WorldWideScience
 
 
1

Infinite-dimensional multilayer perceptrons.  

Science.gov (United States)

In this paper a new multilayer perceptron (MLP) structure is introduced to simulate nonlinear transformations on infinite-dimensional function spaces. This extension is achieved by replacing discrete neurons by a continuum of neurons, summations by integrations and weight matrices by kernels of integral transforms. Variational techniques have been employed for the analysis and training of the infinite-dimensional MLP (IDMLP). The training problem of IDMLP is solved by the Lagrange multiplier technique yielding the coupled state and adjoint state integro-difference equations. A steepest descent-like algorithm is used to construct the required kernel and threshold functions. Finally, some results are presented to show the performance of the new IDMLP. PMID:18263484

Kuzuoglu, M; Leblebicioglu, K

1996-01-01

2

Multi-Layer Perceptrons and Symbolic Data  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multilayer Perceptrons are one of the most successful non-linear regression tool but they are unfortunately restricted to inputs and outputs that belong to a normed vector space. In this chapter, we propose a general recoding method that allows to use symbolic data both as inputs and outputs to Multilayer Perceptrons. The r...

Rossi, Fabrice; Conan-guez, Brieuc

2008-01-01

3

Auto-kernel using multilayer perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This work presents a constructive method to train the multilayer perceptron layer after layer successively and to accomplish the kernel used in the support vector machine. Data in different classes will be trained to map to distant points in each layer. This will ease the mapping of the next layer. A perfect mapping kernel can be accomplished successively. Those distant mapped points can be discriminated easily by a single perceptron.

Wei-Chen Cheng

2012-01-01

4

Multi-Layer Perceptrons and Symbolic Data  

CERN Document Server

In some real world situations, linear models are not sufficient to represent accurately complex relations between input variables and output variables of a studied system. Multilayer Perceptrons are one of the most successful non-linear regression tool but they are unfortunately restricted to inputs and outputs that belong to a normed vector space. In this chapter, we propose a general recoding method that allows to use symbolic data both as inputs and outputs to Multilayer Perceptrons. The recoding is quite simple to implement and yet provides a flexible framework that allows to deal with almost all practical cases. The proposed method is illustrated on a real world data set.

Rossi, Fabrice

2008-01-01

5

Hierarchical Multilayer Perceptron based Language Identification  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Automatic language identification (LID) systems generally exploit acoustic knowledge, possibly enriched by explicit language specific phonotactic or lexical constraints. This paper investigates a new LID approach based on hierarchical multilayer perceptron (MLP) classifiers, where the first layer is a "universal phoneme set MLP classifier''. The resulting (multilingual) phoneme posterior sequence is fed into a second MLP taking a larger temporal context into account. The second MLP can learn/...

Imseng, David; Magimai -doss, Mathew; Bourlard, Herve?

2010-01-01

6

Quaternionic Multilayer Perceptron with Local Analyticity  

Digital Repository Infrastructure Vision for European Research (DRIVER)

A multi-layered perceptron type neural network is presented and analyzed in this paper. All neuronal parameters such as input, output, action potential and connection weight are encoded by quaternions, which are a class of hypercomplex number system. Local analytic condition is imposed on the activation function in updating neurons’ states in order to construct learning algorithm for this network. An error back-propagation algorithm is introduced for modifying the connection weights of ...

Teijiro Isokawa; Haruhiko Nishimura; Nobuyuki Matsui

2012-01-01

7

Hierarchical Multilayer Perceptron based Language Identification  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Automatic language identification (LID) systems generally exploit acoustic knowledge, possibly enriched by explicit language specific phonotactic or lexical constraints. This paper investigates a new LID approach based on hierarchical multilayer perceptron (MLP) classifiers, where the first layer is a ``universal phoneme set MLP classifier''. The resulting (multilingual) phoneme posterior sequence is fed into a second MLP taking a larger temporal context into account. The second MLP can learn...

Imseng, David; Magimai -doss, Mathew; Bourlard, Herve?

2010-01-01

8

Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The paper introduces a new objective method for speech quality assessment called Fourier-lapped multilayer perceptron (FLMLP). This method uses an overcomplete transform based on the discrete Fourier transform (DFT) and modulated lapped transform (MLT). This transform generates the DFT and the MLT speech spectral domains from which several relevant perceptual parameters are extracted. The proposed method also employs a multilayer perceptron neural network trained by a modified version of the ...

Vidal Ribeiro, Mois S.; Jayme Garcia Arnal Barbedo; Marcos Travassos Romano, Jo O.; Amauri Lopes

2005-01-01

9

Efficient Estimation of Multidimensional Regression Model with Multilayer Perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This work concerns estimation of multidimensional nonlinear regression models using multilayer perceptron (MLP). The main problem with such model is that we have to know the covariance matrix of the noise to get optimal estimator. however we show that, if we choose as cost function the logarithm of the determinant of the empirical error covariance matrix, we get an asymptotically optimal estimator.

Rynkiewicz, Joseph

2008-01-01

10

Efficient Estimation of Multidimensional Regression Model with Multilayer Perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This work concerns estimation of multidimensional nonlinear regression models using multilayer perceptron (MLP). The main problem with such model is that we have to know the covariance matrix of the noise to get optimal estimator. however we show that, if we choose as cost function the logarithm of the determinant of the empirical error covariance matrix, we get an asymptotically optimal estimator.

Rynkiewicz, Joseph

2005-01-01

11

Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics  

International Nuclear Information System (INIS)

Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control applications in complex technologies such as those employed in the nuclear industry. In this paper, the nonlinear modeling capabilities of an infinite impulse response multilayer perceptron (IIR-MLP) for nuclear dynamics are considered in comparison to static modeling by a finite impulse response multilayer perceptron (FIR-MLP) and a conventional static MLP. The comparison is made with respect to the nonlinear dynamics of a nuclear reactor as investigated by IIR-MLP in a previous paper. The superior performance of the locally recurrent scheme is demonstrated

2007-01-01

12

A Parallel Framework for Multilayer Perceptron for Human Face Recognition  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Artificial neural networks have already shown their success in face recognition and similar complex pattern recognition tasks. However, a major disadvantage of the technique is that it is extremely slow during training for larger classes and hence not suitable for real-time complex problems such as pattern recognition. This is an attempt to develop a parallel framework for the training algorithm of a perceptron. In this paper, two general architectures for a Multilayer Perce...

Bhowmik, M. K.; Bhattacharjee, Debotosh; Nasipuri, M.; Basu, D. K.; Kundu, M.

2010-01-01

13

Accurate Dependency Parsing with a Stacked Multilayer Perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

DeSR is a statistical transition-based dependency parser which learns from annotated corpora which actions to perform for building parse trees while scanning a sentence. We describe recent improvements to the parser, in particular stacked parsing, exploiting a beam search strategy and using a Multilayer Perceptron classifier. For the Evalita 2009 Dependency Parsing task DesR was configured to use a combination of stacked parsers. The stacked combination achieved the best accuracy scores in bo...

Attardi, Giuseppe; Orletta, Felice; Simi, Maria; Turian, Joseph

2009-01-01

14

Classification of Log-Polar-Visual Eigenfaces using Multilayer Perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In this paper we present a simple novel approach to tackle the challenges of scaling and rotation of face images in face recognition. The proposed approach registers the training and testing visual face images by log-polar transformation, which is capable to handle complicacies introduced by scaling and rotation. Log-polar images are projected into eigenspace and finally classified using an improved multi-layer perceptron. In the experiments we have used ORL face database an...

Bhowmik, Mrinal Kanti; Bhattacharjee, Debotosh; Nasipuri, Mita; Kundu, Mahantapas; Basu, Dipak Kumar

2010-01-01

15

Prediction of Parametric Roll Resonance by Multilayer Perceptron Neural Network  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Parametric roll resonance is a ship stability related phenomenon that generates sudden large amplitude oscillations up to 30-40 degrees of roll. This can cause severe damage, and it can put the crew in serious danger. The need for a parametric rolling real time prediction system has been acknowledged in the last few years. This work proposes a prediction system based on a multilayer perceptron (MP) neural network. The training and testing of the MP network is accomplished ...

Mi?guez Gonza?lez, M.; Lo?pez Pen?a, F.; Di?az Casa?s, V.; Galeazzi, Roberto; Blanke, Mogens

2011-01-01

16

Asymptotic law of likelihood ratio for multilayer perceptron models  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The data are assumed to be generated by a true MLP model and the estimation of the parameters of the MLP is done by maximizing the likelihood of the model. When the number of hidden units of the true model is known, the asymptotic distribution of the maximum likelihood estimator (MLE) and the likelihood ratio (LR) statistic is easy to compute and converge to a $\\c...

Rynkiewicz, Joseph

2010-01-01

17

Consistent estimation of the architecture of multilayer perceptrons  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The estimation of the parameters of the MLP can be done by maximizing the likelihood of the model. In this framework, it is difficult to determine the true number of hidden units using an information criterion, like the Bayesian information criteria (BIC), because the information matrix of Fisher is not invertible if the number of hidden units is overestimated. In...

Rynkiewicz, Joseph

2008-01-01

18

Efficient Estimation of Multidimensional Regression Model using Multilayer Perceptrons  

CERN Document Server

This work concerns the estimation of multidimensional nonlinear regression models using multilayer perceptrons (MLPs). The main problem with such models is that we need to know the covariance matrix of the noise to get an optimal estimator. However, we show in this paper that if we choose as the cost function the logarithm of the determinant of the empirical error covariance matrix, then we get an asymptotically optimal estimator. Moreover, under suitable assumptions, we show that this cost function leads to a very simple asymptotic law for testing the number of parameters of an identifiable MLP. Numerical experiments confirm the theoretical results.

Rynkiewicz, Joseph

2008-01-01

19

Asymptotic law of likelihood ratio for multilayer perceptron models.  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The data are assumed to be generated by a true MLP model and the estimation of the parameters of the MLP is done by maximizing the likelihood of the model. When the number of hidden units of the true model is known, the asymptotic distribution of the maximum likelihood estimator (MLE) and the likelihood ratio (LR) statistic is easy to compute and converge to a $\\chi^2$ law. However...

Rynkiewicz, Joseph

2010-01-01

20

Error correcting code using tree-like multilayer perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

An error correcting code using a tree-like multilayer perceptron is proposed. An original message $\\mbi{s}^0$ is encoded into a codeword $\\boldmath{y}_0$ using a tree-like committee machine (committee tree) or a tree-like parity machine (parity tree). Based on these architectures, several schemes featuring monotonic or non-monotonic units are introduced. The codeword $\\mbi{y}_0$ is then transmitted via a Binary Asymmetric Channel (BAC) where it is corrupted by noise. The ana...

Cousseau, Florent; Mimura, Kazushi; Okada, Masato

2008-01-01

 
 
 
 
21

A Choice of Input Variables for a Multilayer Perceptron  

International Nuclear Information System (INIS)

In the paper some aspects of multilayer perceptron (MLP) application to the problem of classifying the events presented by empirical samples of a finite volume are considered. The results of the MLP learning for various forms of the input data are analyzed and the reasons leading to the effect of an instantaneous learning of the MLP and rise of the neural network are investigated for the case when the input data are presented in a form of variational series. The problem of hidden layer neuron reduction without raising the recognition error is discussed. (author). 13 refs., 6 figs., 1 tab

1994-01-01

22

Key Generation and Certification using Multilayer Perceptron in Wireless communication(KGCMLP)  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In this paper, a key generation and certification technique using multilayer perceptron (KGCMLP) has been proposed in wireless communication of data/information. In this proposed KGCMLP technique both sender and receiver uses an identical multilayer perceptrons. Both perceptrons are start synchronization by exchanging some control frames. During synchronization process message integrity test and synchronization test has been carried out. Only the synchronization test does no...

Sarkar, Arindam; Mandal, J. K.

2012-01-01

23

Fast parallel off-line training of multilayer perceptrons.  

Science.gov (United States)

Various approaches to the parallel implementation of second-order gradient-based multilayer perceptron training algorithms are described. Two main classes of algorithm are defined involving Hessian and conjugate gradient-based methods. The limited- and full-memory Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithms are selected as representative examples and used to show that the step size and gradient calculations are critical components. For larger problems the matrix calculations in the full-memory algorithm are also significant. Various strategies are considered for parallelization, the best of which is implemented on parallel virtual machine (PVM) and transputer-based architectures. Results from a range of problems are used to demonstrate the performance achievable with each architecture. The transputer implementation is found to give excellent speed-ups but the problem size is limited by memory constraints. The speed-ups achievable with the PVM implementation are much poorer because of inefficient communication, but memory is not a difficulty. PMID:18255667

McLoone, S; Irwin, G W

1997-01-01

24

Consistent estimation of the architecture of multilayer perceptrons  

CERN Multimedia

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The estimation of the parameters of the MLP can be done by maximizing the likelihood of the model. In this framework, it is difficult to determine the true number of hidden units using an information criterion, like the Bayesian information criteria (BIC), because the information matrix of Fisher is not invertible if the number of hidden units is overestimated. Indeed, the classical theoretical justification of information criteria relies entirely on the invertibility of this matrix. However, using recent methodology introduced to deal with models with a loss of identifiability, we prove that suitable information criterion leads to consistent estimation of the true number of hidden units.

Rynkiewicz, Joseph

2008-01-01

25

Optical proximity correction using a multilayer perceptron neural network  

Science.gov (United States)

Optical proximity correction (OPC) is one of the resolution enhancement techniques (RETs) in optical lithography, where the mask pattern is modified to improve the output pattern fidelity. Algorithms are needed to generate the modified mask pattern automatically and efficiently. In this paper, a multilayer perceptron (MLP) neural network (NN) is used to synthesize the mask pattern. We employ the pixel-based approach in this work. The MLP takes the pixel values of the desired output wafer pattern as input, and outputs the optimal mask pixel values. The MLP is trained with the backpropagation algorithm, with a training set retrieved from the desired output pattern, and the optimal mask pattern obtained by the model-based method. After training, the MLP is able to generate the optimal mask pattern non-iteratively with good pattern fidelity.

Luo, Rui

2013-07-01

26

Ground Radar Target Classification Using Singular Value Decomposition and Multilayer Perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The paper deals with classification of ground radar targets. Areceived radar signal backscattered from a ground radar target wasdigitized and in the form of radar signal matrix utilized for a featureextraction based on Singular Value Decomposition. Furthermore, singularvalues of a backscattered radar signal matrix, as a target feature,were utilized for Radar Target Classification by multilayer perceptron.In the learning phase of a multilayer perceptron we used the learningtarget set and in th...

Matousek, Z.; Kurty, J.; Mokris, I.

2001-01-01

27

Multilayer Perceptron Guided Key Generation Through Mutation with Recursive Replacement in Wireless Communication (MLPKG)  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In this paper, a multilayer perceptron guided key generation for encryption/decryption (MLPKG) has been proposed through recursive replacement using mutated character code generation for wireless communication of data/information. Multilayer perceptron transmitting systems at both ends accept an identical input vector, generate an output bit and the network are trained based on the output bit which is used to form a protected variable length secret-key. For each session, dif...

Sarkar, Arindam; Mandal, J. K.

2012-01-01

28

Classification of Log-Polar-Visual Eigenfaces using Multilayer Perceptron  

CERN Multimedia

In this paper we present a simple novel approach to tackle the challenges of scaling and rotation of face images in face recognition. The proposed approach registers the training and testing visual face images by log-polar transformation, which is capable to handle complicacies introduced by scaling and rotation. Log-polar images are projected into eigenspace and finally classified using an improved multi-layer perceptron. In the experiments we have used ORL face database and Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database for visual face images. Experimental results show that the proposed approach significantly improves the recognition performances from visual to log-polar-visual face images. In case of ORL face database, recognition rate for visual face images is 89.5% and that is increased to 97.5% for log-polar-visual face images whereas for OTCBVS face database recognition rate for visual images is 87.84% and 96.36% for log-polar-visual face images.

Bhowmik, Mrinal Kanti; Nasipuri, Mita; Kundu, Mahantapas; Basu, Dipak Kumar

2010-01-01

29

Asymptotic law of likelihood ratio for multilayer perceptron models  

CERN Document Server

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The data are assumed to be generated by a true MLP model and the estimation of the parameters of the MLP is done by maximizing the likelihood of the model. When the number of hidden units of the true model is known, the asymptotic distribution of the maximum likelihood estimator (MLE) and the likelihood ratio (LR) statistic is easy to compute and converge to a $\\chi^2$ law. However, if the number of hidden unit is over-estimated the Fischer information matrix of the model is singular and the asymptotic behavior of the MLE is unknown. This paper deals with this case, and gives the exact asymptotic law of the LR statistics. Namely, if the parameters of the MLP lie in a suitable compact set, we show that the LR statistics is the supremum of the square of a Gaussian process indexed by a class of limit score functions.

Rynkiewicz, Joseph

2010-01-01

30

Ground Radar Target Classification Using Singular Value Decomposition and Multilayer Perceptron  

Directory of Open Access Journals (Sweden)

Full Text Available The paper deals with classification of ground radar targets. Areceived radar signal backscattered from a ground radar target wasdigitized and in the form of radar signal matrix utilized for a featureextraction based on Singular Value Decomposition. Furthermore, singularvalues of a backscattered radar signal matrix, as a target feature,were utilized for Radar Target Classification by multilayer perceptron.In the learning phase of a multilayer perceptron we used the learningtarget set and in the testing phase the testing target set was used.The learning and testing target sets were created on the basis of realground radar targets.

I. Mokris

2001-12-01

31

Design of Near-Optimal Classifier Using Multi-Layer Perceptron Neural Networks for Intelligent Sensors  

Directory of Open Access Journals (Sweden)

Full Text Available The Multi-layer Perceptron Neural Networks (MLP NN are well known for their simplicity, ease of training for small-scale problems, and suitability for online implementation. This paper presents the methodology and challenges in the design of near-optimal MLP NN based classifier with maximize classification accuracy under the constraints of minimum network dimension for implementation intelligent sensors.

Nadir N. Charniya

2013-02-01

32

Empirical model development and validation with dynamic learning in the recurrent multilayer perception  

International Nuclear Information System (INIS)

A nonlinear multivariable empirical model is developed for a U-tube steam generator using the recurrent multilayer perceptron network as the underlying model structure. The recurrent multilayer perceptron is a dynamic neural network, very effective in the input-output modeling of complex process systems. A dynamic gradient descent learning algorithm is used to train the recurrent multilayer perceptron, resulting in an order of magnitude improvement in convergence speed over static learning algorithms. In developing the U-tube steam generator empirical model, the effects of actuator, process,and sensor noise on the training and testing sets are investigated. Learning and prediction both appear very effective, despite the presence of training and testing set noise, respectively. The recurrent multilayer perceptron appears to learn the deterministic part of a stochastic training set, and it predicts approximately a moving average response. Extensive model validation studies indicate that the empirical model can substantially generalize (extrapolate), though online learning becomes necessary for tracking transients significantly different than the ones included in the training set and slowly varying U-tube steam generator dynamics. In view of the satisfactory modeling accuracy and the associated short development time, neural networks based empirical models in some cases appear to provide a serious alternative to first principles models. Caution, however, must be exercised because extensive on-line validation of these models is still warranted

1994-02-01

33

Evaluation of multilayer perceptron and self-organizing map neural network topologies applied on microstructure segmentation from metallographic images  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Artificial neuronal networks have been used intensively in many domains to accomplish different computational tasks. One of these tasks is the segmentation of objects in images, like to segment microstructures from metallographic images, and for that goal several network topologies were proposed. This paper presents a comparative analysis between multilayer perceptron and selforganizing map topologies applied to segment microstructures from metallographic images. The multilayer perceptron neu...

Albuquerque, Victor Hugo C.; Auzuir Ripardo de Alexandria; Paulo César Cortez; Tavares, Joa?o Manuel R. S.

