due to mesh tension and catenary cable tension can also be compensated for, and the pattern from which the mesh gores are cut can be determined.
A brief on writing a successful abstract.
Gambescia, Stephen F
2013-01-01
The abstract for an article submitted to a clinical or academic journal often gets little attention in the manuscript preparation process. The abstract serves multiple purposes in scholarly work dissemination, including the one piece of information reviewers have to invite presenters to professional conferences. Therefore, the abstract can be the most important and should be the most powerful 150-250 words written by authors of scholarly work. This brief for healthcare practitioners, junior faculty, and students provides general comments, details, nuances and tips and explains the various uses of the abstract for publications and presentations in the healthcare field.
Neural correlates of abstract verb processing.
Rodríguez-Ferreiro, Javier; Gennari, Silvia P; Davies, Robert; Cuetos, Fernando
2011-01-01
The present study investigated the neural correlates of the processing of abstract (low imageability) verbs. An extensive body of literature has investigated concrete versus abstract nouns but little is known about how abstract verbs are processed. Spanish abstract verbs including emotion verbs (e.g., amar, "to love"; molestar, "to annoy") were compared to concrete verbs (e.g., llevar, "to carry"; arrastrar, "to drag"). Results indicated that abstract verbs elicited stronger activity in regions previously associated with semantic retrieval such as inferior frontal, anterior temporal, and posterior temporal regions, and that concrete and abstract activation networks (compared to that of pseudoverbs) were partially distinct, with concrete verbs eliciting more posterior activity in these regions. In contrast to previous studies investigating nouns, verbs strongly engage both left and right inferior frontal gyri, suggesting, as previously found, that right prefrontal cortex aids difficult semantic retrieval. Together with previous evidence demonstrating nonverbal conceptual roles for the active regions as well as experiential content for abstract word meanings, our results suggest that abstract verbs impose greater demands on semantic retrieval or property integration, and are less consistent with the view that abstract words recruit left-lateralized regions because they activate verbal codes or context, as claimed by proponents of the dual-code theory. Moreover, our results are consistent with distributed accounts of semantic memory because distributed networks may coexist with varying retrieval demands.
Neural correlates of abstract verb processing.
Rodríguez-Ferreiro, Javier; Gennari, Silvia P; Davies, Robert; Cuetos, Fernando
2011-01-01
The present study investigated the neural correlates of the processing of abstract (low imageability) verbs. An extensive body of literature has investigated concrete versus abstract nouns but little is known about how abstract verbs are processed. Spanish abstract verbs including emotion verbs (e.g., amar, "to love"; molestar, "to annoy") were compared to concrete verbs (e.g., llevar, "to carry"; arrastrar, "to drag"). Results indicated that abstract verbs elicited stronger activity in regions previously associated with semantic retrieval such as inferior frontal, anterior temporal, and posterior temporal regions, and that concrete and abstract activation networks (compared to that of pseudoverbs) were partially distinct, with concrete verbs eliciting more posterior activity in these regions. In contrast to previous studies investigating nouns, verbs strongly engage both left and right inferior frontal gyri, suggesting, as previously found, that right prefrontal cortex aids difficult semantic retrieval. Together with previous evidence demonstrating nonverbal conceptual roles for the active regions as well as experiential content for abstract word meanings, our results suggest that abstract verbs impose greater demands on semantic retrieval or property integration, and are less consistent with the view that abstract words recruit left-lateralized regions because they activate verbal codes or context, as claimed by proponents of the dual-code theory. Moreover, our results are consistent with distributed accounts of semantic memory because distributed networks may coexist with varying retrieval demands. PMID:20044889
Analysis of complex networks using aggressive abstraction.
Colbaugh, Richard; Glass, Kristin.; Willard, Gerald
2008-10-01
This paper presents a new methodology for analyzing complex networks in which the network of interest is first abstracted to a much simpler (but equivalent) representation, the required analysis is performed using the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit abstractions that are simultaneously dramatically simplifying and property preserving we call these aggressive abstractions -- and which can therefore be analyzed using the proposed approach. We then introduce and develop two forms of aggressive abstraction: 1.) finite state abstraction, in which dynamical networks with uncountable state spaces are modeled using finite state systems, and 2.) onedimensional abstraction, whereby high dimensional network dynamics are captured in a meaningful way using a single scalar variable. In each case, the property preserving nature of the abstraction process is rigorously established and efficient algorithms are presented for computing the abstraction. The considerable potential of the proposed approach to complex networks analysis is illustrated through case studies involving vulnerability analysis of technological networks and predictive analysis for social processes.