2009-01-01

34

Improvement of the multilayer perceptron for air quality modelling through an adaptive learning scheme  

Science.gov (United States)

Multilayer perceptron (MLP), normally trained by the offline backpropagation algorithm, could not adapt to the changing air quality system and subsequently underperforms. To improve this, the extended Kalman filter is adopted into the learning algorithm to build a time-varying multilayer perceptron (TVMLP) in this study. Application of the TVMLP to model the daily averaged concentration of the respirable suspended particulates with aerodynamic diameter of not more than 10 µm (PM10) in Macau shows statistically significant improvement on the performance indicators over the MLP counterpart. In addition, the adaptive learning algorithm could also address explicitly the uncertainty of the prediction so that confidence intervals can be provided. More importantly, the adaptiveness of the TVMLP gives prediction improvement on the region of higher particulate concentrations that the public concerns.

Hoi, K. I.; Yuen, K. V.; Mok, K. M.

2013-09-01

35

Estimating the Number of Components in a Mixture of Multilayer Perceptrons  

CERN Document Server

BIC criterion is widely used by the neural-network community for model selection tasks, although its convergence properties are not always theoretically established. In this paper we will focus on estimating the number of components in a mixture of multilayer perceptrons and proving the convergence of the BIC criterion in this frame. The penalized marginal-likelihood for mixture models and hidden Markov models introduced by Keribin (2000) and, respectively, Gassiat (2002) is extended to mixtures of multilayer perceptrons for which a penalized-likelihood criterion is proposed. We prove its convergence under some hypothesis which involve essentially the bracketing entropy of the generalized score-functions class and illustrate it by some numerical examples.

Olteanu, Madalina

2008-01-01

36

Direct optimisation of a multilayer perceptron for the estimation of cepstral mean and variance statistics  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We propose an alternative means of training a multilayer perceptron for the task of speech activity detection based on a criterion to minimise the error in the estimation of mean and variance statistics for speech cepstrum based features using the Kullback-Leibler divergence. We present our baseline and proposed speech activity detection approaches for multi-channel meeting room recordings and demonstrate the effectiveness of the new criterion by comparing the two approaches when used to carr...

Dines, John; Vepa, Jithendra

2007-01-01

37

Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. Their use is becoming increasingly popular in the complex modeling tasks required by diagnostic, safety, and control applications in complex technologies such as those employed in the nuclear industry. In this paper, the nonlinear modeling capabilities of an infinite impulse response multilayer perceptron (IIR-MLP) for nuclear dynamics are considered in comparison to static mo...

Cadini, F.; Zio, E.; Pedroni, N.

2008-01-01

38

Understanding Dropout: Training Multi-Layer Perceptrons with Auxiliary Independent Stochastic Neurons  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In this paper, a simple, general method of adding auxiliary stochastic neurons to a multi-layer perceptron is proposed. It is shown that the proposed method is a generalization of recently successful methods of dropout (Hinton et al., 2012), explicit noise injection (Vincent et al., 2010; Bishop, 1995) and semantic hashing (Salakhutdinov & Hinton, 2009). Under the proposed framework, an extension of dropout which allows using separate dropping probabilities for different hid...

Cho, Kyunghyun

2013-01-01

39

Photometric redshifts with the Multilayer Perceptron Neural Network: application to the HDF-S and SDSS  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We present a technique for the estimation of photometric redshifts based on feed-forward neural networks. The Multilayer Perceptron (MLP) Artificial Neural Network is used to predict photometric redshifts in the HDF-S from an ultra deep multicolor catalog. Various possible approaches for the training of the neural network are explored, including the deepest and most complete spectroscopic redshift catalog currently available (the Hubble Deep Field North dataset) and models o...

Vanzella, E.; Cristiani, S.; Fontana, A.; Nonino, M.; Arnouts, S.; Giallongo, E.; Grazian, A.; Fasano, G.; Popesso, P.; Saracco, P.; Zaggia, S.

2003-01-01

40

Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This paper is an improved version of \\cit in which we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional MLP. We obtain universal approximation results that show the expressive power of functional MLP is comparable to that of numerical MLP. We obtain consistency results which imply that the estimation of optimal parameters for functional MLP is statistically well defined. We finally ...

Rossi, Fabrice; Conan-guez, Brieuc

2004-01-01

 
 
 
 
41

Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In this paper, we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional MLP. We obtain universal approximation results that show the expressive power of functional MLP is comparable to that of numerical MLP. We obtain consistency results which imply that the estimation of optimal parameters for functional MLP is statistically well defined. We finally show on simulated ...

Rossi, Fabrice; Conan-guez, Brieuc

2007-01-01

42

Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The sonar images provide a rapid view of the seabed in order to characterize it. However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict. In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms. The classification is conducted by a multilayer perceptron, taking into account the uncertainty of...

Martin, Arnaud; Osswald, Christophe

2008-01-01

43

A New Approach to Predicting Bankruptcy: Combining DEA and Multi-Layer Perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The question of financial health and sustenance of a firm is so intriguing that it has spanned numerous studies. For investors,stakeholders and lenders, assessing the risk associated with an enterprise is vital. Several tools have been formulated to deal with predicting the solvency of a firm. This paper attempts to combine Data Envelopment Analysis and Multi-Layer Perceptron (MLP) to suggest a new method for prediction of bankruptcy that not only focusses on historical financial data of firm...

Ayan Mukhopadhyay; Suman Tiwari; Ankit Narsaria; Bhaskar Roy Karmaker

2012-01-01

44

Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The sonar images provide a rapid view of the seabed in order to characterize it. However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict. In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms. The classification is conducted by a multilayer perceptron, taking into account ...

Martin, Arnaud; Osswald, Christophe

2008-01-01

45

Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In this paper, we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional MLP. We obtain universal approximation results that show the expressive power of functional MLP is comparable to that of numerical MLP. We obtain consistency results which imply that the estimation of optimal parameters for functional MLP is statistically well defined. We finally show on simulated and real world dat...

Rossi, Fabrice; Conan-guez, Brieuc

2005-01-01

46

Estimating the Number of Components in a Mixture of Multilayer Perceptrons  

Digital Repository Infrastructure Vision for European Research (DRIVER)

BIC criterion is widely used by the neural-network community for model selection tasks, although its convergence properties are not always theoretically established. In this paper we will focus on estimating the number of components in a mixture of multilayer perceptrons and proving the convergence of the BIC criterion in this frame. The penalized marginal-likelihood for mixture models and hidden Markov models introduced by Keribin (2000) and, respectively, Gassiat (2002) is...

Olteanu, Madalina; Rynkiewicz, Joseph

2008-01-01

47

A multilayer perceptron solution to the match phase problem in rule-based artificial intelligence systems  

Science.gov (United States)

In rule-based AI planning, expert, and learning systems, it is often the case that the left-hand-sides of the rules must be repeatedly compared to the contents of some 'working memory'. The traditional approach to solve such a 'match phase problem' for production systems is to use the Rete Match Algorithm. Here, a new technique using a multilayer perceptron, a particular artificial neural network model, is presented to solve the match phase problem for rule-based AI systems. A syntax for premise formulas (i.e., the left-hand-sides of the rules) is defined, and working memory is specified. From this, it is shown how to construct a multilayer perceptron that finds all of the rules which can be executed for the current situation in working memory. The complexity of the constructed multilayer perceptron is derived in terms of the maximum number of nodes and the required number of layers. A method for reducing the number of layers to at most three is also presented.

Sartori, Michael A.; Passino, Kevin M.; Antsaklis, Panos J.

1992-01-01

48

Second-Order Learning Methods for a Multilayer Perceptron  

International Nuclear Information System (INIS)

First- and second-order learning methods for feed-forward multilayer neural networks are studied. Newton-type and quasi-Newton algorithms are considered and compared with commonly used back-propagation algorithm. It is shown that, although second-order algorithms require enhanced computer facilities, they provide better convergence and simplicity in usage. 13 refs., 2 figs., 2 tabs

1994-01-01

49

An Analog Multilayer Perceptron Neural Network for a Portable Electronic Nose  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This study examines an analog circuit comprising a multilayer perceptron neural network (MLPNN). This study proposes a low-power and small-area analog MLP circuit to implement in an E-nose as a classifier, such that the E-nose would be relatively small, power-efficient, and portable. The analog MLP circuit had only four input neurons, four hidden neurons, and one output neuron. The circuit was designed and fabricated using a 0.18 ?m standard CMOS process with a 1.8 V supply. The power consum...

Pan, Chih-heng; Hsieh, Hung-yi; Tang, Kea-tiong

2013-01-01

50

An Analog Multilayer Perceptron Neural Network for a Portable Electronic Nose  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This study examines an analog circuit comprising a multilayer perceptron neural network (MLPNN). This study proposes a low-power and small-area analog MLP circuit to implement in an E-nose as a classifier, such that the E-nose would be relatively small, power-efficient, and portable. The analog MLP circuit had only four input neurons, four hidden neurons, and one output neuron. The circuit was designed and fabricated using a 0.18 ?m standard CMOS process with a 1.8 V supply. The power co...

Chih-Heng Pan; Hung-Yi Hsieh; Kea-Tiong Tang

2012-01-01

51

Multilayered perceptron neural networks to compute energy losses in magnetic cores  

International Nuclear Information System (INIS)

This paper presents a new approach based on multilayered perceptrons (MLPs) to compute the specific energy losses of toroidal wound cores built from 3% SiFe 0.27 mm thick M4, 0.1 and 0.08 mm thin gauge electrical steel strips. The MLP has been trained by a back-propagation and extended delta-bar-delta learning algorithm. The results obtained by using the MLP model were compared with a commonly used conventional method. The comparison has shown that the proposed model improved loss estimation with respect to the conventional method

2006-12-01

52

Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis  

CERN Document Server

In this paper, we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional MLP. We obtain universal approximation results that show the expressive power of functional MLP is comparable to that of numerical MLP. We obtain consistency results which imply that the estimation of optimal parameters for functional MLP is statistically well defined. We finally show on simulated and real world data that the proposed model performs in a very satisfactory way.

Rossi, Fabrice

2005-01-01

53

Geomagnetic storms prediction from InterMagnetic Observatories data using the Multilayer Perceptron neural network  

Science.gov (United States)

In this paper, a tentative of geomagnetic storms prediction is implanted by analyzing the International Real-Time Magnetic Observatory Network data using the Artificial Neural Network (ANN). The implanted method is based on the prediction of future horizontal geomagnetic field component using a Multilayer Perceptron (MLP) neural network model. The input is the time and the output is the X and Y magnetic field components. Application to geomagnetic data of Mai 2002 shows that the implanted ANN model can greatly help the geomagnetic storms prediction.

Ouadfeul, S.; Aliouane, L.; Tourtchine, V.

2013-09-01

54

Highly Accurate Multi-layer Perceptron Neural Network for Air Data System  

Directory of Open Access Journals (Sweden)

Full Text Available The error backpropagation multi-layer perceptron algorithm is revisited. This algorithm is used to train and validate two models of three-layer neural networks that can be used to calibrate a 5-hole pressure probe. This paper addresses Occam.s Razor problem as it describes the adhoc training methodology applied to improve accuracy and sensitivity. The trained outputs from 5-4-3 feed-forward network architecture with jump connection are comparable to second decimal digit (~0.05 accuracy, hitherto unreported in literature.

H.S. Krishna

2009-11-01

55

Experts Fusion and Multilayer Perceptron Based on Belief Learning for Sonar Image Classification  

CERN Multimedia

The sonar images provide a rapid view of the seabed in order to characterize it. However, in such as uncertain environment, real seabed is unknown and the only information we can obtain, is the interpretation of different human experts, sometimes in conflict. In this paper, we propose to manage this conflict in order to provide a robust reality for the learning step of classification algorithms. The classification is conducted by a multilayer perceptron, taking into account the uncertainty of the reality in the learning stage. The results of this seabed characterization are presented on real sonar images.

Martin, Arnaud

2008-01-01

56

Apply Multi-Layer Perceptrons Neural Network for Off-Line Signature Verification and Recognition  

Directory of Open Access Journals (Sweden)

Full Text Available This paper discusses the applying of Multi-layer perceptrons for signature verification and recognition using a new approach enables the user to recognize whether a signature is original or a fraud. The approach starts by scanning images into the computer, then modifying their quality through image enhancement and noise reduction, followed by feature extraction and neural network training, and finally verifies the authenticity of the signature. The paper discusses the different stages of the process including: image pre-processing, feature extraction and pattern recognition through neural networks.

Suhail Odeh

2011-11-01

57

Generation of hourly irradiation synthetic series using the neural network multilayer perceptron  

Energy Technology Data Exchange (ETDEWEB)

In this work, a methodology based on the neural network model called multilayer perceptron (MLP) to solve a typical problem in solar energy is presented. This methodology consists of the generation of synthetic series of hourly solar irradiation. The model presented is based on the capacity of the MLP for finding relations between variables for which interrelation is unknown explicitly. The information available can be included progressively at the series generator at different stages. A comparative study with other solar irradiation synthetic generation methods has been done in order to demonstrate the validity of the one proposed. (author)

Hontoria, L.; Aguilera, J. [Universidad de Jaen, Linares-Jaen (Spain). Dpto. de Electronica; Zufiria, P. [Ciudad Universitaria, Madrid (Spain). Grupo de Redes Neuronales

2002-05-01

58

Missing value imputation on missing completely at random data using multilayer perceptrons.  

Science.gov (United States)

Data mining is based on data files which usually contain errors in the form of missing values. This paper focuses on a methodological framework for the development of an automated data imputation model based on artificial neural networks. Fifteen real and simulated data sets are exposed to a perturbation experiment, based on the random generation of missing values. These data set sizes range from 47 to 1389 records. A perturbation experiment was performed for each data set where the probability of missing value was set to 0.05. Several architectures and learning algorithms for the multilayer perceptron are tested and compared with three classic imputation procedures: mean/mode imputation, regression and hot-deck. The obtained results, considering different performance measures, not only suggest this approach improves the quality of a database with missing values, but also the best results are clearly obtained using the Multilayer Perceptron model in data sets with categorical variables. Three learning rules (Levenberg-Marquardt, BFGS Quasi-Newton and Conjugate Gradient Fletcher-Reeves Update) and a small number of hidden nodes are recommended. PMID:20875726

Silva-Ramírez, Esther-Lydia; Pino-Mejías, Rafael; López-Coello, Manuel; Cubiles-de-la-Vega, María-Dolores

2011-01-01

59

Approximating Gaussian mixture model or radial basis function network with multilayer perceptron.  

Science.gov (United States)

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. PMID:24808530

Patrikar, Ajay M

2013-07-01

60

Classification of Polar-Thermal Eigenfaces using Multilayer Perceptron for Human Face Recognition  

CERN Multimedia

This paper presents a novel approach to handle the challenges of face recognition. In this work thermal face images are considered, which minimizes the affect of illumination changes and occlusion due to moustache, beards, adornments etc. The proposed approach registers the training and testing thermal face images in polar coordinate, which is capable to handle complicacies introduced by scaling and rotation. Polar images are projected into eigenspace and finally classified using a multi-layer perceptron. In the experiments we have used Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database benchmark thermal face images. Experimental results show that the proposed approach significantly improves the verification and identification performance and the success rate is 97.05%.

Bhowmik, Mrinal Kanti; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

2010-01-01

 
 
 
 
61

An Analog Multilayer Perceptron Neural Network for a Portable Electronic Nose  

Directory of Open Access Journals (Sweden)

Full Text Available This study examines an analog circuit comprising a multilayer perceptron neural network (MLPNN. This study proposes a low-power and small-area analog MLP circuit to implement in an E-nose as a classifier, such that the E-nose would be relatively small, power-efficient, and portable. The analog MLP circuit had only four input neurons, four hidden neurons, and one output neuron. The circuit was designed and fabricated using a 0.18 ?m standard CMOS process with a 1.8 V supply. The power consumption was 0.553 mW, and the area was approximately 1.36 × 1.36 mm2. The chip measurements showed that this MLPNN successfully identified the fruit odors of bananas, lemons, and lychees with 91.7% accuracy.

Chih-Heng Pan

2012-12-01

62

Recognition of Epileptiform Patterns in the Human Electroencephalogram Using Multi-Layer Perceptron  

Directory of Open Access Journals (Sweden)

Full Text Available Automatic detection of epileptiform patterns is highly desirable during continuous monitoring of patients with epilepsy. This paper describes an unconvential system for automatic off-line recognition of epileptic sharp transients in the human electroencephalogram (EEG, based on a standard neural network architecture - multi-layer perceptron (MLP, and implemented on a Silicon Graphics Indigo workstation. The system makes comprehensive use of wide spatial contextual information available on 12 channels of EEG and takes advantage of discrete dyadic wavelet transform (DDWT for efficient parameterisation of EEG data. The EEG database consists of 12 patients, 7 of which are used in the process of training of MLP. The resulting MLP is presented with the testing data set consisting of all data vectors from all 12 patients, and is shown to be capable to recognise a wide variety of epileptic signals.

V. Mokran

1995-06-01

63

Image Binarization Using Multi-Layer Perceptron: A Semi-Supervised Approach  

Directory of Open Access Journals (Sweden)

Full Text Available In this paper, we have discussed the Image Binarization technique using Multilayer Perceptron (MLP. The purpose of Image Binarization is to extract the lightness (brightness, density as a feature amount from the Image. It converts a gray-scale image of up to 256 gray levels to a black and white image. We use Backpropagation algorithm for training MLP. It is a supervised learning technique. Here Kmeans clustering algorithm has been used for clustering a 256 × 256 gray-level image. The dataset obtained by this is fed to the MLP and processed in a Semi-Supervised way where some training samples are taken as Known patterns (for training and others as Unknown patterns. Finally through this approach a Binarized image is produced.

Amlan Raychaudhuri

2012-04-01

64

A New Approach to Predicting Bankruptcy: Combining DEA and Multi-Layer Perceptron  

Directory of Open Access Journals (Sweden)

Full Text Available The question of financial health and sustenance of a firm is so intriguing that it has spanned numerous studies. For investors,stakeholders and lenders, assessing the risk associated with an enterprise is vital. Several tools have been formulated to deal with predicting the solvency of a firm. This paper attempts to combine Data Envelopment Analysis and Multi-Layer Perceptron (MLP to suggest a new method for prediction of bankruptcy that not only focusses on historical financial data of firms that filed for bankruptcy like other past studies but also takes into account the data of those firms that were likely to do so. This method thus identifies firms that have a high chance of facing bankruptcy along with those that have filed for bankruptcy. The performance of this procedure is compared with MLP. The suggested method outperforms MLP in prediction of bankruptcy.

Ayan Mukhopadhyay

2012-07-01

65

Exchange rate prediction with multilayer perceptron neural network using gold price as external factor  

Directory of Open Access Journals (Sweden)

Full Text Available In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast accuracy. The five-day delay has been chosen because of the weekly cyclic behavior of the exchange rate time series with the consideration of two holidays in a week. The result of forecasts are then compared with using the multilayer peceptron neural network without gold price external factor by two most important evaluation techniques in the literature of exchange rate prediction. For the experimental analysis phase, the data of three important exchange rates of EUR/USD, GBP/USD, and USD/JPY are used.

Mohammad Fathian

2012-04-01

66

Moisture Content Prediction of Dried Longan Aril from Dielectric Constant Using Multilayer Perceptrons and Support Vector Regression  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Problem statement: Estimation of moisture contents of dried food products from their dielectric constants was an important step in moisture measurement systems. The regression models that provide good prediction performance are desirable. Approach: The Multilayer Perceptrons (MLP) and Support Vector Regression (SVR) were applied in this research to predict the moisture contents of dried longan arils from their dielectric constants. The data set was collected ...

Sanong Amaroek; Nipon Theera-Umpon; Kittichai Wantanajittikul; Sansanee Auephanwiriyakul

2010-01-01

67

Time series modeling with pruned multi-layer perceptron and 2-stage damped least-squares method  

Digital Repository Infrastructure Vision for European Research (DRIVER)

A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its "black box" aspect, many researchers refuse to use it. Moreover, the optimization (often based on the exhaustive approach where "all" configurations are tested) and learning phases of this artificial intelligence tool (often based on the Levenberg-Marquardt algorithm; LMA) are weaknesses of this approach (exhaustively and local minima). These two tasks must b...

Voyant, Cyril; Tamas, Wani; Paoli, Christophe; Balu, Aure?lia; Muselli, Marc; Nivet, Marie Laure; Notton, Gilles

2013-01-01

68

Time series modeling with pruned multi-layer perceptron and 2-stage damped least-squares method  

Digital Repository Infrastructure Vision for European Research (DRIVER)

A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its "black box" aspect, many researchers refuse to use it. Moreover, the optimization (often based on the exhaustive approach where "all" configurations are tested) and learning phases of this artificial intelligence tool (often based on the Levenberg-Marquardt algorithm; LMA) are weaknesses of this approach (exhaustively and local minima). Thes...

Voyant, Cyril; Tamas, Wani W.; Paoli, Christophe; Balu, Aure?lia; Muselli, Marc; Nivet, Marie Laure; Notton, Gilles

2013-01-01

69

Saccadic points classification using Multilayer Perceptron and Randon Forest classifiers in EOG recording of patients with Ataxia SCA2  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In this paper, we compare the performance of two different methods for the task of electrooculogram saccadic points classification in Patients with Ataxia SCA2: Multilayer Perceptrons (MLP) and Random Forest. First we segment the recordings of 6 subjects into ranges of saccadic and non-saccadic points as the basis of supervised learning. Then, we randomly select a set of cases based on the velocity profile near each selected point for training and validation purposes using percent split schem...

Becerra, Roberto; Joya, Gonzalo; Garci?a, Rodolfo; Vela?zque, Luis; Rodri?guez, Roberto; Pino, Carmen

2013-01-01

70

Exploiting Heavy Tails in Training Times of Multilayer Perceptrons: A Case Study with the UCI Thyroid Disease Database  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The random initialization of weights of a multilayer perceptron makes it possible to model its training process as a Las Vegas algorithm, i.e. a randomized algorithm which stops when some required training error is obtained, and whose execution time is a random variable. This modeling is used to perform a case study on a well-known pattern recognition benchmark: the UCI Thyroid Disease Database. Empirical evidence is presented of the training time probability distribution ex...

Cebrian, Manuel; Cantador, Ivan

2007-01-01

71

Evaluation of 1-D tracer concentration profile in a small river by means of Multi-Layer Perceptron Neural Networks  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The prediction of temporal concentration profiles of a transported pollutant in a river is still a subject of ongoing research efforts worldwide. The present paper is aimed at studying the possibility of using Multi-Layer Perceptron Neural Networks to evaluate the whole concentration versus time profile at several cross-sections of a river under various flow conditions, using as little information about the river system as possible. In contrast with the earlier neural networks based work on l...

Piotrowski, A.; Wallis, S. G.; Napio?rkowski, J. J.; Rowin?ski, P. M.

2007-01-01

72

DISCRETE WAVELET TRANSFORM AND S-TRANSFORM BASED TIME SERIES DATA MINING USING MULTILAYER PERCEPTRON NEURAL NETWORK  

Directory of Open Access Journals (Sweden)

Full Text Available This paper presents discrete wavelet transform and the S-transform based neural classifier scheme used for time series data mining of power quality events occurring due to power signal disturbances. The DWT and the S –transform are used for feature extraction and then the extracted features are classified with neural classifiers such as multilayered perceptron network (MLP for pattern classification, data mining and subsequent knowledge discovery.

LALIT KUMAR BEHERA

2011-11-01

73

An application of the multilayer perceptron: Solar radiation maps in Spain  

Energy Technology Data Exchange (ETDEWEB)

In this work an application of a methodology to obtain solar radiation maps is presented. This methodology is based on a neural network system [Lippmann, R.P., 1987. An introduction to computing with neural nets. IEEE ASSP Magazine, 4-22] called Multi-Layer Perceptron (MLP) [Haykin, S., 1994. Neural Networks. A Comprehensive Foundation. Macmillan Publishing Company; Hornik, K., Stinchcombe, M., White, H., 1989. Multilayer feedforward networks are universal approximators. Neural Networks, 2(5), 359-366]. To obtain a solar radiation map it is necessary to know the solar radiation of many points spread wide across the zone of the map where it is going to be drawn. For most of the locations all over the world the records of these data (solar radiation in whatever scale, daily or hourly values) are non-existent. Only very few locations have the privilege of having good meteorological stations where records of solar radiation have being registered. But even in those locations with historical records of solar data, the quality of these solar series is not as good as it should be for most purposes. In addition, to draw solar radiation maps the number of points on the maps (real sites) that it is necessary to work with makes this problem difficult to solve. Nevertheless, with the application of the methodology proposed in this paper, this problem has been solved and solar radiation maps have been obtained for a small region of Spain: Jaen province, a southern province of Spain between parallels 38{sup o}25' N and 37{sup o}25' N, and meridians 4{sup o}10' W and 2{sup o}10' W, and for a larger region: Andalucia, the most southern region of Spain situated between parallels 38{sup o}40' N and 36{sup o}00' N, and meridians 7{sup o}30' W and 1{sup o}40' W. (author)

Hontoria, L.; Aguilera, J. [Grupo Investigacion y Desarrollo en Energia Solar y Automatica, Dpto. de Ingenieria Electronica, de Telecomunicaciones y Automatica, Escuela Politecnica Superior de Jaen, Campus de las Lagunillas, Universidad de Jaen, 23071 Jaen (Spain); Zufiria, P. [Grupo de Redes Neuronales, Dpto. de Matematica Aplicada a las Tecnologias de la Informacion, ETSI Telecomunicaciones, UPM Ciudad Universitaria s/n, 28040 Madrid (Spain)

2005-11-01

74

Estimate of significant wave height from non-coherent marine radar images by multilayer perceptrons  

Science.gov (United States)

One of the most relevant parameters to characterize the severity of ocean waves is the significant wave height ( H s ). The estimate of H s from remotely sensed data acquired by non-coherent X-band marine radars is a problem not completely solved nowadays. A method commonly used in the literature (standard method) uses the square root of the signal-to-noise ratio (SNR) to linearly estimate H s . This method has been widely used during the last decade, but it presents some limitations, especially when swell-dominated sea states are present. To overcome these limitations, a new non-linear method incorporating additional sea state information is proposed in this article. This method is based on artificial neural networks (ANNs), specifically on multilayer perceptrons (MLPs). The information incorporated in the proposed MLP-based method is given by the wave monitoring system (WaMoS II) and concerns not only to the square root of the SNR, as in the standard method, but also to the peak wave length and mean wave period. Results for two different platforms (Ekofisk and FINO 1) placed in different locations of the North Sea are presented to analyze whether the proposed method works regardless of the sea states observed in each location or not. The obtained results empirically demonstrate how the proposed non-linear solution outperforms the standard method regardless of the environmental conditions (platform), maintaining real-time properties.

Vicen-Bueno, Raúl; Lido-Muela, Cristina; Nieto-Borge, José Carlos

2012-12-01

75

Phase transitions in the generalization behaviour of multilayer perceptrons; 2, The influence of noise  

CERN Document Server

We extend our study of phase transitions in the generalization behaviour of multilayer perceptrons with non-overlapping receptive fields to the problem of the influence of noise, concerning e.g. the input units and/or the couplings between the input units and the hidden units of the second layer (='input noise'), or the final output unit (='output noise'). Without output noise, the output itself is given by a general, permutation-invariant Boolean function of the outputs of the hidden units. As a result we find that the phase transitions, which we found in the deterministic case, mostly persist in the presence of noise. The influence of the noise on the position of the phase transition, as well as on the behaviour in other regimes of the loading parameter $\\alpha$, can often be described by a simple rescaling of $\\alpha$ depending on strength and type of the noise. We then consider the problem of the optimal noise level for Gibbsian and Bayesian learning, looking on replica symmetry breaking as well. Finally ...

Schottky, B

1997-01-01

76

Runoff Forecasting with General Regression Neural Networks and Multilayer Perceptrons Networks  

Science.gov (United States)

Numerous studies have been conducted to forecast univariate hydrological time series using Artificial Neural Networks, and most of them are conducted with Multilayer Perceptrons Networks (MLP). In the present study, a simple one-parameter neural network model, General Regression Neural Networks (GRNN), is proposed for forecasting univariate time series. The proposed GRNN approach employs the theory of phase-space to reconstruct the evolution trajectory of motion, which is used as the input. The projected state uses unequal weights; the nearer projected state is weighed heavier than the remotely projected state -- a reasonable approximation in the phase-space. The parameter of the GRNN (i.e. smoothing factor) determines how tightly the predictions match the actual values in the training patterns. For example, a low value of the smoothing factor causes a tighter surface fit through the data. Therefore, the success of the GRNN depends heavily on the smoothing factor. The advantage of GRNN over MLP is that it takes only a few iterations to converge to the desired solution, and only one parameter has to be optimized. The performance of the GRNN is tested on a real hydrological time series, the daily discharge data observed at the Tryggevaelde catchment in Denmark. The study shows that the GRNN performs very well in the prediction of the discharge series. The performance of the GRNN is also found to be comparable with that of MLP.

Islam, M.; Sivakumar, B.; Wallender, W. W.

2001-12-01

77

Application of a multilayer perceptron neural network to phytoplankton concentration using marine reflectance measures  

Science.gov (United States)

The multilayer perceptron (MLP) neural network have been widely used to fit non-linear transfer function and performed well. In this study, we use MLP to estimate chlorophyll-a concentrations from marine reflectance measures. The optical data were assembled from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Algorithm Mini-workshop (SeaBAM). Most bio-optical algorithms use simple ratios of reflectance in blue and green bands or combinations of ratios as parameters for regression analysis. Regression analysis has limitations for nonlinear function. Neural network, however, have been shown better performance for nonlinear problems. The result showed that accuracy of chlorophyll-a concentration using MLP is much higher than that of regression method. Nevertheless, using all of the five bands as input can derive the best performance. The results showed that each band could carry some useful messages for ocean color remote sensing. Only using band ratio (OC2) or band switch (OC4) might lose some available information. By preprocessing reflectance data with the principle component analysis (PCA), MLP could derive much better accuracy than traditional methods. The result showed that the reflectance of all bands should not be ignored for deriving the chlorophyll-a concentration because each band carries different useful ocean color information.

Su, Feng-Chun; Ho, Chung-Ru; Kuo, Nan-Jung

2005-01-01

78

Analog Multilayer Perceptron Circuit with On-chip Learning: Portable Electronic Nose  

Science.gov (United States)

This article presents an analog multilayer perceptron (MLP) neural network circuit with on-chip back propagation learning. This low power and small area analog MLP circuit is proposed to implement as a classifier in an electronic nose (E-nose). Comparing with the E-nose using microprocessor or FPGA as a classifier, the E-nose applying analog circuit as a classifier can be faster and much smaller, demonstrate greater power efficiency and be capable of developing a portable E-nose [1]. The system contains four inputs, four hidden neurons, and only one output neuron; this simple structure allows the circuit to have a smaller area and less power consumption. The circuit is fabricated using TSMC 0.18 ?m 1P6M CMOS process with 1.8 V supply voltage. The area of this chip is 1.353×1.353 mm2 and the power consumption is 0.54 mW. Post-layout simulations show that the proposed analog MLP circuit can be successively trained to identify three kinds of fruit odors.

Pan, Chih-Heng; Tang, Kea-Tiong

2011-09-01

79

Gas chimney detection based on improving the performance of combined multilayer perceptron and support vector classifier  

Directory of Open Access Journals (Sweden)

Full Text Available Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general applicability, is demonstrated here on a gas chimney detection problem. First, we evaluate a set of input seismic attributes extracted at locations labeled by a human expert using regularized discriminant analysis (RDA. In order to find the RDA score for each seismic attribute, forward and backward search strategies are used. Subsequently, two non-linear classifiers: multilayer perceptron (MLP and support vector classifier (SVC are run on the ranked seismic attributes. Finally, to capitalize on the intrinsic differences between both classifiers, the MLP and SVC results are combined using logical rules of maximum, minimum and mean. The proposed method optimizes the ranked feature space size and yields the lowest classification error in the final combined result. We will show that the logical minimum reveals gas chimneys that exhibit both the softness of MLP and the resolution of SVC classifiers.

H. Hashemi

2008-11-01

80

Photometric redshifts with the Multilayer Perceptron Neural Network: application to the HDF-S and SDSS  

CERN Document Server

We present a technique for the estimation of photometric redshifts based on feed-forward neural networks. The Multilayer Perceptron (MLP) Artificial Neural Network is used to predict photometric redshifts in the HDF-S from an ultra deep multicolor catalog. Various possible approaches for the training of the neural network are explored, including the deepest and most complete spectroscopic redshift catalog currently available (the Hubble Deep Field North dataset) and models of the spectral energy distribution of galaxies available in the literature. The MLP can be trained on observed data, theoretical data and mixed samples. The prediction of the method is tested on the spectroscopic sample in the HDF-S (44 galaxies). Over the entire redshift range, $0.1

Vanzella, E; Fontana, A; Nonino, M; Arnouts, S; Giallongo, E; Grazian, A; Fasano, G; Popesso, P; Saracco, P; Zaggia, S R

2003-01-01

 
 
 
 
81

Face Recognition through Multilayer Perceptron (MLP and Learning Vector Quantization (LVQ  

Directory of Open Access Journals (Sweden)

Full Text Available Face recognition is challenging problems and there is still a lot of work that needs to be done in this area. Over the past ten years, face recognition has received substantial attention from researchers in biometrics, pattern recognition, computer vision, and cognitive psychology communities. This common interest in facial recognition technology among researchers working in diverse fields is motivated both by the remarkable ability to recognize people and by the increased attention being devoted to security applications. Applications of face recognition can be found in security, tracking, multimedia, and entertainment domains.This paper presents a face recognition system using artificial neural network. Here, we have designed a neural network with some own set network parameters. The results presented here have been obtained using two basic methods: multilayer perceptron (MLP, and learning vector quantization (LVQ. In both cases, two kinds of data have been fed to the classifiers: reduced resolution images (gray level or segmented, and feature vectors. The experimental results also show that, for the approaches considered here, analyzing gray level images produced better results than analyzing geometrical features, either because of the errors introduced during their extraction or because the original images have a richer information content. Furthermore, training times were much shorter for LVQ than for MLP. On the other hand, MLP achieved lower error rates when dealing with geometrical features.

Dr. Ikvinderpal Singh

2012-12-01

82

Prediction for energy content of Taiwan municipal solid waste using multilayer perceptron neural networks.  

Science.gov (United States)

In the past decade, the treatment amount of municipal solid waste (MSW) by incineration has increased significantly in Taiwan. By year 2008, approximately 70% of the total MSW generated will be incinerated. The energy content (usually expressed by lower heating value [LHV]) of MSW is an important parameter for the selection of incinerator capacity. In this work, wastes from 55 sampling sites, including villages, towns, cities, and remote islands in the Taiwan area, were sampled and analyzed once a season from April 2002 to March 2003 to determine the waste characteristics. The LHV of MSW in Taiwan was predicted by the multilayer perceptron (MLP) neural networks model using the input parameters of elemental analysis and dry- or wet-base physical compositions. Although all three of the models predicted LHV values rather accurately, the elemental analysis model provided the most accurate prediction of LHV values. Additionally, the wet-base physical composition model was the easiest and most economical. Therefore, the waste treatment operators can choose the more appropriate analysis method considering situations themselves, such as time, equipment, technology, and cost. PMID:16805410

Shu, Hung-Yee; Lu, Hsin-Chung; Fan, Huan-Jung; Chang, Ming-Chin; Chen, Jyh-Cherng

2006-06-01

83

Cross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural Networks  

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Full Text Available Problem statement: The presence of metastasis in the regional lymph nodes is the most important factor in predicting prognosis in breast cancer. Many biomarkers have been identified that appear to relate to the aggressive behaviour of cancer. However, the nonlinear relation of these markers to nodal status and also the existence of complex interaction between markers have prohibited an accurate prognosis. Approach: The aim of this study is to investigate the effectiveness of a Multilayer Perceptron (MLP for predicting breast cancer progression using a set of four biomarkers of breast tumors. The biomarkers include DNA ploidy, cell cycle distribution (G0G1/G2M, steroid receptors (ER/PR and S-Phase Fraction (SPF. A further objective of the study is to explore the predictive potential of these markers in defining the state of nodal involvement in breast cancer. Two methods of outcome evaluation viz. stratified and simple k-fold Cross Validation (CV are studied in order to assess their accuracy and reliability for neural network validation. Criteria such as output accuracy, sensitivity and specificity are used for selecting the best validation technique besides evaluating the network outcome for different combinations of markers. Results: The results show that stratified 2-fold CV is more accurate and reliable compared to simple k-fold CV as it obtains a higher accuracy and specificity and also provides a more stable network validation in terms of sensitivity. Best prediction results are obtained by using an individual marker-SPF which obtains an accuracy of 65%. Conclusion/Recommendations: Our findings suggest that MLP-based analysis provides an accurate and reliable platform for breast cancer prediction given that an appropriate design and validation method is employed.

Shirin A. Mojarad

2011-01-01

84

Automatic discrimination between supraventricular and ventricular tachycardia using a multilayer perceptron in implantable cardioverter defibrillators.  

Science.gov (United States)

The morphological analysis of implantable cardioverter defibrillator (ICD) stored electrograms (EGM) using a multilayer perceptron (MLP) has been proposed for discrimination between supraventricular and ventricular arrhythmias. However, a reliable estimation of the accuracy of MLP methods is lacking. The aim of the study was to compare the morphology and spectrum-based MLP with more conventional morphology-based algorithms in a large series of ICD-stored episodes of arrhythmia. One set of ICD-stored electrograms was used for control and training purposes and a second one, consisting of spontaneous episodes in patients with dual chamber ICDs, for validation of the MLP performance. The correlation waveform analysis (CWA) and the EGM width criterion were compared with MLP methods. Bootstrap resampling techniques were used to extract the relevant information in the MLP training. The morphology-based MLP achieved better discrimination than any other method, with areas under the receiver operating characteristic (ROC) curve (tolerance intervals): 0.96 (0.81, 0.96) for MLP, 0.91 (0.77, 0.94) for CWA, and 0.68 (0.49, 0.78) for EGM width in the validation set. A specificity of 73.0% was obtained at 95% sensitivity, compared with 38.1% and 55.1% using CWA and EGM width criteria, respectively. In contrast, the generalization capabilities of spectral-based MLP methods are poor, showing a lower area under the ROC curve in the validation set. Time-domain MLP techniques may be useful for the morphological analysis of the intracardiac EGM signal stored by ICD devices. When properly trained and validated, these methods perform better than other commonly used morphological criteria for discrimination between supraventricular and ventricular arrhythmias. PMID:12494618

Rojo-Alvarez, José L; García-Alberola, Arcadi; Arenal-Maíz, Angel; Piñeiro-Ave, José; Valdés-Chavarri, Mariano; Artés-Rodríguez, Antonio

2002-11-01

85

On electron and pion identification using a multilayer perceptron in the transition radiation detector of the CBM experiment  

International Nuclear Information System (INIS)

The problem of pion-electron identification based on their energy losses in the TRD is considered in the frame of the CBM experiment. For particles identification an artificial neural network (ANN) was used, a multilayer perceptron realized in JETNET and ROOT packages. It is demonstrated that, in order to get correct and comparable results, it is important to define the network structure correctly. The recommendations for such a selection are given. In order to achieve an acceptable level of pions suppression, the energy losses need to be transformed to more 'effective' variables. The dependency of ANN output threshold for a fixed portion of electron loss on the particle momentum is presented

2009-01-01

86

Fast accurate MEG source localization using a multilayer perceptron trained with real brain noise  

International Nuclear Information System (INIS)

Iterative gradient methods such as Levenberg-Marquardt (LM) are in widespread use for source localization from electroencephalographic (EEG) and magnetoencephalographic (MEG) signals. Unfortunately, LM depends sensitively on the initial guess, necessitating repeated runs. This, combined with LM's high per-step cost, makes its computational burden quite high. To reduce this burden, we trained a multilayer perceptron (MLP) as a real-time localizer. We used an analytical model of quasistatic electromagnetic propagation through a spherical head to map randomly chosen dipoles to sensor activities according to the sensor geometry of a 4D Neuroimaging Neuromag-122 MEG system, and trained a MLP to invert this mapping in the absence of noise or in the presence of various sorts of noise such as white Gaussian noise, correlated noise, or real brain noise. A MLP structure was chosen to trade off computation and accuracy. This MLP was trained four times, with each type of noise. We measured the effects of initial guesses on LM performance, which motivated a hybrid MLP-start-LM method, in which the trained MLP initializes LM. We also compared the localization performance of LM, MLPs, and hybrid MLP-start-LMs for realistic brain signals. Trained MLPs are much faster than other methods, while the hybrid MLP-start-LMs are faster and more accurate than fixed-4-start-LM. In particular, the hybrid MLP-start-LM initialized by a MLP trained with the real brain noise dataset is 60 times faster and is comparable in accuracy to random-20-start-LM, and this hybrid system (localization error: 0.28 cm, computation time: 36 ms) shows almost as good performance as optimal-1-start-LM (localization error: 0.23 cm, computation time: 22 ms), which initializes LM with the correct dipole location. MLPs trained with noise perform better than the MLP trained without noise, and the MLP trained with real brain noise is almost as good an initial guesser for LM as the correct dipole location. (author) )

2002-07-21

87

An Optical Thresholding Perceptron  

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An implementation of an optical perceptron with a soft optical threshold trained with an adapted BP algorithm is described as a precursor to an optical multilayer perceptron (MLP). It has 64 inputs and ten outputs. The soft threshold is implemented by a liquid crystal light valve. Experimental results on perceptron recall are also reported. The effect of a modified grey-scale to weight mapping for weight levels implemented by LCTVs is evaluated based on the results of handwritten digit recogn...