Development of a Radial Deconsolidation Method
Helmreich, Grant W.; Montgomery, Fred C.; Hunn, John D.
2015-12-01
A series of experiments have been initiated to determine the retention or mobility of fission products* in AGR fuel compacts [Petti, et al. 2010]. This information is needed to refine fission product transport models. The AGR-3/4 irradiation test involved half-inch-long compacts that each contained twenty designed-to-fail (DTF) particles, with 20-μm thick carbon-coated kernels whose coatings were deliberately fabricated such that they would crack under irradiation, providing a known source of post-irradiation isotopes. The DTF particles in these compacts were axially distributed along the compact centerline so that the diffusion of fission products released from the DTF kernels would be radially symmetric [Hunn, et al. 2012; Hunn et al. 2011; Kercher, et al. 2011; Hunn, et al. 2007]. Compacts containing DTF particles were irradiated at Idaho National Laboratory (INL) at the Advanced Test Reactor (ATR) [Collin, 2015]. Analysis of the diffusion of these various post-irradiation isotopes through the compact requires a method to radially deconsolidate the compacts so that nested-annular volumes may be analyzed for post-irradiation isotope inventory in the compact matrix, TRISO outer pyrolytic carbon (OPyC), and DTF kernels. An effective radial deconsolidation method and apparatus appropriate to this application has been developed and parametrically characterized.
Approximate theory for radial filtration/consolidation
Tiller, F.M.; Kirby, J.M.; Nguyen, H.L.
1996-10-01
Approximate solutions are developed for filtration and subsequent consolidation of compactible cakes on a cylindrical filter element. Darcy`s flow equation is coupled with equations for equilibrium stress under the conditions of plane strain and axial symmetry for radial flow inwards. The solutions are based on power function forms involving the relationships of the solidosity {epsilon}{sub s} (volume fraction of solids) and the permeability K to the solids effective stress p{sub s}. The solutions allow determination of the various parameters in the power functions and the ratio k{sub 0} of the lateral to radial effective stress (earth stress ratio). Measurements were made of liquid and effective pressures, flow rates, and cake thickness versus time. Experimental data are presented for a series of tests in a radial filtration cell with a central filter element. Slurries prepared from two materials (Microwate, which is mainly SrSO{sub 4}, and kaolin) were used in the experiments. Transient deposition of filter cakes was followed by static (i.e., no flow) conditions in the cake. The no-flow condition was accomplished by introducing bentonite which produced a nearly impermeable layer with negligible flow. Measurement of the pressure at the cake surface and the transmitted pressure on the central element permitted calculation of k{sub 0}.
Interactional Metadiscourse in Research Article Abstracts
ERIC Educational Resources Information Center
Gillaerts, Paul; Van de Velde, Freek
2010-01-01
This paper deals with interpersonality in research article abstracts analysed in terms of interactional metadiscourse. The evolution in the distribution of three prominent interactional markers comprised in Hyland's (2005a) model, viz. hedges, boosters and attitude markers, is investigated in three decades of abstract writing in the field of…
Tour the Galaxy of the Abstract.
ERIC Educational Resources Information Center
Kennedy, Patricia
2003-01-01
Describes an abstract art unit in which students in an introductory art course created abstract art inspired by the work of M. C. Escher. Explains that some students are unsure of their drawing ability. States this unit helps them overcome their fears. (CMK)
Abstracting in the Context of Spontaneous Learning
ERIC Educational Resources Information Center
Williams, Gaye
2007-01-01
There is evidence that spontaneous learning leads to relational understanding and high positive affect. To study spontaneous abstracting, a model was constructed by combining the RBC model of abstraction with Krutetskii's mental activities. Using video-stimulated interviews, the model was then used to analyze the behavior of two Year 8 students…
Interpreting Abstract Interpretations in Membership Equational Logic
NASA Technical Reports Server (NTRS)
Fischer, Bernd; Rosu, Grigore
2001-01-01
We present a logical framework in which abstract interpretations can be naturally specified and then verified. Our approach is based on membership equational logic which extends equational logics by membership axioms, asserting that a term has a certain sort. We represent an abstract interpretation as a membership equational logic specification, usually as an overloaded order-sorted signature with membership axioms. It turns out that, for any term, its least sort over this specification corresponds to its most concrete abstract value. Maude implements membership equational logic and provides mechanisms to calculate the least sort of a term efficiently. We first show how Maude can be used to get prototyping of abstract interpretations "for free." Building on the meta-logic facilities of Maude, we further develop a tool that automatically checks and abstract interpretation against a set of user-defined properties. This can be used to select an appropriate abstract interpretation, to characterize the specified loss of information during abstraction, and to compare different abstractions with each other.