Saxena, Indu; Moerland, Perry; Fiesler, Emile; Pourzand, A. R.; Collings, N.

1997-01-01

88

Replica Symmetry Breaking and the Kuhn-Tucker Cavity Method in Simple and Multilayer Perceptrons  

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Within a Kuhn-Tucker cavity method introduced in a former paper, we study optimal stability learning for situations, where in the replica formalism the replica symmetry may be broken, namely (i) the case of a simple perceptron above the critical loading, and (ii) the case of two-layer AND-perceptrons, if one learns with maximal stability. We find that the deviation of our cavity solution from the replica symmetric one in these cases is a clear indication of the necessity of replica symmetry b...

Gerl, F.; Krey, U.

1997-01-01

89

Replica Symmetry Breaking and the Kuhn-Tucker Cavity Method in simple and multilayer Perceptrons  

CERN Document Server

Within a Kuhn-Tucker cavity method introduced in a former paper, we study optimal stability learning for situations, where in the replica formalism the replica symmetry may be broken, namely (i) the case of a simple perceptron above the critical loading, and (ii) the case of two-layer AND-perceptrons, if one learns with maximal stability. We find that the deviation of our cavity solution from the replica symmetric one in these cases is a clear indication of the necessity of replica symmetry breaking. In any case the cavity solution tends to underestimate the storage capabilities of the networks.

Gerl, F

1996-01-01

90

Comparison between Multi-Layer Perceptron and Radial Basis Function Networks for Sediment Load Estimation in a Tropical Watershed  

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Full Text Available Prediction of highly non-linear behavior of suspended sediment flow in rivers has prime importance in environmental studies and watershed management. In this study, the predictive performance of two Artificial Neural Networks (ANNs, namely Radial Basis Function (RBF and Multi-Layer Perceptron (MLP were compared. Time series data of daily suspended sediment discharge and water discharge at the Langat River, Malaysia were used for training and testing the networks. Mean Square Error (MSE, Normalized Mean Square Error (NMSE and correlation coefficient (r were used for performance evaluation of the models. Using the testing data set, both models produced a similar level of robustness in sediment load simulation. The MLP network model showed a slightly better output than the RBF network model in predicting suspended sediment discharge, especially in the training process. However, both ANNs showed a weak robustness in estimating large magnitudes of sediment load.

Hadi Memarian

2012-10-01

91

Exploiting Heavy Tails in Training Times of Multilayer Perceptrons. A Case Study with the UCI Thyroid Disease Database  

CERN Document Server

The random initialization of weights of a multilayer perceptron makes it possible to model its training process as a Las Vegas algorithm, i.e. a randomized algorithm which stops when some required training error is obtained, and whose execution time is a random variable. This modelling is used to perform a case study on a well-known pattern recognition benchmark: the UCI Thyroid Disease Database. Empirical evidence is presented of the training time probability distribution exhibiting a heavy tail behavior, meaning a big probability mass of long executions. This fact is exploited to reduce the training time cost by applying two simple restart strategies. The first assumes full knowledge of the distribution yielding a 40% cut down in expected time with respect to the training without restarts. The second, assumes null knowledge, yielding a reduction ranging from 9% to 23%.

Cebrian, Manuel

2007-01-01

92

Feature-Based Facial Expression Recognition: Experiments With a Multi-Layer Perceptron  

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In this paper, we report our experiments on feature-based facial expression recognition within an architecture based on a two-layer perceptron. We investigate the use of two types of features extracted from face images: the geometric positions of a set of fiducialpoints on a face, and a set of multi-scale and multi-orientation Gabor wavelet coefficients at these points. They can be used either independently or jointly. The recognition performance with different types of features has been comp...

Zhang, Zhengyou

1998-01-01

93

Compact yet efficient hardware architecture for multilayer-perceptron neural networks Arquitetura de hardware compacta e eficiente para redes neurais artificiais do tipo múltiplas camadas  

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There are several neural network implementations using either software, hardware-based or a hardware/software co-design. This work proposes a hardware architecture to implement an artificial neural network (ANN), whose topology is the multilayer perceptron (MLP). In this paper, we explore the parallelism of neural networks and allow on-thefly changes of the number of inputs, number of layers and number of neurons per layer of the net. This reconfigurability characteristic permits that any app...

Rodrigo Martins da Silva; Luiza de Macedo Mourelle; Nadia Nedjah

2011-01-01

94

On the Comparison of Capacitance-Based Tomography Data Normalization Methods for Multilayer Perceptron Recognition of Gas-Oil Flow Patterns  

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Normalization is important for Electrical Capacitance Tomography (ECT) data due to the very small capacitance values obtained either from the physical or simulated ECT system.  Thus far, there are two commonly used normalization methods for ECT, but their suitability has not been investigated.  This paper presents the work on comparing the performances of two Multilayer Perceptron (MLP) neural networks; one trained based on ECT data normalized using the conventional equation and the other n...

Hafizah Talib; Junita Mohamad-Saleh; Khursiah Zainal-Mokhtar; Najwan Osman-Ali

2009-01-01

95

Lithofacies prediction from well log data using a multilayer perceptron (MLP) and Kohonen's self-organizing map (SOM) - a case study from the Algerian Sahara  

Science.gov (United States)

In this paper, a combination of supervised and unsupervised leanings is used for lithofacies classification from well log data. The main idea consists of enhancing the multilayer perceptron (MLP) learning by the output of the self-organizing map (SOM) neural network. Application to real data of two wells located the Algerian Sahara clearly shows that the lithofacies model built by the neural combination is able to give better results than a self-organizing map.

Ouadfeul, S.-A.; Aliouane, L.

2013-06-01

96

Critical heat flux prediction by using radial basis function and multilayer perceptron neural networks: A comparison study  

Energy Technology Data Exchange (ETDEWEB)

Critical heat flux (CHF) is an important parameter for the design of nuclear reactors. Although many experimental and theoretical researches have been performed, there is not a single correlation to predict CHF because it is influenced by many parameters. These parameters are based on fixed inlet, local and fixed outlet conditions. Artificial neural networks (ANNs) have been applied to a wide variety of different areas such as prediction, approximation, modeling and classification. In this study, two types of neural networks, radial basis function (RBF) and multilayer perceptron (MLP), are trained with the experimental CHF data and their performances are compared. RBF predicts CHF with root mean square (RMS) errors of 0.24%, 7.9%, 0.16% and MLP predicts CHF with RMS errors of 1.29%, 8.31% and 2.71%, in fixed inlet conditions, local conditions and fixed outlet conditions, respectively. The results show that neural networks with RBF structure have superior performance in CHF data prediction over MLP neural networks. The parametric trends of CHF obtained by the trained ANNs are also evaluated and results reported.

Vaziri, Nima [Department of Physics, Islamic Azad University, Karaj Branch, Moazen Blvd., Rajaee shahr (Iran, Islamic Republic of)]. E-mail: n.vaziri@gmail.com; Hojabri, Alireza [Department of Physics, Islamic Azad University, Karaj Branch, Moazen Blvd., Rajaee shahr (Iran, Islamic Republic of); Erfani, Ali [Department of Physics, Islamic Azad University, Karaj Branch, Moazen Blvd., Rajaee shahr (Iran, Islamic Republic of); Monsefi, Mehrdad [Department of Physics, Islamic Azad University, Karaj Branch, Moazen Blvd., Rajaee shahr (Iran, Islamic Republic of); Nilforooshan, Behnam [Department of Physics, Islamic Azad University, Karaj Branch, Moazen Blvd., Rajaee shahr (Iran, Islamic Republic of)

2007-02-15

97

Critical heat flux prediction by using radial basis function and multilayer perceptron neural networks: A comparison study  

International Nuclear Information System (INIS)

Critical heat flux (CHF) is an important parameter for the design of nuclear reactors. Although many experimental and theoretical researches have been performed, there is not a single correlation to predict CHF because it is influenced by many parameters. These parameters are based on fixed inlet, local and fixed outlet conditions. Artificial neural networks (ANNs) have been applied to a wide variety of different areas such as prediction, approximation, modeling and classification. In this study, two types of neural networks, radial basis function (RBF) and multilayer perceptron (MLP), are trained with the experimental CHF data and their performances are compared. RBF predicts CHF with root mean square (RMS) errors of 0.24%, 7.9%, 0.16% and MLP predicts CHF with RMS errors of 1.29%, 8.31% and 2.71%, in fixed inlet conditions, local conditions and fixed outlet conditions, respectively. The results show that neural networks with RBF structure have superior performance in CHF data prediction over MLP neural networks. The parametric trends of CHF obtained by the trained ANNs are also evaluated and results reported

2007-02-01

98

Time series modeling with pruned multi-layer perceptron and 2-stage damped least-squares method  

Science.gov (United States)

A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks often used in TS modeling and forecasting. Because of its "black box" aspect, many researchers refuse to use it. Moreover, the optimization (often based on the exhaustive approach where "all" configurations are tested) and learning phases of this artificial intelligence tool (often based on the Levenberg-Marquardt algorithm; LMA) are weaknesses of this approach (exhaustively and local minima). These two tasks must be repeated depending on the knowledge of each new problem studied, making the process, long, laborious and not systematically robust. In this paper a pruning process is proposed. This method allows, during the training phase, to carry out an inputs selecting method activating (or not) inter-nodes connections in order to verify if forecasting is improved. We propose to use iteratively the popular damped least-squares method to activate inputs and neurons. A first pass is applied to 10% of the learning sample to determine weights significantly different from 0 and delete other. Then a classical batch process based on LMA is used with the new MLP. The validation is done using 25 measured meteorological TS and cross-comparing the prediction results of the classical LMA and the 2-stage LMA.

Voyant, Cyril; Tamas, Wani; Paoli, Christophe; Balu, Aurélia; Muselli, Marc; Nivet, Marie-Laure; Notton, Gilles

2014-03-01

99

Application of Multi-Layered Perceptron Neural network (MLPNN) to Combined Economic and Emission Dispatch  

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This paper presents a multi-layered perceptronneural network (MLPNN) method to solve the combinedeconomic and emission dispatch (CEED) problem. The harmfulecological effects caused by the emission of particulate andgaseous pollutants like sulfur dioxide (SO2) and oxides ofnitrogen ( NOx ) can be reduced by adequate distribution ofload between the plants of a power system. However, this leadsto a noticeable increase in the operating cost of the plants. Thispaper presents the (MLPNN) method app...

2012-01-01

100

Application of Multi-Layered Perceptron Neural network (MLPNN to Combined Economic and Emission Dispatch  

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Full Text Available This paper presents a multi-layered perceptronneural network (MLPNN method to solve the combinedeconomic and emission dispatch (CEED problem. The harmfulecological effects caused by the emission of particulate andgaseous pollutants like sulfur dioxide (SO2 and oxides ofnitrogen ( NOx can be reduced by adequate distribution ofload between the plants of a power system. However, this leadsto a noticeable increase in the operating cost of the plants. Thispaper presents the (MLPNN method applied for the successfuloperation of the power system subject to economical andenvironmental constraints. The proposed MLP NN method istested for a three plant thermal power system and the results arecompared with the solutions obtained from the classical lambdaiterative technique and simple genetic algorithm (SGA refinedgenetic algorithm (RGA method.

Sarakhs branch

2012-01-01

 
 
 
 
101

Moisture Content Prediction of Dried Longan Aril from Dielectric Constant Using Multilayer Perceptrons and Support Vector Regression  

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Full Text Available Problem statement: Estimation of moisture contents of dried food products from their dielectric constants was an important step in moisture measurement systems. The regression models that provide good prediction performance are desirable. Approach: The Multilayer Perceptrons (MLP and Support Vector Regression (SVR were applied in this research to predict the moisture contents of dried longan arils from their dielectric constants. The data set was collected from 1500 samples of dried longan aril with five different moisture contents of 10, 14, 18, 22 and 25% Wet basis (Wb. Dielectric constant of dried longan aril was measured by using our previously proposed electrical capacitance-based system. The results from the MLP and SVR models were compared to that from the linear regression and polynomial regression models. To take into account the generalization of the models, the four-fold cross validation was applied. Results: For the training sets, the average mean absolute errors over three bulk densities of 1.30, 1.45 and 1.60 g cm-3 were 1.7578, 0.6157, 0.3812, 0.3113, 0.0103 and 0.0044% Wb for the linear regression, second-, third-, fourth-order polynomial regression, MLP and SVR models, respectively. For the validation sets, the average mean absolute errors over the three bulk densities were 1.7616, 0.6192, 0.3844, 0.3146, 0.0126 and 0.0093% Wb for the linear regression, 2nd, 3rd and 4th-order polynomial regression, MLP and SVR models, respectively. Conclusion: The regression models based on MLP and SVR yielded better performances than the models based on linear regression and polynomial regression on both training and validation sets. The models based on MLP and SVR also provided robustness to the variation of bulk density. Not only for dried longan aril, the proposed models can also be adapted and applied to other materials or dried food products.

Sanong Amaroek

2010-01-01

102

Evaluation of Süleymanköy (Diyarbakir, Eastern Turkey) and Seferihisar (Izmir, Western Turkey) Self Potential Anomalies with Multilayer Perceptron Neural Networks  

Science.gov (United States)

Self-potential (SP) is one of the oldest geophysical methods that provides important information about near-surface structures. Several methods have been developed to interpret SP data using simple geometries. This study investigated inverse solution of a buried, polarized sphere-shaped self-potential (SP ) anomaly via Multilayer Perceptron Neural Networks ( MLPNN ). The polarization angle ( ? ) and depth to the centre of sphere ( h )were estimated. The MLPNN is applied to synthetic and field SP data. In order to see the capability of the method in detecting the number of sources, MLPNN was applied to different spherical models at different depths and locations.. Additionally, the performance of MLPNN was tested by adding random noise to the same synthetic test data. The sphere model successfully obtained similar parameters under different S/N ratios. Then, MLPNN method was applied to two field examples. The first one is the cross section taken from the SP anomaly map of the Ergani-Süleymanköy (Turkey) copper mine. MLPNN was also applied to SP data from Seferihisar Izmir (Western Turkey) geothermal field. The MLPNN results showed good agreement with the original synthetic data set. The effect of The technique gave satisfactory results following the addition of 5% and 10% Gaussian noise levels. The MLPNN results were compared to other SP interpretation techniques, such as Normalized Full Gradient (NFG), inverse solution and nomogram methods. All of the techniques showed strong similarity. Consequently, the synthetic and field applications of this study show that MLPNN provides reliable evaluation of the self potential data modelled by the sphere model.

Kaftan, Ilknur; Sindirgi, Petek

2013-04-01

103

Data Optimization with Multilayer Perceptron Neural Network and Using New Pattern in Decision Tree Comparatively  

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Full Text Available Problem statement: The aim of the present study is to exemplify the use of Artificial Neural Networks (ANN for parameter prediction. Missing value or unreal approach to some questions in scale is a problem for unbiased findings. To learn a real pattern with ANN provides robust and unbiased parameter estimation. Approach: To this end, data was collected from 906 students using ?Scale of student views about the expected situations and the current expectations from their families during learning process? for the study entitled ?Student views about the expected situations and the current expectations from their families during learning process?. In the study, first the initial data set gathered using the measurement tool and the new data set produced by Multi-Layer Receptors algorithm, which was considered as the highest predictive level of ANN for the research were individually analyzed by Chaid analysis and the results of the two analyses were compared. Results: The findings showed that as a result of Chaid analysis with the initial data set the variable ?education level of mother? had a considerable effect on total score dependent variable, while ?education level of father? was the influential variable on the attitude level in the data set predicted by ANN, unlike the previous model. Conclusion/Recommendations: The findings of the research show Artificial Neural Networks could be used for parameter estimation in cause-effect based studies. It is also thought the research will contribute to extensive use of advanced statistical methods.

Murat Kayri

2010-01-01

104

Evaluation of 1-D tracer concentration profile in a small river by means of Multi-Layer Perceptron Neural Networks  

Directory of Open Access Journals (Sweden)

Full Text Available The prediction of temporal concentration profiles of a transported pollutant in a river is still a subject of ongoing research efforts worldwide. The present paper is aimed at studying the possibility of using Multi-Layer Perceptron Neural Networks to evaluate the whole concentration versus time profile at several cross-sections of a river under various flow conditions, using as little information about the river system as possible. In contrast with the earlier neural networks based work on longitudinal dispersion coefficients, this new approach relies more heavily on measurements of concentration collected during tracer tests over a range of flow conditions, but fewer hydraulic and morphological data are needed. The study is based upon 26 tracer experiments performed in a small river in Edinburgh, UK (Murray Burn at various flow rates in a 540 m long reach. The only data used in this study were concentration measurements collected at 4 cross-sections, distances between the cross-sections and the injection site, time, as well as flow rate and water velocity, obtained according to the data measured at the 1st and 2nd cross-sections.

The four main features of concentration versus time profiles at a particular cross-section, namely the peak concentration, the arrival time of the peak at the cross-section, and the shapes of the rising and falling limbs of the profile are modeled, and for each of them a separately designed neural network was used. There was also a variant investigated in which the conservation of the injected mass was assured by adjusting the predicted peak concentration. The neural network methods were compared with the unit peak attenuation curve concept.

In general the neural networks predicted the main features of the concentration profiles satisfactorily. The predicted peak concentrations were generally better than those obtained using the unit peak attenuation method, and the method with mass-conservation assured generally performed better than the method that did not account for mass-conservation. Predictions of peak travel time were also better using the neural networks than the unit peak attenuation method. Including more data into the neural network training set clearly improved the prediction of the shapes of the concentration profiles. Similar improvements in peak concentration were less significant and the travel time prediction appeared to be largely unaffected.

A. Piotrowski

2007-08-01

105

Evaluation of 1-D tracer concentration profile in a small river by means of Multi-Layer Perceptron Neural Networks  

Directory of Open Access Journals (Sweden)

Full Text Available The prediction of temporal concentration profiles of a transported pollutant in a river is still a subject of ongoing research efforts worldwide. The present paper is aimed at studying the possibility of using Multi-Layer Perceptron Neural Networks to evaluate the whole concentration versus time profile at several cross-sections of a river under various flow conditions, using as little information about the river system as possible. In contrast with the earlier neural networks based work on longitudinal dispersion coefficients, this new approach relies more heavily on measurements of concentration collected during tracer tests over a range of flow conditions, but fewer hydraulic and morphological data are needed. The study is based upon 26 tracer experiments performed in a small river in Edinburgh, UK (Murray Burn at various flow rates in a 540 m long reach. The only data used in this study were concentration measurements collected at 4 cross-sections, distances between the cross-sections and the injection site, time, as well as flow rate and water velocity, obtained according to the data measured at the 1st and 2nd cross-sections.

The four main features of concentration versus time profiles at a particular cross-section, namely the peak concentration, the arrival time of the peak at the cross-section, and the shapes of the rising and falling limbs of the profile are modeled, and for each of them a separately designed neural network was used. There was also a variant investigated in which the conservation of the injected mass was assured by adjusting the predicted peak concentration. The neural network methods were compared with the unit peak attenuation curve concept.

In general the neural networks predicted the main features of the concentration profiles satisfactorily. The predicted peak concentrations were generally better than those obtained using the unit peak attenuation method, and the method with mass-conservation assured generally performed better than the method that did not account for mass-conservation. Predictions of peak travel time were also better using the neural networks than the unit peak attenuation method. Including more data into the neural network training set clearly improved the prediction of the shapes of the concentration profiles. Similar improvements in peak concentration were less significant and the travel time prediction appeared to be largely unaffected.

A. Piotrowski

2007-12-01

106

Preprocessing perceptrons  

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Reliable results are crucial when working with medical decision support systems. A decision support system should be reliable but also be interpretable, i.e. able to show how it has inferred its conclusions. In this thesis, the preprocessing perceptron is presented as a simple but effective and efficient analysis method to consider when creating medical decision support systems. The preprocessing perceptron has the simplicity of a perceptron combined with a performance comparable to the multi...

Kallin Westin, Lena

2004-01-01

107

Generación dinámica de la topología de una red neuronal artificial del tipo perceptron multicapa / Dynamic topology generation of an artificial neural network of the multilayer perceptron type  

Scientific Electronic Library Online (English)

Full Text Available SciELO Colombia | Language: Spanish Abstract in spanish En este trabajo se aplica un método constructivo aproximado para encontrar ar­quitecturas de redes neuronales artificiales (RNA) de tipo perceptrón multicapa (PMC). El método se complementa con la técnica de la búsqueda forzada de mejores mínimos locales. El entrenamiento de la red se lleva a cabo a [...] través del algoritmo gradiente descendente básico (GDB); se aplican técnicas como la repetición del entrenamiento y la detención temprana (validación cruzada), para mejorar los resultados. El criterio de evaluación se basa en las habilidades de aprendizaje y de generalización de las arquitecturas generadas específicas de un dominio. Se presentan resultados experimentales con los cuales se demuestra la efectividad del método propuesto y comparan con las arquitecturas halladas por otros métodos. Abstract in english This paper deals with an approximate constructive method to find architectures of artificial neuronal network (ANN) of the type MultiLayer Percetron (MLP) which solves a particular problem. This method is supplemented with the technique of the Forced search of better local minima. The training of th [...] e net uses an algorithm basic descending gradient (BDG). Techniques such as repetition of the training and the early stopping (cross validation) are used to improve the results. The evaluation approach is based not only on the learning abilities but also on the generalization of the specific generated architectures of a domain. Experimental results are presented in order to prove the effectiveness of the proposed method. These are compared with architectures found by other methods.

Héctor, Tabares; John, Branch; Jaime, Valencia.

108

On the Comparison of Capacitance-Based Tomography Data Normalization Methods for Multilayer Perceptron Recognition of Gas-Oil Flow Patterns  

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Full Text Available Normalization is important for Electrical Capacitance Tomography (ECT data due to the very small capacitance values obtained either from the physical or simulated ECT system.  Thus far, there are two commonly used normalization methods for ECT, but their suitability has not been investigated.  This paper presents the work on comparing the performances of two Multilayer Perceptron (MLP neural networks; one trained based on ECT data normalized using the conventional equation and the other normalized using the improved equation, to recognize gas-oil flow patterns.  The correct pattern recognition percentages for both MLPs were calculated and compared.  The results showed that the MLP trained with the conventional ECT normalization equation out-performed the ones trained with the improved normalization data for the task of gas-oil pattern recognition.

Hafizah Talib

2009-02-01

109

Local linear perceptrons for classification.  

Science.gov (United States)

A structure composed of local linear perceptrons for approximating global class discriminants is investigated. Such local linear models may be combined in a cooperative or competitive way. In the cooperative model, a weighted sum of the outputs of the local perceptrons is computed where the weight is a function of the distance between the input and the position of the local perceptron. In the competitive model, the cost function dictates a mixture model where only one of the local perceptrons give output. Learning of the local models' positions and the linear mappings they implement are coupled and both supervised. We show that this is preferable to the uncoupled case where the positions are trained in an unsupervised manner before the separate, supervised training of mappings. We use goodness criteria based on the cross-entropy and give learning equations for both the cooperative and competitive cases. The coupled and uncoupled versions of cooperative and competitive approaches are compared among themselves and with multilayer perceptrons of sigmoidal hidden units and radial basis functions (RBFs) of Gaussian units on the application of recognition of handwritten digits. The criteria of comparison are the generalization accuracy, learning time, and the number of free parameters. We conclude that even on such a high-dimensional problem, such local models are promising. They generalize much better than RBF's and use much less memory. When compared with multilayer perceptrons, we note that local models learn much faster and generalize as well and sometimes better with comparable number of parameters. PMID:18263476

Alpaydin, E; Jordan, M I

1996-01-01

110

Determination of near-surface structures from multi-channel surface wave data using multi-layer perceptron neural network (MLPNN) algorithm  

Science.gov (United States)

This study proposes the use of multi-layer perceptron neural networks (MLPNN) to invert dispersion curves obtained via multi-channel analysis of surface waves (MASW) for shear S-wave velocity profile. The dispersion curve used in inversion includes the fundamental-mode dispersion data. In order to investigate the applicability and performance of the proposed MLPNN algorithm, test studies were performed using both synthetic and field examples. Gaussian random noise with a standard deviation of 4 and 8% was added to the noise-free test data to make the synthetic test more realistic. The model parameters, such as S-wave velocities and thicknesses of the synthetic layered-earth model, were obtained for different S/N ratios and noise-free data. The field survey was performed over the natural gas pipeline, located in the Germencik district of Ayd?n city, western Turkey. The results show that depth, velocity, and location of the embedded natural gas pipe are successfully estimated with reasonably good approximation.

Çaylak, Ça?r?; Kaftan, ?lknur

2014-04-01

111

Hourly air temperature driven using multi-layer perceptron and radial basis function networks in arid and semi-arid regions  

Science.gov (United States)

This study employed two artificial neural network (ANN) models, including multi-layer perceptron (MLP) and radial basis function (RBF), as data-driven methods of hourly air temperature at three meteorological stations in Fars province, Iran. MLP was optimized using the Levenberg-Marquardt (MLP_LM) training algorithm with a tangent sigmoid transfer function. Both time series (TS) and randomized (RZ) data were used for training and testing of ANNs. Daily maximum and minimum air temperatures (MM) and antecedent daily maximum and minimum air temperatures (AMM) constituted the input for ANNs. The ANN models were evaluated using the root mean square error (RMSE), the coefficient of determination ( R 2) and the mean absolute error. The use of AMM led to a more accurate estimation of hourly temperature compared with the use of MM. The MLP-ANN seemed to have a higher estimation efficiency than the RBF ANN. Furthermore, the ANN testing using randomized data showed more accurate estimation. The RMSE values for MLP with RZ data using daily maximum and minimum air temperatures for testing phase were equal to 1.2°C, 1.8°C, and 1.7°C, respectively, at Arsanjan, Bajgah, and Kooshkak stations. The results of this study showed that hourly air temperature driven using ANNs (proposed models) had less error than the empirical equation.

Rezaeian-Zadeh, Mehdi; Zand-Parsa, Shahrookh; Abghari, Hirad; Zolghadr, Masih; Singh, Vijay P.

2012-08-01

112

Gas sensors characterization and multilayer perceptron (MLP) hardware implementation for gas identification using a Field Programmable Gate Array (FPGA).  

Science.gov (United States)

This paper develops a primitive gas recognition system for discriminating between industrial gas species. The system under investigation consists of an array of eight micro-hotplate-based SnO2 thin film gas sensors with different selectivity patterns. The output signals are processed through a signal conditioning and analyzing system. These signals feed a decision-making classifier, which is obtained via a Field Programmable Gate Array (FPGA) with Very High-Speed Integrated Circuit Hardware Description Language. The classifier relies on a multilayer neural network based on a back propagation algorithm with one hidden layer of four neurons and eight neurons at the input and five neurons at the output. The neural network designed after implementation consists of twenty thousand gates. The achieved experimental results seem to show the effectiveness of the proposed classifier, which can discriminate between five industrial gases. PMID:23529119

Benrekia, Fayçal; Attari, Mokhtar; Bouhedda, Mounir

2013-01-01

113

Multilayer perceptron classification of unknown volatile chemicals from the firing rates of insect olfactory sensory neurons and its application to biosensor design.  

Science.gov (United States)

In this letter, we use the firing rates from an array of olfactory sensory neurons (OSNs) of the fruit fly, Drosophila melanogaster, to train an artificial neural network (ANN) to distinguish different chemical classes of volatile odorants. Bootstrapping is implemented for the optimized networks, providing an accurate estimate of a network's predicted values. Initially a simple linear predictor was used to assess the complexity of the data and was found to provide low prediction performance. A nonlinear ANN in the form of a single multilayer perceptron (MLP) was also used, providing a significant increase in prediction performance. The effect of the number of hidden layers and hidden neurons of the MLP was investigated and found to be effective in enhancing network performance with both a single and a double hidden layer investigated separately. A hybrid array of MLPs was investigated and compared against the single MLP architecture. The hybrid MLPs were found to classify all vectors of the validation set, presenting the highest degree of prediction accuracy. Adjustment of the number of hidden neurons was investigated, providing further performance gain. In addition, noise injection was investigated, proving successful for certain network designs. It was found that the best-performing MLP was that of the double-hidden-layer hybrid MLP network without the use of noise injection. Furthermore, the level of performance was examined when different numbers of OSNs used were varied from the maximum of 24 to only 5 OSNs. Finally, the ideal OSNs were identified that optimized network performance. The results obtained from this study provide strong evidence of the usefulness of ANNs in the field of olfaction for the future realization of a signal processing back end for an artificial olfactory biosensor. PMID:23020109

Bachtiar, Luqman R; Unsworth, Charles P; Newcomb, Richard D; Crampin, Edmund J

2013-01-01

114

Compact yet efficient hardware architecture for multilayer-perceptron neural networks Arquitetura de hardware compacta e eficiente para redes neurais artificiais do tipo múltiplas camadas  

Directory of Open Access Journals (Sweden)

Full Text Available There are several neural network implementations using either software, hardware-based or a hardware/software co-design. This work proposes a hardware architecture to implement an artificial neural network (ANN, whose topology is the multilayer perceptron (MLP. In this paper, we explore the parallelism of neural networks and allow on-thefly changes of the number of inputs, number of layers and number of neurons per layer of the net. This reconfigurability characteristic permits that any application of ANNs may be implemented using the proposed hardware. In order to reduce the processing time that is spent in arithmetic computation, a real number is represented using a fraction of integers. In this way, the arithmetics is limited to integer operations, performed by fast combinational circuits. A simple state machine is required to control sums and products of fractions. Sigmoid is used as the activation function in the proposed implementation. It is approximated by polynomials, whose underlying computation requires only sums and products. A theorem is introduced and proven so as to cover the arithmetic strategy of the computation of the activation function. Thus, the arithmetic circuitry used to implement the neuron weighted sum is reused for computing the sigmoid. this resource sharing decreased drastically the total area of the system. After modeling and simulation for functionality validation, the proposed architecture synthesized using reconfigurable hardware. The results are promising.Em termos computacionais, uma rede neural artificial (RNA pode ser implementada em software ou em hardware, ou ainda de maneira híbrida, combinando ambos os recursos. O presente trabalho propõe uma arquitetura de hardware para a computação de uma rede neural do tipo perceptron com múltiplas camadas (MLP. Soluções em hardware tendem a ser mais eficientes do que soluções em software. O projeto em questão, além de explorar fortemente o paralelismo das redes neurais, permite alterações do número de entradas, número de camadas e de neurônios por camada, de modo que diversas aplicações de RNAs possam ser executadas no hardware proposto. Visando a uma redução de tempo do processamento aritmético, um número real é aproximado por uma fração de inteiros. Dessa forma, as operações aritméticas limitam-se a operações inteiras, executadas por circuitos combinacionais. Uma simples máquina de estados é demandada para controlar somas e produtos de frações. A função de ativação usada neste projeto é a sigmóide. Essa função é aproximada mediante o uso de polinômios, cujas operações são regidas por somas e produtos. Um teorema é introduzido e provado, permitindo a fundamentação da estratégia de cálculo da função de ativação. Dessa forma, reaproveita-se o circuito aritmético da soma ponderada para também computar a sigmóide. Essa re-utilização dos recursos levou a uma redução drástica de área total de circuito. Após modelagem e simulação para validação do bom funcionamento, a arquitetura proposta foi sintetizada utilizando recursos reconfiguráveis, do tipo FPGA. Os resultados são promissores.

Rodrigo Martins da Silva

2011-12-01

115

El uso de perceptrones multicapa para la modelización estadística de series de tiempo no lineales de so2, en Salta Capital, Argentina The use of multilayer perceptrons for statistical modeling so2 non linear time series in Salta Capital, Argentina  

Directory of Open Access Journals (Sweden)

Full Text Available En este trabajo se realizó un estudio estadístico de variables físico químicas asociadas al fenómeno de contaminación ambiental, en particular concentración media mensual de SO2 , medidas en la ciudad Salta Capital, Argentina, simultáneamente a concentraciones de NO2 y O3 . Las series bajo estudio presentaban comportamientos dinámicos no lineales, datos atípicos y cambios estructurales, lo que hizo imposible modelarlas con tipologías econométricas tradiciones (AR, MA, ARMA, ARIMA, entre otras. Una solución eficiente que se encontró, hace uso de la teoría de los perceptrones multicapa. Mediante el modelo estructural de series de tiempo, esta solución se presenta como un proceso matemático iterativo que permite obtener un modelado final el cual tiene una muy alta confiabilidad (95%, para realizar pronoósticos a futuro sobre el comportamiento de la variable estudiada.In this paper a statistical study of phisical-chemistry variables connected with enviroment pollution, specifically SO2 monthly average concentration, measured in Salta Capital city, Argentina, together with NO2 and O3 concentrations, was made. Time series under study shown non linear dinamic behaviour, outliers and structural changes. Due to these it was impossible to use typical econometric typologies (AR, MA, ARMA, ARIMA, among others. An effective solution which uses multistep perceptrons theory was found. By using structural time series modelling, this solution is presented by an iterative mathematical process that allows us to obtain a final model with a high confidence level (95% in order to do the forecasting step on the studied variable.

Haydeé Elena Musso

2013-01-01

116

Exact Solution and Learning of Binary Classification Problems with Simple Perceptrons.  

Science.gov (United States)

This paper discusses the effect of response functions on the performance of multi-layered perceptrons. It will be shown that the N-bit parity problem, and even any binary classification problem, is exactly solvable with a simple perceptron using the right...

J. A. Matla H. P. Stehouwer J. Wessels

1994-01-01

117

Detección de Latidos Cardiacos Patológicos y Normales Utilizando Transformada por Paquetes Wavelet, Máquinas de Soporte Vectorial y Perceptrón Multicapa / Detection of Pathological and Normal Heartbeat Using Wavelet Packet, Support Vector Machines and Multilayer Perceptron  

Scientific Electronic Library Online (English)

Full Text Available SciELO Colombia | Language: Spanish Abstract in spanish Este artículo presenta los resultados obtenidos al desarrollar una metodología para la detección de 5 tipos de latidos cardiacos (Normal (N), Bloqueo de Rama Derecha (RBBB), Bloqueo de Rama Izquierda (LBBB), Contracción Auricular Prematura (APC) y Contracción Ventricular Prematura (PVC)) utilizando [...] la transformada por paquetes Wavelet de manera no adaptativa en la extracción de características de las señales cardiacas, empleando la función Shanon para cálculo de la entropía y adicionando una fase de identificación de nodos por cada tipo de señal cardiaca en el árbol Wavelet. La utilización de la transformada por paquetes Wavelet permite acceder a información obtenida de la descomposición tanto de baja como de alta frecuencia proporcionando un análisis más integral que el logrado con la transformada Wavelet discreta. Se evaluaron Wavelets madre de las familias Daubechies, Symlet 5 y Biortogonal inversa; que fueron resultado de una investigación previa en que se identificaron las Wavelet madre que mayor entropía presentaban con las señales cardiacas. Con la modalidad no adaptativa se reduce el costo computacional al utilizar los paquetes Wavelet, coste que representa la mayor desventaja de esta transformada, dando validez a la investigación realizada. Para la clasificación de los patrones cardiacos se emplearon las máquinas de soporte vectorial y el perceptrón multicapa. Con las máquinas de soporte vectorial empleando kernel de función de base radial, se logró un error de clasificación del 2,57 %. Abstract in english This paper presents the results obtained by developing a methodology to detect 5 types of heartbeats (Normal (N), Right bundle branch block (RBBB), Left bundle branch block (LBBB), Premature atrial contraction (APC) and Premature ventricular contraction (PVC)), using Wavelet transform packets with n [...] on-adaptative mode applied on features extraction from heartbeats. It was used the Shannon function to calculate the entropy and It was added an identification nodes stage per every type of cardiac signal in the Wavelet tree. The using of Wavelet packets transform allows the access to information which results of decomposition of low and high frecuency, giving providing a more integral analysis than achieved by the discrete Wavelet transform. Three families of mother Wavelet were evaluated on transformation: Daubechies, Symlet and Reverse Biorthogonal, which were results from a previous research in that were identified the mother Wavelet that had higher entropy with the cardiac signals. With non-adaptive mode, the computational cost is reduced when Wavelet packets are used; this cost represents the most marked disadvantage from the transform. To classify the heartbeats were used Support Vector Machines and Multilayer Perceptron. The best classification error was achieved employing Support Vector Machine and a radial basis function; it was 2.57 %.

Orozco-Naranjo, Alejandro J.; Muñoz-Gutiérrez, Pablo A..

118

Performance of an Audio Perceptron.  

Science.gov (United States)

Perceptrons are a class of simple adaptive pattern-recognition devices built of crude model neurons. In the work a perceptron is used to recognize patterns generated by an audio preprocessor. The preprocessor is modeled on the cochlea and cochlear ganglio...

M. G. Scattergood

1971-01-01

119

Estimation consistante de l'architecture des perceptrons multicouches  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The estimation of the parameters of the MLP can be done by maximizing the likelihood of the model. In this framework, it is difficult to determine the true number of hidden units because the information matrix of Fisher is not invertible if this number is overestimated. However, if the parameters of the MLP are in a compact set, we prove that the minimization of a...

Rynkiewicz, Joseph

2008-01-01

120

Finite Size Scaling of Perceptron  

CERN Document Server

We study the first-order transition in the model of a simple perceptron with continuous weights and large, bit finite value of the inputs. Making the analogy with the usual finite-size physical systems, we calculate the shift and the rounding exponents near the transition point. In the case of a general perceptron with larger variety of inputs, the analysis only gives bounds for the exponents.

Korutcheva, E R; Korutcheva, Elka

2000-01-01

 
 
 
 
121

Multilayer neural networks : learnability, network generation, and network simplification  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Chapter 1 of this book shall give a little impression of the theoretical diversity of the non-trivial theory of multilayer neural networks (multilayer perceptrons). This diversity comprises ideas from Approximation Theory, Measure and Probability Theory, Statistics, the Theory of NP-Completeness, Geometry, Topology and Graph Theory. In Chapter 2 a new perspective in learning and generalization of multilayer perceptrons is introduced. Proposing a definition of 'representativity' for trai...