Title I, Higher Education Act Program Abstracts.
ERIC Educational Resources Information Center
Miller, Lorna M., Ed.
The 1979 edition of the Title I, Higher Education Act Program Abstracts is presented. Directed toward state Title I, HEA administrators, the program abstracts are made available in order to encourage nationwide program replication of those tested and evaluated programs that have been conducted with Title I support by institutions of higher…
New Features in the ADS Abstract Service
NASA Technical Reports Server (NTRS)
Eichhorn, Guenther; Accomazzi, Alberto; Grant, Carolyn S.; Kurtz, Michael J.; Henneken, Edwin A.; Thompson, Donna M.; Murray, Stephen S.
2005-01-01
The NASA-ADS Abstract Service provides a sophisticated search capability for the literature in Astronomy, Planetary Sciences, Physics/Geophysics, and Space Instrumentation. The ADS is funded by NASA and access to the ADS services is free to anybody world-wide without restrictions. It allows the user to search the literature by author, title, and abstract text.
Youth Studies Abstracts. Vol. 4 No. 1.
ERIC Educational Resources Information Center
Youth Studies Abstracts, 1985
1985-01-01
This volume contains abstracts of 76 projects (most of which were conducted in Australia and New Zealand) concerned with programs for youth and with social and educational developments affecting youth. The abstracts are arranged in the following two categories: (1) Social and Educational Developments: Policy, Analysis, Research; and (2) Programs:…
Abstractions of Awareness: Aware of What?
NASA Astrophysics Data System (ADS)
Metaxas, Georgios; Markopoulos, Panos
This chapter presents FN-AAR, an abstract model of awareness systems. The purpose of the model is to capture in a concise and abstract form essential aspects of awareness systems, many of which have been discussed in design essays or in the context of evaluating specific design solutions.
Third LDEF Post-Retrieval Symposium Abstracts
NASA Technical Reports Server (NTRS)
Levine, Arlene S. (Compiler)
1993-01-01
This volume is a compilation of abstracts submitted to the Third Long Duration Exposure Facility (LDEF) Post-Retrieval Symposium. The abstracts represent the data analysis of the 57 experiments flown on the LDEF. The experiments include materials, coatings, thermal systems, power and propulsion, science (cosmic ray, interstellar gas, heavy ions, micrometeoroid, etc.), electronics, optics, and life science.
Some Call It Stone: Teaching Abstract Sculpture
ERIC Educational Resources Information Center
Asher, Rikki
2004-01-01
Abstract visual art is not for everybody. Some people find it threatening, uncomfortable, and often, inaccessible. Understandably, this can result in a lack of attention paid to nonrepresentational works of art in the visual arts curriculum. This article describes an experiential, hands-on, field trip that sought to demystify abstract sculpture,…
Foundations of the Bandera Abstraction Tools
NASA Technical Reports Server (NTRS)
Hatcliff, John; Dwyer, Matthew B.; Pasareanu, Corina S.; Robby
2003-01-01
Current research is demonstrating that model-checking and other forms of automated finite-state verification can be effective for checking properties of software systems. Due to the exponential costs associated with model-checking, multiple forms of abstraction are often necessary to obtain system models that are tractable for automated checking. The Bandera Tool Set provides multiple forms of automated support for compiling concurrent Java software systems to models that can be supplied to several different model-checking tools. In this paper, we describe the foundations of Bandera's data abstraction mechanism which is used to reduce the cardinality (and the program's state-space) of data domains in software to be model-checked. From a technical standpoint, the form of data abstraction used in Bandera is simple, and it is based on classical presentations of abstract interpretation. We describe the mechanisms that Bandera provides for declaring abstractions, for attaching abstractions to programs, and for generating abstracted programs and properties. The contributions of this work are the design and implementation of various forms of tool support required for effective application of data abstraction to software components written in a programming language like Java which has a rich set of linguistic features.