Ellerbrock, Thomas M.

1999-01-01

122

Prediction of Bladder Cancer Recurrences Using Artificial Neural Networks  

Science.gov (United States)

Even if considerable advances have been made in the field of early diagnosis, there is no simple, cheap and non-invasive method that can be applied to the clinical monitorisation of bladder cancer patients. Moreover, bladder cancer recurrences or the reappearance of the tumour after its surgical resection cannot be predicted in the current clinical setting. In this study, Artificial Neural Networks (ANN) were used to assess how different combinations of classical clinical parameters (stage-grade and age) and two urinary markers (growth factor and pro-inflammatory mediator) could predict post surgical recurrences in bladder cancer patients. Different ANN methods, input parameter combinations and recurrence related output variables were used and the resulting positive and negative prediction rates compared. MultiLayer Perceptron (MLP) was selected as the most predictive model and urinary markers showed the highest sensitivity, predicting correctly 50% of the patients that would recur in a 2 year follow-up period.

Zulueta Guerrero, Ekaitz; Garay, Naiara Telleria; Lopez-Guede, Jose Manuel; Vilches, Borja Ayerdi; Iragorri, Eider Egilegor; Castaños, David Lecumberri; de La Hoz Rastrollo, Ana Belén; Peña, Carlos Pertusa

123

S\\'election de la structure d'un perceptron multicouches pour la r\\'eduction dun mod\\`ele de simulation d'une scierie  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Simulation is often used to evaluate the relevance of a Directing Program of Production (PDP) or to evaluate its impact on detailed sc\\'enarii of scheduling. Within this framework, we propose to reduce the complexity of a model of simulation by exploiting a multilayer perceptron. A main phase of the modeling of one system using a multilayer perceptron remains the determination of the structure of the network. We propose to compare and use various pruning algorithms in order ...

Thomas, Philippe; Thomas, Andre?

2008-01-01

124

Estimation consistante de l'architecture des perceptrons multicouches  

CERN Document Server

We consider regression models involving multilayer perceptrons (MLP) with one hidden layer and a Gaussian noise. The estimation of the parameters of the MLP can be done by maximizing the likelihood of the model. In this framework, it is difficult to determine the true number of hidden units because the information matrix of Fisher is not invertible if this number is overestimated. However, if the parameters of the MLP are in a compact set, we prove that the minimization of a suitable information criteria leads to consistent estimation of the true number of hidden units.

Rynkiewicz, Joseph

2008-01-01

125

Recurrent neural networks for diagnosis of carpal tunnel syndrome using electrophysiologic findings.  

Science.gov (United States)

This paper presents the use of recurrent neural networks (RNNs) for diagnosis of carpal tunnel syndrome (CTS) (normal, right CTS, left CTS, bilateral CTS). The RNN is trained with the Levenberg-Marquardt algorithm. The RNN is trained on the features of CTS (right median motor latency, left median motor latency, right median sensory latency, left median sensory latency). The multilayer perceptron neural network (MLPNN) is also implemented for comparison the performance of the classifiers on the same diagnosis problem. The total classification accuracy of the RNN is significantly high (94.80%). The obtained results confirmed the validity of the RNNs to help in clinical decision-making. PMID:20703918

Ilbay, Konuralp; Ubeyli, Elif Derya; Ilbay, Gul; Budak, Faik

2010-08-01

126

A Novel Single Neuron Perceptron with Universal Approximation and XOR Computation Properties.  

Science.gov (United States)

We propose a biologically motivated brain-inspired single neuron perceptron (SNP) with universal approximation and XOR computation properties. This computational model extends the input pattern and is based on the excitatory and inhibitory learning rules inspired from neural connections in the human brain's nervous system. The resulting architecture of SNP can be trained by supervised excitatory and inhibitory online learning rules. The main features of proposed single layer perceptron are universal approximation property and low computational complexity. The method is tested on 6 UCI (University of California, Irvine) pattern recognition and classification datasets. Various comparisons with multilayer perceptron (MLP) with gradient decent backpropagation (GDBP) learning algorithm indicate the superiority of the approach in terms of higher accuracy, lower time, and spatial complexity, as well as faster training. Hence, we believe the proposed approach can be generally applicable to various problems such as in pattern recognition and classification. PMID:24868200

Lotfi, Ehsan; Akbarzadeh-T, M-R

2014-01-01

127

Online learning in a chemical perceptron.  

Science.gov (United States)

Autonomous learning implemented purely by means of a synthetic chemical system has not been previously realized. Learning promotes reusability and minimizes the system design to simple input-output specification. In this article we introduce a chemical perceptron, the first full-featured implementation of a perceptron in an artificial (simulated) chemistry. A perceptron is the simplest system capable of learning, inspired by the functioning of a biological neuron. Our artificial chemistry is deterministic and discrete-time, and follows Michaelis-Menten kinetics. We present two models, the weight-loop perceptron and the weight-race perceptron, which represent two possible strategies for a chemical implementation of linear integration and threshold. Both chemical perceptrons can successfully identify all 14 linearly separable two-input logic functions and maintain high robustness against rate-constant perturbations. We suggest that DNA strand displacement could, in principle, provide an implementation substrate for our model, allowing the chemical perceptron to perform reusable, programmable, and adaptable wet biochemical computing. PMID:23514238

Banda, Peter; Teuscher, Christof; Lakin, Matthew R

2013-01-01

128

Parameter estimation in space systems using recurrent neural networks  

Science.gov (United States)

The identification of time-varying parameters encountered in space systems is addressed, using artificial neural systems. A hybrid feedforward/feedback neural network, namely a recurrent multilayer perception, is used as the model structure in the nonlinear system identification. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard back-propagation-learning algorithm is modified and it is used for both the off-line and on-line supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying parameters of nonlinear dynamic systems is investigated by estimating the mass properties of a representative large spacecraft. The changes in the spacecraft inertia are predicted using a trained neural network, during two configurations corresponding to the early and late stages of the spacecraft on-orbit assembly sequence. The proposed on-line mass properties estimation capability offers encouraging results, though, further research is warranted for training and testing the predictive capabilities of these networks beyond nominal spacecraft operations.

Parlos, Alexander G.; Atiya, Amir F.; Sunkel, John W.

1991-01-01

129

Fuzzy and Multilayer Perceptron for Evaluation of HV Bushings  

CERN Document Server

The work proposes the application of fuzzy set theory (FST) to diagnose the condition of high voltage bushings. The diagnosis uses dissolved gas analysis (DGA) data from bushings based on IEC60599 and IEEE C57-104 criteria for oil impregnated paper (OIP) bushings. FST and neural networks are compared in terms of accuracy and computational efficiency. Both FST and NN simulations were able to diagnose the bushings condition with 10% error. By using fuzzy theory, the maintenance department can classify bushings and know the extent of degradation in the component.

Dhlamini, Sizwe M; Majozi, Thokozani

2007-01-01

130

Classification of fused face images using multilayer perceptron neural network  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This paper presents a concept of image pixel fusion of visual and thermal faces, which can significantly improve the overall performance of a face recognition system. Several factors affect face recognition performance including pose variations, facial expression changes, occlusions, and most importantly illumination changes. So, image pixel fusion of thermal and visual images is a solution to overcome the drawbacks present in the individual thermal and visual face images. F...

Bhattacharjee, Debotosh; Bhowmik, Mrinal Kanti; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

2010-01-01

131

Fuzzy and Multilayer Perceptron for Evaluation of HV Bushings  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The work proposes the application of fuzzy set theory (FST) to diagnose the condition of high voltage bushings. The diagnosis uses dissolved gas analysis (DGA) data from bushings based on IEC60599 and IEEE C57-104 criteria for oil impregnated paper (OIP) bushings. FST and neural networks are compared in terms of accuracy and computational efficiency. Both FST and NN simulations were able to diagnose the bushings condition with 10% error. By using fuzzy theory, the maintenanc...

Dhlamini, Sizwe M.; Marwala, Tshilidzi; Majozi, Thokozani

2007-01-01

132

Multilayer Perceptron with Functional Inputs: an Inverse Regression Approach  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Functional data analysis is a growing research field as more and more practical applications involve functional data. In this paper, we focus on the problem of regression and classification with functional predictors: the model suggested combines an efficient dimension reduction procedure [functional sliced inverse regression, first introduced by Ferr\\'e & Yao (Statistics, 37, 2003, 475)], for which we give a regularized version, with the accuracy of a neural network. Some c...

Ferre?, Louis; Villa, Nathalie

2007-01-01

133

Multilayer Perceptron with Functional Inputs: an Inverse Regression Approach  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Abstract. Functional data analysis is a growing research field as more and more practical applications involve functional data. In this paper, we focus on the problem of regression and classification with functional predictors: the model suggested combines an efficient dimension reduction procedure [functional sliced inverse regression, first introduced by Ferré & Yao (Statistics, 37, 2003, 475)], for which we give a regularized version, with the accuracy of a neural network. Some consistenc...

Ferre?, Louis; Villa, Nathalie

2006-01-01

134

On Clifford neurons and Clifford multi-layer perceptrons.  

Science.gov (United States)

We study the framework of Clifford algebra for the design of neural architectures capable of processing different geometric entities. The benefits of this model-based computation over standard real-valued networks are demonstrated. One particular example thereof is the new class of so-called Spinor Clifford neurons. The paper provides a sound theoretical basis to Clifford neural computation. For that purpose the new concepts of isomorphic neurons and isomorphic representations are introduced. A unified training rule for Clifford MLPs is also provided. The topic of activation functions for Clifford MLPs is discussed in detail for all two-dimensional Clifford algebras for the first time. PMID:18514482

Buchholz, Sven; Sommer, Gerald

2008-09-01

135

The Normalized Radial Basis Function Neural Network and its Relation to the Perceptron  

CERN Document Server

The normalized radial basis function neural network emerges in the statistical modeling of natural laws that relate components of multivariate data. The modeling is based on the kernel estimator of the joint probability density function pertaining to given data. From this function a governing law is extracted by the conditional average estimator. The corresponding nonparametric regression represents a normalized radial basis function neural network and can be related with the multi-layer perceptron equation. In this article an exact equivalence of both paradigms is demonstrated for a one-dimensional case with symmetric triangular basis functions. The transformation provides for a simple interpretation of perceptron parameters in terms of statistical samples of multivariate data.

Grabec, I

2007-01-01

136

Parallel strategy for optimal learning in perceptrons  

International Nuclear Information System (INIS)

We developed a parallel strategy for learning optimally specific realizable rules by perceptrons, in an online learning scenario. Our result is a generalization of the Caticha-Kinouchi (CK) algorithm developed for learning a perceptron with a synaptic vector drawn from a uniform distribution over the N-dimensional sphere, so called the typical case. Our method outperforms the CK algorithm in almost all possible situations, failing only in a denumerable set of cases. The algorithm is optimal in the sense that it saturates Bayesian bounds when it succeeds.

2010-03-26

137

Recurrent neural networks with composite features for detection of electrocardiographic changes in partial epileptic patients.  

Science.gov (United States)

The aim of this study is to evaluate the diagnostic accuracy of the recurrent neural networks (RNNs) with composite features (wavelet coefficients and Lyapunov exponents) on the electrocardiogram (ECG) signals. Two types of ECG beats (normal and partial epilepsy) were obtained from the MIT-BIH database. The multilayer perceptron neural networks (MLPNNs) were also tested and benchmarked for their performance on the classification of the ECG signals. Decision making was performed in two stages: computing composite features which were then input into the classifiers and classification using the classifiers trained with the Levenberg-Marquardt algorithm. The research demonstrated that the wavelet coefficients and the Lyapunov exponents are the features which well represent the ECG signals and the RNN trained on these features achieved high classification accuracies. PMID:18275945

Ubeyli, Elif Derya

2008-03-01

138

Landscape statistics of the binary perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The landscape of the binary perceptron is studied by Simulated Annealing, exhaustive search and performing random walks on the landscape. We find that the number of local minima increases exponentially with the number of bonds, becoming deeper in the vicinity of a global minimum, but more and more shallow as we move away from it. The random walker detects a simple dependence on the size of the mapping, the architecture introducing a nontrivial dependence on the number of steps.

Fontanari, J. F.; Ko?berle, R.

1990-01-01

139

On-line learning through simple perceptron with a margin  

CERN Document Server

We analyze a learning method that uses a margin $\\kappa$ {\\it a la} Gardner for simple perceptron learning. This method corresponds to the perceptron learning when $\\kappa=0$, and to the Hebbian learning when $\\kappa \\to \\infty$. Nevertheless, we found that the generalization ability of the method was superior to that of the perceptron and the Hebbian methods at an early stage of learning. We analyzed the asymptotic property of the learning curve of this method through computer simulation and found that it was the same as for perceptron learning. We also investigated an adaptive margin control method.

Hara, K; Hara, Kazuyuki; Okada, Masato

2003-01-01

140

Learning from correlated patterns by simple perceptrons  

Science.gov (United States)

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance.

Shinzato, Takashi; Kabashima, Yoshiyuki

2009-01-01

 
 
 
 
141

Learning from correlated patterns by simple perceptrons  

Energy Technology Data Exchange (ETDEWEB)

Learning behavior of simple perceptrons is analyzed for a teacher-student scenario in which output labels are provided by a teacher network for a set of possibly correlated input patterns, and such that the teacher and student networks are of the same type. Our main concern is the effect of statistical correlations among the input patterns on learning performance. For this purpose, we extend to the teacher-student scenario a methodology for analyzing randomly labeled patterns recently developed in Shinzato and Kabashima 2008 J. Phys. A: Math. Theor. 41 324013. This methodology is used for analyzing situations in which orthogonality of the input patterns is enhanced in order to optimize the learning performance.

Shinzato, Takashi; Kabashima, Yoshiyuki [Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 226-8502 (Japan)], E-mail: shinzato@sp.dis.titech.ac.jp, E-mail: kaba@dis.titech.ac.jp

2009-01-09

142

On-line learning and generalization in coupled perceptrons  

Science.gov (United States)

We study supervised learning and generalization in coupled perceptrons trained on-line using two learning scenarios. In the first scenario the teacher and the student are independent networks and both are represented by an Ashkin-Teller perceptron. In the second scenario the student and the teacher are simple perceptrons but are coupled by an Ashkin-Teller-type four-neuron interaction term. Expressions for the generalization error and the learning curves are derived for various learning algorithms. The analytical results find excellent confirmation in numerical simulations.

Bollé, D.; Kozlowski, P.

2002-03-01

143

On-line learning and generalisation in coupled perceptrons  

CERN Document Server

We study supervised learning and generalisation in coupled perceptrons trained on-line using two learning scenarios. In the first scenario the teacher and the student are independent networks and both are represented by an Ashkin-Teller perceptron. In the second scenario the student and the teacher are simple perceptrons but are coupled by an Ashkin-Teller type four-neuron interaction term. Expressions for the generalisation error and the learning curves are derived for various learning algorithms. The analytic results find excellent confirmation in numerical simulations.

Bollé, D

2002-01-01

144

Chaotic diagonal recurrent neural network  

International Nuclear Information System (INIS)

We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

2012-03-01

145

Generalization ability of a multilayer neural network  

CERN Document Server

We investigate the generalization ability of a perceptron with non-monotonic transfer function of a reversed-wedge type in on-line mode. This network is identical to a parity machine, a multilayer network. We consider several learning algorithms. By the perceptron algorithm the generalization error is shown to decrease by the ${\\alpha}^{-1/3}$-law similarly to the case of a simple perceptron in a restricted range of the parameter $a$ characterizing the non-monotonic transfer function. For other values of $a$, the perceptron algorithm leads to the state where the weight vector of the student is just opposite to that of the teacher. The Hebbian learning algorithm has a similar property; it works only in a limited range of the parameter. The conventional AdaTron algorithm does not give a vanishing generalization error for any values of $a$. We thus introduce a modified AdaTron algorithm which yields a good performance for all values of $a$. We also investigate the effects of optimization of the learning rate as ...

Inoue, J; Kabashima, Yoshiyuki; Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki

1998-01-01

146

Optimal properties of analog perceptrons with excitatory weights.  

Science.gov (United States)

The cerebellum is a brain structure which has been traditionally devoted to supervised learning. According to this theory, plasticity at the Parallel Fiber (PF) to Purkinje Cell (PC) synapses is guided by the Climbing fibers (CF), which encode an 'error signal'. Purkinje cells have thus been modeled as perceptrons, learning input/output binary associations. At maximal capacity, a perceptron with excitatory weights expresses a large fraction of zero-weight synapses, in agreement with experimental findings. However, numerous experiments indicate that the firing rate of Purkinje cells varies in an analog, not binary, manner. In this paper, we study the perceptron with analog inputs and outputs. We show that the optimal input has a sparse binary distribution, in good agreement with the burst firing of the Granule cells. In addition, we show that the weight distribution consists of a large fraction of silent synapses, as in previously studied binary perceptron models, and as seen experimentally. PMID:23436991

Clopath, Claudia; Brunel, Nicolas

2013-01-01

147

The Perceptron Algorithm: Image and Signal Decomposition, Compression, and Analysis by Iterative Gaussian Blurring  

CERN Document Server

A novel algorithm for tunable compression to within the precision of reproduction targets, or storage, is proposed. The new algorithm is termed the `Perceptron Algorithm', which utilises simple existing concepts in a novel way, has multiple immediate commercial application aspects as well as it opens up a multitude of fronts in computational science and technology. The aims of this paper are to present the concepts underlying the algorithm, observations by its application to some example cases, and the identification of a multitude of potential areas of applications such as: image compression by orders of magnitude, signal compression including sound as well, image analysis in a multilayered detailed analysis, pattern recognition and matching and rapid database searching (e.g. face recognition), motion analysis, biomedical applications e.g. in MRI and CAT scan image analysis and compression, as well as hints on the link of these ideas to the way how biological memory might work leading to new points of view i...

Vassiliadis, V S

2006-01-01

148

Adaptation to the optimal learning rate in simple perceptron dynamics  

Science.gov (United States)

A simple perceptron has an optimal learning rate for a given set of patterns. Beyond the optimal learning rate, the error dynamics oscillates and becomes divergent at a critical value, the edge of learning. We study systems with low-pass filtered feedback from the dynamics of the neurons to their learning rate. We find that these adapt to the edge of learning, whereas perceptrons with randomized low-pass-filtered feedback adapt to the optimal learning rate. We discuss potential implementations.

Fleck, Peter; Hubler, Alfred

2004-03-01

149

Training a perceptron in a discrete weight space  

Digital Repository Infrastructure Vision for European Research (DRIVER)

On-line and batch learning of a perceptron in a discrete weight space, where each weight can take $2 L+1$ different values, are examined analytically and numerically. The learning algorithm is based on the training of the continuous perceptron and prediction following the clipped weights. The learning is described by a new set of order parameters, composed of the overlaps between the teacher and the continuous/clipped students. Different scenarios are examined among them on-...

Rosen-zvi, Michal; Kanter, Ido

2001-01-01

150

Learning strategies for the maximally stable diluted binary perceptron  

Science.gov (United States)

I show analytically that an optimally chosen continuous precursor J in the hypercube is highly correlated to the maximally stable diluted binary perceptron which solves the same storage problem. J allows the construction of a diluted binary perceptron D by a simple rule. Performing simulations for perceptrons of size N=100 I demonstrate that D is highly stable and can be improved in an efficient manner by partial enumeration thereby incorporating information from the precursor components. The precursor highlights the vector components on which partial enumeration improves the stability of the vector most efficiently. Moreover, it discriminates for each vector component i at least one of the three possible values Di=\\{-1,0,1\\} as being extremely unlikely.

Malzahn, D.