Abstraction and context in concept representation.
Hampton, James A
2003-01-01
This paper develops the notion of abstraction in the context of the psychology of concepts, and discusses its relation to context dependence in knowledge representation. Three general approaches to modelling conceptual knowledge from the domain of cognitive psychology are discussed, which serve to illustrate a theoretical dimension of increasing levels of abstraction. PMID:12903660
A Method for Automatically Abstracting Visual Documents.
ERIC Educational Resources Information Center
Rorvig, Mark E.
1993-01-01
Describes a method for automatically selecting key frames that can be used to represent the total image sequence of visual documents. An abstracting algorithm developed at the National Aeronautics and Space Administration is explained, and extensive examples of abstracted motion sequences are presented. (eight references) (LRW)
Code of Federal Regulations, 2010 CFR
2010-07-01
... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false The abstract. 1.438 Section 1.438 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF... application will not affect the granting of a filing date. However, failure to furnish an abstract within...
Code of Federal Regulations, 2014 CFR
2014-07-01
... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false The abstract. 1.438 Section 1.438 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF... application will not affect the granting of a filing date. However, failure to furnish an abstract within...
Code of Federal Regulations, 2012 CFR
2012-07-01
... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false The abstract. 1.438 Section 1.438 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF... application will not affect the granting of a filing date. However, failure to furnish an abstract within...
14 CFR 71.7 - Bearings, radials, and mileages.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Bearings, radials, and mileages. 71.7 Section 71.7 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION... REPORTING POINTS § 71.7 Bearings, radials, and mileages. All bearings and radials in this part are true...
14 CFR 73.5 - Bearings; radials; miles.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Bearings; radials; miles. 73.5 Section 73.5 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIRSPACE SPECIAL USE AIRSPACE General § 73.5 Bearings; radials; miles. (a) All bearings and radials in this...
14 CFR 71.7 - Bearings, radials, and mileages.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Bearings, radials, and mileages. 71.7 Section 71.7 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION... REPORTING POINTS § 71.7 Bearings, radials, and mileages. All bearings and radials in this part are true...
14 CFR 73.5 - Bearings; radials; miles.
Code of Federal Regulations, 2011 CFR
2011-01-01
... 14 Aeronautics and Space 2 2011-01-01 2011-01-01 false Bearings; radials; miles. 73.5 Section 73.5 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIRSPACE SPECIAL USE AIRSPACE General § 73.5 Bearings; radials; miles. (a) All bearings and radials in this...
14 CFR 71.7 - Bearings, radials, and mileages.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Bearings, radials, and mileages. 71.7 Section 71.7 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION... REPORTING POINTS § 71.7 Bearings, radials, and mileages. All bearings and radials in this part are true...
14 CFR 73.5 - Bearings; radials; miles.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 14 Aeronautics and Space 2 2012-01-01 2012-01-01 false Bearings; radials; miles. 73.5 Section 73.5 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIRSPACE SPECIAL USE AIRSPACE General § 73.5 Bearings; radials; miles. (a) All bearings and radials in this...
14 CFR 73.5 - Bearings; radials; miles.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Bearings; radials; miles. 73.5 Section 73.5 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIRSPACE SPECIAL USE AIRSPACE General § 73.5 Bearings; radials; miles. (a) All bearings and radials in this...
14 CFR 71.7 - Bearings, radials, and mileages.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Bearings, radials, and mileages. 71.7 Section 71.7 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION... REPORTING POINTS § 71.7 Bearings, radials, and mileages. All bearings and radials in this part are true...
14 CFR 73.5 - Bearings; radials; miles.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 14 Aeronautics and Space 2 2014-01-01 2014-01-01 false Bearings; radials; miles. 73.5 Section 73.5 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) AIRSPACE SPECIAL USE AIRSPACE General § 73.5 Bearings; radials; miles. (a) All bearings and radials in this...
14 CFR 71.7 - Bearings, radials, and mileages.
Code of Federal Regulations, 2013 CFR
2013-01-01
... 14 Aeronautics and Space 2 2013-01-01 2013-01-01 false Bearings, radials, and mileages. 71.7 Section 71.7 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION... REPORTING POINTS § 71.7 Bearings, radials, and mileages. All bearings and radials in this part are true...