2000-06-01

151

A Simple Perceptron that Learns Non-Monotonic Rules  

CERN Multimedia

We investigate the generalization ability of a simple perceptron trained in the off-line and on-line supervised modes. Examples are extracted from the teacher who is a non-monotonic perceptron. For this system, difficulties of training can be controlled continuously by changing a parameter of the teacher. We train the student by several learning strategies in order to obtain the theoretical lower bounds of generalization errors under various conditions. Asymptotic behavior of the learning curve has been derived, which enables us to determine the most suitable learning algorithm for a given value of the parameter controlling difficulties of training.

Inoue, J; Kabashima, Yoshiyuki; Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki

1997-01-01

152

Estimativa do perfil da concentração de clorofila em águas naturais através de um perceptron de múltiplas camadas  

Scientific Electronic Library Online (English)

Full Text Available SciELO Brazil | Language: Portuguese Abstract in portuguese Estimativa do perfil de concentração de clorofila, em águas naturais, a partir da radiação emergente na superfície de um corpo d'agua, com o uso de rede neural artificial do tipo Perceptron de Múltiplas Camadas. A concentração de clorofila está relacionada com os coeficientes de absorção e espalhame [...] nto via modelos bio-ópticos. O treinamento da rede é formulado como um problema de otimização, no qual a atualização das variáveis livres da rede (pesos, viés e parâmetros de cada função de ativação) é feita através do método quasi-Newton. Abstract in english In this work the average profile of chlorophyll concentration is estimated from the emitted radiation at the surface of natural waters. This is performed through the use an Artificial Neural Network of Multilayer Perceptron type to act as the inverse operator. Bio-optical models are used to correlat [...] e the chlorophyll concentration with the absorption and scattering coefficients. The network training is formulated as an optimization problem, in which the update of the free variables of network (weights, viéses and each slope of the activation functions) is performed through the quasi-Newton method.

Dall Cortivo, F.; Chalhoub, E. S.; Campos Velho, H. F..

153

Higher-order probabilistic perceptrons as Bayesian inference engines  

International Nuclear Information System (INIS)

This letter makes explicit a structural connection between the Bayes optimal classifier operating on K binary input variables and corresponding two-layer perceptron having normalized output activities and couplings from input to output units of all orders up to K. Given a large and unbiased training set and an effective learning algorithm, such a neural network should be able to learn the statistics of the classification problem and match the a posteriori probabilities given by the Bayes optimal classifier. (author). 18 refs

1994-01-01

154

Learning Kernel Perceptrons on Noisy Data and Random Projections  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classification noise. Our proposed approach relies on the combination of the technique of random or deterministic projections with a classification noise tolerant perceptron learning algorithm that assumes distributions defined over finite-dimensional spaces. Provided a sufficient separation margin characterizes the problem, t...

Stempfel, Guillaume; Ralaivola, Liva

2007-01-01

155

Complex-bilinear recurrent neural network for equalization of a digital satellite channel.  

Science.gov (United States)

Equalization of satellite communication using complex-bilinear recurrent neural network (C-BLRNN) is proposed. Since the BLRNN is based on the bilinear polynomial, it can be used in modeling highly nonlinear systems with time-series characteristics more effectively than multilayer perceptron type neural networks (MLPNN). The BLRNN is first expanded to its complex value version (C-BLRNN) for dealing with the complex input values in the paper. C-BLRNN is then applied to equalization of a digital satellite communication channel for M-PSK and QAM, which has severe nonlinearity with memory due to traveling wave tube amplifier (TWTA). The proposed C-BLRNN equalizer for a channel model is compared with the currently used Volterra filter equalizer or decision feedback equalizer (DFE), and conventional complex-MLPNN equalizer. The results show that the proposed C-BLRNN equalizer gives very favorable results in both the MSE and BER criteria over Volterra filter equalizer, DFE, and complex-MLPNN equalizer. PMID:18244467

Park, Dong-Chul; Jeong, Tae-Kyun Jung

2002-01-01

156

FORECASTING ON FOREX MARKET WITH RBF AND PERCEPTRON NEURAL NETWORKS  

Directory of Open Access Journals (Sweden)

Full Text Available This work deals with an alternative approach in financial modelling -artificial neural networks approach. The aim of this paper is to show that this type oftime series modelling is an excellent alternative to classical econometric modelling. Atfirst, neural networks using methods of supervised machine learning are discussed.After explaining theoretical basis of ANN, these models are then applied to specificexchange rate (AUD/USD. Finally, the comparison between statistical models andRBF and perceptron neural networks is made to illustrate the sense of using ANNmodels

ALEXANDRA KOTTILOVÁ

2012-01-01

157

The cell spectrum of perceptrons with biased patterns  

CERN Document Server

We calculate the multifractal spectrum of the partition of the coupling space of a perceptron induced by random input-output pairs with non-zero mean. From the results we infer the influence of the input and output bias respectively on both the storage and generalization properties of the network. It turns out that the value of the input bias is irrelevant as long as it is different from zero. The generalization problem with output bias is new and shows an interesting two-level scenario. To compare our analytical results with simulations we introduce a simple and efficient algorithm to implement Gibbs learning.

Berg, J

1998-01-01

158

24-hours ahead global irradiation forecasting using Multi-Layer Perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The grid integration of variable renewable energy sources implies that their effective production could be predicted, at different times ahead. In the case of solar plants, the driving factor is the global solar irradiation (sum of direct and diffuse solar radiation projected on a plane (Wh/m²)). This paper focuses on the 24-hours ahead forecast of global solar irradiation (i.e. hourly solar irradiation prediction for the day after). A method based on artificial intelligence using Artificial...

Voyant, Cyril; Randimbivololona, Prisca; Nivet, Marie Laure; Paoli, Christophe; Muselli, Marc

2013-01-01

159

Classification of Polar-Thermal Eigenfaces using Multilayer Perceptron for Human Face Recognition  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This paper presents a novel approach to handle the challenges of face recognition. In this work thermal face images are considered, which minimizes the affect of illumination changes and occlusion due to moustache, beards, adornments etc. The proposed approach registers the training and testing thermal face images in polar coordinate, which is capable to handle complicacies introduced by scaling and rotation. Polar images are projected into eigenspace and finally classified ...

Bhowmik, Mrinal Kanti; Bhattacharjee, Debotosh; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

2010-01-01

160

Multilayer perceptron for simulation models reduction: application to a sawmill workshop  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Simulation is often used to evaluate supply chain or workshop management. This simulation task needs models, which are difficult to construct. The aim of this work is to reduce the complexity of a simulation model design. The proposed approach combines discrete and continuous approaches in order to construct speeder and simpler reduced model. The simulation model focuses on bottlenecks with a discrete approach according to the theory of constraints. The remaining of the workshop must be taken...

Thomas, Philippe; Thomas, Andre?

2011-01-01

 
 
 
 
161

Data Optimization with Multilayer Perceptron Neural Network and Using New Pattern in Decision Tree Comparatively  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Problem statement: The aim of the present study is to exemplify the use of Artificial Neural Networks (ANN) for parameter prediction. Missing value or unreal approach to some questions in scale is a problem for unbiased findings. To learn a real pattern with ANN provides robust and unbiased parameter estimation. Approach: To this end, data was collected from 906 students using ?Scale of student views about the expected situations and the current expectations from their families ...

Murat Kayri; Omay Cokluk

2010-01-01

162

Cross Validation Evaluation for Breast Cancer Prediction Using Multilayer Perceptron Neural Networks  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Problem statement: The presence of metastasis in the regional lymph nodes is the most important factor in predicting prognosis in breast cancer. Many biomarkers have been identified that appear to relate to the aggressive behaviour of cancer. However, the nonlinear relation of these markers to nodal status and also the existence of complex interaction between markers have prohibited an accurate prognosis. Approach: The aim of this study is to investigate the effectiveness of a M...

Mojarad, Shirin A.; Dlay, Satnam S.; Woo, Wai L.; Sherbet, Gajanan V.

2011-01-01

163

Hybrid Optimized Back propagation Learning Algorithm For Multi-layer Perceptron  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Standard neural network based on general back propagation learning using delta method or gradient descent method has some great faults like poor optimization of error-weight objective function, low learning rate, instability .This paper introduces a hybrid supervised back propagation learning algorithm which uses trust-region method of unconstrained optimization of the error objective function by using quasi-newton method .This optimization leads to more accurate weight upda...

Chakraborty, Mriganka; Ghosh, Arka

2012-01-01

164

Gas chimney detection based on improving the performance of combined multilayer perceptron and support vector classifier :  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general applicability, is demonstrated here on a gas chimney detection problem. First, we evaluate a set of i...

Hashemi, H.; Tax, D. M. J.; Duin, R. P. W.; Javaherian, A.; Groot, P.

2008-01-01

165

Gas chimney detection based on improving the performance of combined multilayer perceptron and support vector classifier  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Seismic object detection is a relatively new field in which 3-D bodies are visualized and spatial relationships between objects of different origins are studied in order to extract geologic information. In this paper, we propose a method for finding an optimal classifier with the help of a statistical feature ranking technique and combining different classifiers. The method, which has general applicability, is demonstrated here on a gas chimney detection problem. First, we evaluate a set of i...

Hashemi, H.; Tax, D. M. J.; Duin, R. P. W.; Javaherian, A.; Groot, P.

2008-01-01

166

Electron/pion identification in the CBM TRD using a multilayer perceptron  

International Nuclear Information System (INIS)

The problem of electron/pion identification in the CBM experiment based on the measurements of energy losses and transition radiation in the TRD detector is discussed. A possibility to solve such a problem by applying an artificial neural network (ANN) is considered. As input information for the network we used both the samples of energy losses of pions or electrons in the TRD absorbers and the 'clever' variable obtained on the basis of the original data. We show that usage of this new variable permits one to reach a reliable level of particle recognition no longer than after 10-20 training epochs; there are practically no fluctuations against the trend, and the needed level of pions suppression is obtained under the condition of a minimal loss of electrons

2008-01-01

167

Systematic Learning of Gene Functional Classes From DNA Array Expression Data by Using Multilayer Perceptrons  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Recent advances in microarray technology have opened new ways for functional annotation of previously uncharacterised genes on a genomic scale. This has been demonstrated by unsupervised clustering of co-expressed genes and, more importantly, by supervised learning algorithms. Using prior knowledge, these algorithms can assign functional annotations based on more complex expression signatures found in existing functional classes. Previously, support vector machines (SVMs) and other machine-le...

Mateos, Alvaro; Dopazo, Joaqui?n; Jansen, Ronald; Tu, Yuhai; Gerstein, Mark; Stolovitzky, Gustavo

2002-01-01

168

Analysis of Ensemble Learning Using SimplePerceptrons Based on Online Learning Theory  

Science.gov (United States)

Ensemble learning of K simple perceptrons,which determine their outputs by sign functions, is discussed within the framework of online learning and statistical mechanics. Hebbian, perceptron and AdaTron learning show different characteristics in their affinity for ensemble learning, that is ``maintaining variety among students". Results show that AdaTron learning is superior to the other two rules.

Miyoshi, S.; Hara, K.; Okada, M.

169

Training a perceptron in a discrete weight space  

CERN Multimedia

On-line and batch learning of a perceptron in a discrete weight space, where each weight can take $2 L+1$ different values, are examined analytically and numerically. The learning algorithm is based on the training of the continuous perceptron and prediction following the clipped weights. The learning is described by a new set of order parameters, composed of the overlaps between the teacher and the continuous/clipped students. Different scenarios are examined among them on-line learning with discrete/continuous transfer functions and off-line Hebb learning. The generalization error of the clipped weights decays asymptotically as $exp(-K \\alpha^2)$/$exp(-e^{|\\lambda| \\alpha})$ in the case of on-line learning with binary/continuous activation functions, respectively, where $\\alpha$ is the number of examples divided by N, the size of the input vector and $K$ is a positive constant that decays linearly with 1/L. For finite $N$ and $L$, a perfect agreement between the discrete student and the teacher is obtained ...

Rosen-Zvi, M; Rosen-Zvi, Michal; Kanter, Ido

2001-01-01

170

On-line learning of non-monotonic rules by simple perceptron  

CERN Document Server

We study the generalization ability of a simple perceptron which learns unlearnable rules. The rules are presented by a teacher perceptron with a non-monotonic transfer function. The student is trained in the on-line mode. The asymptotic behaviour of the generalization error is estimated under various conditions. Several learning strategies are proposed and improved to obtain the theoretical lower bound of the generalization error.

Inoue, J; Kabashima, Yoshiyuki; Inoue, Jun-ichi; Nishimori, Hidetoshi; Kabashima, Yoshiyuki

1997-01-01

171

Statistical Mechanical Analysis of the Dynamics of Learning in Perceptrons  

CERN Document Server

We describe the application of tools from statistical mechanics to analyse the dynamics of various classes of supervised learning rules in perceptrons. The character of this paper is mostly that of a cross between a biased non-encyclopedic review and lecture notes: we try to present a coherent and self-contained picture of the basics of this field, to explain the ideas and tricks, to show how the predictions of the theory compare with (simulation) experiments, and to bring together scattered results. Technical details are given explicitly in an appendix. In order to avoid distraction we concentrate the references in a final section. In addition this paper contains some new results: (i) explicit solutions of the macroscopic equations that describe the error evolution for on-line and batch learning rules, (ii) an analysis of the dynamics of arbitrary macroscopic observables (for complete and incomplete trainingsets), leading to a general Fokker-Planck equation, and (iii) the macroscopic laws describing batch le...

Mace, C W H

1997-01-01

172

Perfect transmission and highly asymmetric light localization in photonic multilayers  

Digital Repository Infrastructure Vision for European Research (DRIVER)

General principles for the existence of perfect transmission resonances in photonic multilayer structures are formulated in terms of light interference described by recurrent Airy formulas. Mirror symmetry in the multilayer is shown to be a sufficient but not necessary condition for perfect transmission resonances. Asymmetric structures displaying perfect transmission in accordance with the proposed principles are demonstrated. A hybrid Fabry-Perot/photonic-crystal structure...

Zhukovsky, Sergei V.

2009-01-01

173

Noise-enhanced categorization in a recurrently reconnected neural network  

Science.gov (United States)

We investigate the interplay of recurrence and noise in neural networks trained to categorize spatial patterns of neural activity. We develop the following procedure to demonstrate how, in the presence of noise, the introduction of recurrence permits to significantly extend and homogenize the operating range of a feed-forward neural network. We first train a two-level perceptron in the absence of noise. Following training, we identify the input and output units of the feed-forward network, and thus convert it into a two-layer recurrent network. We show that the performance of the reconnected network has features reminiscent of nondynamic stochastic resonance: the addition of noise enables the network to correctly categorize stimuli of subthreshold strength, with optimal noise magnitude significantly exceeding the stimulus strength. We characterize the dynamics leading to this effect and contrast it to the behavior of a more simple associative memory network in which noise-mediated categorization fails.

Monterola, Christopher; Zapotocky, Martin

2005-03-01

174

Noise-enhanced categorization in a recurrently reconnected neural network  

International Nuclear Information System (INIS)

We investigate the interplay of recurrence and noise in neural networks trained to categorize spatial patterns of neural activity. We develop the following procedure to demonstrate how, in the presence of noise, the introduction of recurrence permits to significantly extend and homogenize the operating range of a feed-forward neural network. We first train a two-level perceptron in the absence of noise. Following training, we identify the input and output units of the feed-forward network, and thus convert it into a two-layer recurrent network. We show that the performance of the reconnected network has features reminiscent of nondynamic stochastic resonance: the addition of noise enables the network to correctly categorize stimuli of subthreshold strength, with optimal noise magnitude significantly exceeding the stimulus strength. We characterize the dynamics leading to this effect and contrast it to the behavior of a more simple associative memory network in which noise-mediated categorization fails

2005-03-01

175

Can Perceptrons Find Lyapunov Functions: An Algorithmic Approach to Systems Stability.  

Science.gov (United States)

The problem of finding a Lyapunov function using a simple neural network is discussed. The Rosenblatt single layer perceptron is used for this purpose. It is shown that the problem can be cast in a form suitable for solution. The importance of such a comp...

S. P. Banks R. F. Harrison

1989-01-01

176

How to guess the inter magnetic bubble potential by using a simple perceptron ?  

CERN Document Server

It is shown that magnetic bubble films behaviour can be described by using a 2D super-Ising hamiltonian. Calculated hysteresis curves and magnetic domain patterns are successfully compared with experimental results taken in literature. The reciprocal problem of finding paramaters of the super-Ising model to reproduce computed or experimental magnetic domain pictures is solved by using a perceptron neural network.

Padovani, S

2004-01-01

177

Gas Sensors Characterization and Multilayer Perceptron (MLP) Hardware Implementation for Gas Identification Using a Field Programmable Gate Array (FPGA)  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This paper develops a primitive gas recognition system for discriminating between industrial gas species. The system under investigation consists of an array of eight micro-hotplate-based SnO2 thin film gas sensors with different selectivity patterns. The output signals are processed through a signal conditioning and analyzing system. These signals feed a decision-making classifier, which is obtained via a Field Programmable Gate Array (FPGA) with Very High-Speed Integrated Circuit Hardware D...

Benrekia, Fayc?al; Attari, Mokhtar; Bouhedda, Mounir

2013-01-01

178

Analysis of ensemble learning using simple perceptrons based on online learning theory  

CERN Document Server

Ensemble learning of $K$ nonlinear perceptrons, which determine their outputs by sign functions, is discussed within the framework of online learning and statistical mechanics. One purpose of statistical learning theory is to theoretically obtain the generalization error. This paper shows that ensemble generalization error can be calculated by using two order parameters, that is, the similarity between a teacher and a student, and the similarity among students. The differential equations that describe the dynamical behaviors of these order parameters are derived in the case of general learning rules. The concrete forms of these differential equations are derived analytically in the cases of three well-known rules: Hebbian learning, perceptron learning and AdaTron learning. Ensemble generalization errors of these three rules are calculated by using the results determined by solving their differential equations. As a result, these three rules show different characteristics in their affinity for ensemble learnin...

Okada, S M K H M

2004-01-01

179

Training an asymmetric signal perceptron through reinforcement in an artificial chemistry.  

Science.gov (United States)

State-of-the-art biochemical systems for medical applications and chemical computing are application-specific and cannot be reprogrammed or trained once fabricated. The implementation of adaptive biochemical systems that would offer flexibility through programmability and autonomous adaptation faces major challenges because of the large number of required chemical species as well as the timing-sensitive feedback loops required for learning. In this paper, we begin addressing these challenges with a novel chemical perceptron that can solve all 14 linearly separable logic functions. The system performs asymmetric chemical arithmetic, learns through reinforcement and supports both Michaelis-Menten as well as mass-action kinetics. To enable cascading of the chemical perceptrons, we introduce thresholds that amplify the outputs. The simplicity of our model makes an actual wet implementation, in particular by DNA-strand displacement, possible. PMID:24478284

Banda, Peter; Teuscher, Christof; Stefanovic, Darko

2014-04-01

180

Perceptron learning rule derived from spike-frequency adaptation and spike-time-dependent plasticity  

Digital Repository Infrastructure Vision for European Research (DRIVER)

It is widely believed that sensory and motor processing in the brain is based on simple computational primitives rooted in cellular and synaptic physiology. However, many gaps remain in our understanding of the connections between neural computations and biophysical properties of neurons. Here, we show that synaptic spike-time-dependent plasticity (STDP) combined with spike-frequency adaptation (SFA) in a single neuron together approximate the well-known perceptron learning rule. Our calculat...

D’souza, Prashanth; Liu, Shih-chii; Hahnloser, Richard H. R.

2010-01-01

 
 
 
 
181

Learning rate and attractor size of the single-layer perceptron  

International Nuclear Information System (INIS)

We study the simplest possible order one single-layer perceptron with two inputs, using the delta rule with online learning, in order to derive closed form expressions for the mean convergence rates. We investigate the rate of convergence in weight space of the weight vectors corresponding to each of the 14 out of 16 linearly separable rules. These vectors follow zigzagging lines through the piecewise constant vector field to their respective attractors. Based on our studies, we conclude that a single-layer perceptron with N inputs will converge in an average number of steps given by an Nth order polynomial in (t/l), where t is the threshold, and l is the size of the initial weight distribution. Exact values for these averages are provided for the five linearly separable classes with N=2. We also demonstrate that the learning rate is determined by the attractor size, and that the attractors of a single-layer perceptron with N inputs partition RN+RN

2007-02-01

182

Time-scale invariance as an emergent property in a perceptron with realistic, noisy neurons.  