Radial Extracorporeal Shock Wave Therapy in a Person With Advanced Osteonecrosis of the Femoral Head
Ma, Yue Wen; Jiang, Dong Lei; Zhang, Dai; Wang, Xiao Bei; Yu, Xiao Tong
2016-01-01
ABSTRACT This case report describes the first patient with avascular necrosis of the femoral head of Association Research Circulation Osseous stage IV, treated with radial extracorporeal shock wave therapy. By contrast, previous studies demonstrated the efficacy of a single treatment of focused extracorporeal shock wave therapy in improving pain and Harris Hip Scale in patients with avascular necrosis of the femoral head of Association Research Circulation Osseous stage I to III. The affected hip was treated with 6000 impulses of radial extracorporeal shock wave therapy at 10 Hz and an intensity ranging from 2.5 to 4.0 bar at 7-day intervals for 24 mos. The Harris Hip Scale values were 33, 43, 56, 77, 81, 88, and 92 at baseline and 1, 3, 6, 12, 18, and 24 mos, respectively. The radiographs showed that the subluxation of the right hip was slightly aggravated. Joint effusion was reduced, bone marrow edema disappeared, the density became more uniform, and the gluteal muscles were more developed based on magnetic resonance imaging. Increased tracer uptake was evident along the joint margin and superolateral aspect of the head both before and after radial extracorporeal shock wave therapy. This case report demonstrates the feasibility of long-term radial extracorporeal shock wave therapy in Association Research Circulation Osseous stage IV patients. PMID:27003206
Experimental feasibility study of radial injection cooling of three-pad radial air foil bearings
NASA Astrophysics Data System (ADS)
Shrestha, Suman K.
Air foil bearings use ambient air as a lubricant allowing environment-friendly operation. When they are designed, installed, and operated properly, air foil bearings are very cost effective and reliable solution to oil-free turbomachinery. Because air is used as a lubricant, there are no mechanical contacts between the rotor and bearings and when the rotor is lifted off the bearing, near frictionless quiet operation is possible. However, due to the high speed operation, thermal management is one of the very important design factors to consider. Most widely accepted practice of the cooling method is axial cooling, which uses cooling air passing through heat exchange channels formed underneath the bearing pad. Advantage is no hardware modification to implement the axial cooling because elastic foundation structure of foil bearing serves as a heat exchange channels. Disadvantage is axial temperature gradient on the journal shaft and bearing. This work presents the experimental feasibility study of alternative cooling method using radial injection of cooling air directly on the rotor shaft. The injection speeds, number of nozzles, location of nozzles, total air flow rate are important factors determining the effectiveness of the radial injection cooling method. Effectiveness of the radial injection cooling was compared with traditional axial cooling method. A previously constructed test rig was modified to accommodate a new motor with higher torque and radial injection cooling. The radial injection cooling utilizes the direct air injection to the inlet region of air film from three locations at 120° from one another with each location having three axially separated holes. In axial cooling, a certain axial pressure gradient is applied across the bearing to induce axial cooling air through bump foil channels. For the comparison of the two methods, the same amount of cooling air flow rate was used for both axial cooling and radial injection. Cooling air flow rate was
Abstract quantum computing machines and quantum computational logics
NASA Astrophysics Data System (ADS)
Chiara, Maria Luisa Dalla; Giuntini, Roberto; Sergioli, Giuseppe; Leporini, Roberto
2016-06-01
Classical and quantum parallelism are deeply different, although it is sometimes claimed that quantum Turing machines are nothing but special examples of classical probabilistic machines. We introduce the concepts of deterministic state machine, classical probabilistic state machine and quantum state machine. On this basis, we discuss the question: To what extent can quantum state machines be simulated by classical probabilistic state machines? Each state machine is devoted to a single task determined by its program. Real computers, however, behave differently, being able to solve different kinds of problems. This capacity can be modeled, in the quantum case, by the mathematical notion of abstract quantum computing machine, whose different programs determine different quantum state machines. The computations of abstract quantum computing machines can be linguistically described by the formulas of a particular form of quantum logic, termed quantum computational logic.
Comminuted radial head fractures treated by the Acumed anatomic radial head system
Mou, Zhefei; Chen, Maohua; Xiong, Yan; Fan, Zhihang; Wang, Aimin; Wang, Ziming
2015-01-01
Objective: The treatment of comminuted radial head fractures is still challenging. A radial head replacement is more effective in comminuted radial head fractures. The aim of this paper was to present the medium-term results of the Acumed anatomic radial head system (AARHS). Methods: This study was performed on 12 patients with traumatic elbow fracture and instability between 2008 and 2011 of whom 12 were reviewed at a mean follow-up of 60.8 months (19 to 77 months). The evaluation included a record of pain, function, muscle strength, contracture and rotation. The outcome was assessed using the Hospital for Special Surgery total elbow scoring and a modified Disability of Arm Shoulder Hand (DASH) questionnaire. Results: The average flexion and extension arc was 130° (range, 110° to 140°). The mean range of elbow supination was 75° (rang, 60° to 85°) and pronation 80° (range, 65° to 90°). There were no complications such as infection, implant loosening, instability of the elbow, cubitus valgus, osteoporosis of the capitellum, or pain in the forearm and wrist. The mean DASH score was 11.9/100 (0 to 25/100). Conclusion: The radial head replacement with the AARHS can provide effectively stability and good clinic results at the middle term following up. Our experience has encouraged us to continue using the AARHS in comminuted fractures, especially when instability of elbow is a potential problem. PMID:26131250
DSNF AND OTHER WASTE FORM DEGRADATION ABSTRACTION
J. CUNNANE
2004-11-19
Several hundred distinct types of DOE-owned spent nuclear fuel (DSNF) may potentially be disposed in the Yucca Mountain repository. These fuel types represent many more types than can be viably individually examined for their effect on the Total System Performance Assessment for the License Application (TSPA-LA). Additionally, for most of these fuel types, there is no known direct experimental test data for the degradation and dissolution of the waste form in repository groundwaters. The approach used in the TSPA-LA model is, therefore, to assess available information on each of 11 groups of DSNF, and to identify a model that can be used in the TSPA-LA model without differentiating between individual codisposal waste packages containing different DSNF types. The purpose of this report is to examine the available data and information concerning the dissolution kinetics of DSNF matrices for the purpose of abstracting a degradation model suitable for use in describing degradation of the DSNF inventory in the Total System Performance Assessment for the License Application. The data and information and associated degradation models were examined for the following types of DSNF: Group 1--Naval spent nuclear fuel; Group 2--Plutonium/uranium alloy (Fermi 1 SNF); Group 3--Plutonium/uranium carbide (Fast Flux Test Facility-Test Fuel Assembly SNF); Group 4--Mixed oxide and plutonium oxide (Fast Flux Test Facility-Demonstration Fuel Assembly/Fast Flux Test Facility-Test Demonstration Fuel Assembly SNF); Group 5--Thorium/uranium carbide (Fort St. Vrain SNF); Group 6--Thorium/uranium oxide (Shippingport light water breeder reactor SNF); Group 7--Uranium metal (N Reactor SNF); Group 8--Uranium oxide (Three Mile Island-2 core debris); Group 9--Aluminum-based SNF (Foreign Research Reactor SNF); Group 10--Miscellaneous Fuel; and Group 11--Uranium-zirconium hydride (Training Research Isotopes-General Atomics SNF). The analyses contained in this document provide an ''upper-limit'' (i
Neuromechanical Basis of Kinesiology.
ERIC Educational Resources Information Center
Enoka, Roger M.
This textbook provides a scientific basis for the study of human motion. The eight chapters are organized under three major sections. Part One--The Force-Motion Relationship--contains chapters on (1) motion; (2) force; (3) types of movement analysis. In Part Two--The Simple Joint System--chapters concern (4) simple joint system components; (5)…
Abstracted publications related to the Hanford environment, 1980 to 1988
Becker, C.D.; Gray, R.H.
1989-05-01
This abstracted bibliography provides a reference to the diverse environmental activities conducted on the Hanford Site from 1980 through 1988. It includes 500 reports and articles that were prepared largely by onsite contractors and the Department of Energy. Documents contained here were separated into eight subject areas: air and atmosphere, aquatic ecology, effluents and wastes, geology and hydrology, Hanford Site, radioactivity, terrestrial ecology, and socioeconomics. These areas form the basis of a key word index, which is intended to help the reader locate subjects of interest. An author index is also included.