Science.gov (United States)

In most species, interval timing is time-scale invariant: errors in time estimation scale up linearly with the estimated duration. In mammals, time-scale invariance is ubiquitous over behavioral, lesion, and pharmacological manipulations. For example, dopaminergic drugs induce an immediate, whereas cholinergic drugs induce a gradual, scalar change in timing. Behavioral theories posit that time-scale invariance derives from particular computations, rules, or coding schemes. In contrast, we discuss a simple neural circuit, the perceptron, whose output neurons fire in a clockwise fashion based on the pattern of coincidental activation of its input neurons. We show numerically that time-scale invariance emerges spontaneously in a perceptron with realistic neurons, in the presence of noise. Under the assumption that dopaminergic drugs modulate the firing of input neurons, and that cholinergic drugs modulate the memory representation of the criterion time, we show that a perceptron with realistic neurons reproduces the pharmacological clock and memory patterns, and their time-scale invariance, in the presence of noise. These results suggest that rather than being a signature of higher order cognitive processes or specific computations related to timing, time-scale invariance may spontaneously emerge in a massively connected brain from the intrinsic noise of neurons and circuits, thus providing the simplest explanation for the ubiquity of scale invariance of interval timing. PMID:23518297

Buhusi, Catalin V; Oprisan, Sorinel A

2013-05-01

183

Analysis of ensemble learning using simple perceptrons based on online learning theory  

Science.gov (United States)

Ensemble learning of K nonlinear perceptrons, which determine their outputs by sign functions, is discussed within the framework of online learning and statistical mechanics. One purpose of statistical learning theory is to theoretically obtain the generalization error. This paper shows that ensemble generalization error can be calculated by using two order parameters, that is, the similarity between a teacher and a student, and the similarity among students. The differential equations that describe the dynamical behaviors of these order parameters are derived in the case of general learning rules. The concrete forms of these differential equations are derived analytically in the cases of three well-known rules: Hebbian learning, perceptron learning, and AdaTron (adaptive perceptron) learning. Ensemble generalization errors of these three rules are calculated by using the results determined by solving their differential equations. As a result, these three rules show different characteristics in their affinity for ensemble learning, that is “maintaining variety among students.” Results show that AdaTron learning is superior to the other two rules with respect to that affinity.

Miyoshi, Seiji; Hara, Kazuyuki; Okada, Masato

2005-03-01

184

Energy complexity of recurrent neural networks.  

Science.gov (United States)

Recently a new so-called energy complexity measure has been introduced and studied for feedforward perceptron networks. This measure is inspired by the fact that biological neurons require more energy to transmit a spike than not to fire, and the activity of neurons in the brain is quite sparse, with only about 1% of neurons firing. In this letter, we investigate the energy complexity of recurrent networks, which counts the number of active neurons at any time instant of a computation. We prove that any deterministic finite automaton with m states can be simulated by a neural network of optimal size [Formula: see text] with the time overhead of [Formula: see text] per one input bit, using the energy O(e), for any e such that [Formula: see text] and e=O(s), which shows the time-energy trade-off in recurrent networks. In addition, for the time overhead [Formula: see text] satisfying [Formula: see text], we obtain the lower bound of [Formula: see text] on the energy of such a simulation for some constant c>0 and for infinitely many s. PMID:24555455

Síma, Ji?í

2014-05-01

185

Multilayer dielectric diffraction gratings  

Energy Technology Data Exchange (ETDEWEB)

The design and fabrication of dielectric grating structures with high diffraction efficiency used in reflection or transmission is described. By forming a multilayer structure of alternating index dielectric materials and placing a grating structure on top of the multilayer, a diffraction grating of adjustable efficiency, and variable optical bandwidth can be obtained. Diffraction efficiency into the first order in reflection varying between 1 and 98 percent has been achieved by controlling the design of the multilayer and the depth, shape, and material comprising the grooves of the grating structure. Methods for fabricating these gratings without the use of ion etching techniques are described.

Perry, Michael D. (Livermore, CA); Britten, Jerald A. (Oakley, CA); Nguyen, Hoang T. (Livermore, CA); Boyd, Robert (Livermore, CA); Shore, Bruce W. (Livermore, CA)

1999-01-01

186

Receiver operating characteristics of perceptrons: Influence of sample size and prevalence  

Science.gov (United States)

In many practical classification problems it is important to distinguish false positive from false negative results when evaluating the performance of the classifier. This is of particular importance for medical diagnostic tests. In this context, receiver operating characteristic (ROC) curves have become a standard tool. Here we apply this concept to characterize the performance of a simple neural network. Investigating the binary classification of a perceptron we calculate analytically the shape of the corresponding ROC curves. The influence of the size of the training set and the prevalence of the quality considered are studied by means of a statistical-mechanics analysis.

Freking, Ansgar; Biehl, Michael; Braun, Christian; Kinzel, Wolfgang; Meesmann, Malte

1999-11-01

187

Idiopathic, Recurrent Cholestasis.  

Science.gov (United States)

Idiopathic, recurrent cholestasis is characterized by episodes of obstructive jaundice often preceded by pruritus, steatorrhea, and purpuric rash. Between episodes of jaundice the liver histology is normal. We report a case of idiopathic, recurrent choles...

F. B. Ruymann A. Takeuchi H. W. Boyce

1969-01-01

188

Recurrent aphthous stomatitis  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Recurrent aphthous ulcers are common painful mucosal conditions affecting the oral cavity. Despite their high prevalence, etiopathogenesis remains unclear. This review article summarizes the clinical presentation, diagnostic criteria, and recent trends in the management of recurrent apthous stomatitis.

Preeti, L.; Magesh, Kt; Rajkumar, K.; Karthik, Raghavendhar

2011-01-01

189

Advances in Artificial Neural Networks – Methodological Development and Application  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other networks such as radial basis function, recurrent network, feedback network, and unsupervised Kohonen self-organizing network. These networks, especially the multilayer perceptron network with a back...

Yanbo Huang

2009-01-01

190

Recurrent Linear Operators  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We study the notion of recurrence and some of its variations for linear operators acting on Banach spaces. We characterize recurrence for several classes of linear operators such as weighted shifts, composition operators and multiplication operators on classical Banach spaces. We show that on separable complex Hilbert spaces the study of recurrent operators reduces, in many cases, to the study of unitary operators. Finally, we study the notion of product recurrence and state...

Costakis, George; Manoussos, Antonios; Parissis, Ioannis

2013-01-01

191

Diffusion in multilayers  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Diffusion experiments are usually performed at macroscopic length scales, use of multilayers can lower these scale down to the nanometer range. This paper describes the main idea governing atomic transport at such short distance and in such inhomogeneous systems. The basic experimental methods involved are also discussed. Some representative recent works are shortly described.

Piecuch, M.

1988-01-01

192

Recurrent zosteriform herpes simplex  

Directory of Open Access Journals (Sweden)

Full Text Available A 25-year-old man had recurrent zosteriform herpes simplex for past 6 years. The attacks were precipitated by prolonged exposure to sunlight. Pain was mild and lesions used to subside each time in about 7 days. Clinical features which help in differentiating recurrent herpes simplex from recurrent herpes zoster are summarized.

Inamadar Arun

1992-01-01

193

Recurrent Education in Yugoslavia.  

Science.gov (United States)

These seven papers offer an insight into the different aspects of recurrent education in Yugoslavia. "Recurrent Education and Educational Changes" considers these three processes: the "de-etatization," the democratization, and the de-schooling of education. "The Unity of Education and Work and Recurrent Education" proposes that this unity implies…

Soljan, Niksa Nikola, Ed.

194

Core reactivity estimation in space reactors using recurrent dynamic networks  

International Nuclear Information System (INIS)

A recurrent Multi Layer Perceptron (MLP) network topology is used in the identification of nonlinear dynamic systems from only the input/output measurements. This effort is part of a research program devoted in developing real-time diagnostics and predictive control techniques for large-scale complex nonlinear dynamic systems. The identification is performed in the discrete time domain, with the learning algorithm being a modified form of the Back Propagation (BP) rule. The Recurrent Dynamic Network (RDN) developed is applied for the total core reactivity prediction of a spacecraft reactor from only neutronic power level measurements. Results indicate that the RDN can reproduce the nonlinear response of the reactor while keeping the number of nodes roughly equal to the relative order of the system. As accuracy requirements are increased, the number of required nodes also increases, however, the order of the RDN necessary to obtain such results is still in the same order of magnitude as the order of the matematical model of the system. There are a number of issues identified regarding the behavior of the RDN, which at this point are unresolved and require further research. Nevertheless, it is believed that use of the recurrent MLP structure with a variety of different learning algorithms may prove useful in utilizing artifical neural networks (ANNs) for recognition, classification and prediction of dynamic systems

1991-01-10

195

Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels  

CERN Document Server

A framework to analyze inference performance in densely connected single-layer feed-forward networks is developed for situations where a given data set is composed of correlated patterns. The framework is based on the assumption that the left and right singular value bases of the given pattern matrix are generated independently and uniformly from Haar measures. This assumption makes it possible to characterize the objective system by a single function of two variables which is determined by the eigenvalue spectrum of the cross-correlation matrix of the pattern matrix. Links to existing methods for analysis of perceptron learning and Gaussian linear vector channels and an application to a simple but nontrivial problem are also shown.

Kabashima, Yoshiyuki

2007-01-01

196

Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels  

Energy Technology Data Exchange (ETDEWEB)

A framework to analyze inference performance in densely connected single-layer feed-forward networks is developed for situations where a given data set is composed of correlated patterns. The framework is based on the assumption that the left and right singular value bases of the given pattern matrix are generated independently and uniformly from Haar measures. This assumption makes it possible to characterize the objective system by a single function of two variables which is determined by the eigenvalue spectrum of the cross-correlation matrix of the pattern matrix. Links to existing methods for analysis of perceptron learning and Gaussian linear vector channels and an application to a simple but nontrivial problem are also shown.

Kabashima, Y [Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama 226-8502 (Japan)], E-mail: kaba@dis.titech.ac.jp

2008-01-15

197

Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels  

Science.gov (United States)

A framework to analyze inference performance in densely connected single-layer feed-forward networks is developed for situations where a given data set is composed of correlated patterns. The framework is based on the assumption that the left and right singular value bases of the given pattern matrix are generated independently and uniformly from Haar measures. This assumption makes it possible to characterize the objective system by a single function of two variables which is determined by the eigenvalue spectrum of the cross-correlation matrix of the pattern matrix. Links to existing methods for analysis of perceptron learning and Gaussian linear vector channels and an application to a simple but nontrivial problem are also shown.

Kabashima, Y.

2008-01-01

198

Generalizing with perceptrons in case of structured phase- and pattern-spaces  

CERN Multimedia

We investigate the influence of different kinds of structure on the learning behaviour of a perceptron performing a classification task defined by a teacher rule. The underlying pattern distribution is permitted to have spatial correlations. The prior distribution for the teacher coupling vectors itself is assumed to be nonuniform. Thus classification tasks of quite different difficulty are included. As learning algorithms we discuss Hebbian learning, Gibbs learning, and Bayesian learning with different priors, using methods from statistics and the replica formalism. We find that the Hebb rule is quite sensitive to the structure of the actual learning problem, failing asymptotically in most cases. Contrarily, the behaviour of the more sophisticated methods of Gibbs and Bayes learning is influenced by the spatial correlations only in an intermediate regime of $\\alpha$, where $\\alpha$ specifies the size of the training set. Concerning the Bayesian case we show, how enhanced prior knowledge improves the performa...

Dirscherl, G; Krey, U

1998-01-01

199

Inference from correlated patterns: a unified theory for perceptron learning and linear vector channels  

International Nuclear Information System (INIS)

A framework to analyze inference performance in densely connected single-layer feed-forward networks is developed for situations where a given data set is composed of correlated patterns. The framework is based on the assumption that the left and right singular value bases of the given pattern matrix are generated independently and uniformly from Haar measures. This assumption makes it possible to characterize the objective system by a single function of two variables which is determined by the eigenvalue spectrum of the cross-correlation matrix of the pattern matrix. Links to existing methods for analysis of perceptron learning and Gaussian linear vector channels and an application to a simple but nontrivial problem are also shown

2008-01-01

200

Imaging recurrent parosteal osteosarcoma  

International Nuclear Information System (INIS)

The aim of this study was to document the imaging features of recurrent parosteal osteosarcoma. The clinical and imaging records of 33 patients with a parosteal osteosarcoma referred to an orthopaedic oncology service over a 17-year period were retrospectively reviewed. The mode of identification of locally recurrent tumour was noted, together with the management and clinical outcome. Five patients developed a local recurrence of their parosteal osteosarcoma ranging from 6 months to 10 years after initial surgery. In 4 patients the recurrence was first suspected clinically due to the development of a mass. In the fifth patient recurrence was first detected on routine follow-up radiography. In 4 patients the recurrence could be identified on radiography as a mineralized mass. All the recurrences were readily identified on MR imaging, despite artefacts from prostheses. The recurrences were also evident in the 3 cases in which bone scintigraphy was performed. Local recurrence of parosteal osteosarcoma is adequately detected with a combination of clinical examination and conventional radiography. MR imaging is required to stage local recurrence or where radiography has failed to confirm clinically suspected recurrence. The routine use of MR imaging to follow-up patients is of doubtful value because of the frequently long time between initial surgery and relapse. (orig.)

2001-03-01

 
 
 
 
201

Porous germanium multilayers  

Energy Technology Data Exchange (ETDEWEB)

We present the reproducible fabrication of porous germanium (PGe) single- and multilayers. Mesoporous layers form on heavily doped 4'' p-type Ge wafers by electrochemical etching in highly concentrated HF-based electrolytes with concentrations in a range of 30-50 wt.%. Direct PGe formation is accompanied by a constant dissolution of the already-formed porous layer at the electrolyte/PGe interface, hence yielding a thinner substrate after etching. This effect inhibits multilayer formation as the starting layer is etched while forming the second layer. We avoid dissolution of the porous layer by alternating the etching bias from anodic to cathodic. PGe formation occurs during anodic etching whereas the cathodic step passivates pore walls with H-atoms and avoids electropolishing. The passivation lasts a limited time depending on the etching current density and electrolyte concentration, necessitating a repetition of the cathodic step at suitable intervals. With optimized alternating bias mesoporous multilayer production is possible. We control the porosity of each single layer by varying the etching current density and the electrolyte (copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Garralaga Rojas, Enrique; Hensen, Jan; Brendel, Rolf [Institut fuer Solarenergieforschung Hameln (ISFH), Emmerthal (Germany); Carstensen, Juergen; Foell, Helmut [Chair for General Materials Science, Faculty of Engineering, Christian-Albrechts-University of Kiel (Germany)

2011-06-15

202

Supratentorial recurrences in medulloblastoma  

Energy Technology Data Exchange (ETDEWEB)

Four children with medulloblastoma had massive supratentorial recurrences in the region of the cribriform plate after adequate craniospinal irradiation. The pathogenesis of these recurrences is probably related to underdosage to this region by shielding of the eyes. This hypothesis was corroborated by autopsy findings in two other patients in whom subfrontal implants were histologically different from recurrences elsewhere. Two possible solutions to avoid this problem in the future are suggested.

Jereb, B.; Sundaresan, N.; Horten, B.; Reid, A.; Galicich, J.H.

1981-02-15

203

Recurrent rheumatic fever.  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Although recurrent rheumatic fever in adults is uncommon and the recurrence rate declines with age and with the interval from the attack, we describe a patient who has had four attacks of rheumatic fever, two in childhood and two in adult life.

Murray, N. H.; Fordham, J. N.; Davies, P. G.; Barnes, C. G.

1985-01-01

204

Recurrent gastric trichobezoar.  

Science.gov (United States)

Trichobezoars are concretions of ingested hair that are found in the stomach. Recurrence of this condition has not been reported. We report an 18-year-old girl with recurrent trichobezoar; this emphasizes the need for counseling in these patients. PMID:12546177

Ratnagiri, Ranganath; Smile, S Robinson; Sistla, Sarath Chandra

2002-01-01

205

Multi-layers castings  

Digital Repository Infrastructure Vision for European Research (DRIVER)

In paper is presented the possibility of making of multi-layers cast steel castings in result of connection of casting and welding coating technologies. First layer was composite surface layer on the basis of Fe-Cr-C alloy, which was put directly in founding process of cast carbon steel 200–450 with use of preparation of mould cavity method. Second layer were padding welds, which were put with use of TIG – Tungsten Inert Gas surfacing by welding technology with filler on Ni matrix, Ni and...

2010-01-01

206

Multilayer graphene waveguides  

CERN Multimedia

We study dispersion properties of TM-polarized electromagnetic waves guided by a multilayer graphene metamaterial. We demonstrate that both dispersion and localization of the guided modes can be efficiently controlled by changing the number of layers in the structure. Remarkably, we find that in the long wavelength limit, the dispersion of the fundamental mode of the N-layer graphene structure coincides with the dispersion of a plasmon mode supported by a single graphene layer, but with N times larger conductivity. We also compare our exact dispersion relations with the results provided by the effective media model.

Smirnova, Daria; Shadrivov, Ilya; Kivshar, Yuri

2014-01-01

207

Recurrent aortoduodenal fistula.  

Science.gov (United States)

Aortoenteric fistula is defined as a communication between the aorta and an adjacent loop of the bowel and is often the cause of devastating upper gastrointestinal tract bleeding with only few survivors. According to the etiology, the aortoenteric fistulas are classified as primary aortoenteric fistula or secondary aortoenteric fistula (SAEF) after previous aortic surgery. The recurrence of a fistula on a previous SAEF is defined as recurrent aortoenteric fistula and is reported only in a few rare cases occurring within an unpredictable period from the previous surgical treatment. We describe a unique case of recurrent aortoenteric fistula, in which the relationship with recurrence consisted of the presence of the metallic clips of a stapled suture to close the duodenal wall during the previous SAEF repair. A review of the published data on this subject was performed to analyze the clinical features, the overall results, the risk factors of recurrence, and the main technical points of surgical treatment to prevent it. PMID:21269799

La Greca, Gaetano; Barbagallo, Francesco; Gagliardo, Salvatrice; Latteri, Saverio; Scala, Vincenzo; Sofia, Maria; Russello, Domenico

2011-04-01

208

Learning from Stochastic Rules by Spherical Perceptrons under Finite Temperature ---Optimal Temperature and Asymptotic Learning Curve---  

Science.gov (United States)

In the problem of learning under external disturbance, there is a possibility that the existence of some tolerance or flexibility in the system weakens the effect of noise and helps the system to perform more efficiently. In a previous letter, we gave one example of such phenomena in learning from stochastic rules by spherical perceptrons adopting the Gibbs algorithm using statistical mechanical methods. By the replica method, we showed that, in the output noise model, there exists an optimal temperature at which the generalization error takes its minimum for the stable replica symmetric (RS) solution. On the other hand, for other types of noise including input noise, it was shown that no such temperature exists up to the one-step replica symmetry breaking (1RSB) solution. That is, it was shown that for the asymptotic region of a large number of training sets, the RS solution becomes unstable, and the asymptotic behavior is determined by the 1RSB solution, The asymptotic expressions for learning curves were derived, and it turned out that, within the 1RSB solution, the learning curve does not depend on temperature. In this study, we give a detailed derivation of these results and also the results obtained by simulated annealing and exchange Monte Carlo simulation. The numerical results support the theoretical predictions.

Uezu, Tatsuya

2011-04-01

209

Ultrahard Multilayer Coatings  

Energy Technology Data Exchange (ETDEWEB)

We have developed a new multilayer a-tC material that is thick stress-free, adherent, low friction, and with hardness and stiffness near that of diamond. The new a-tC material is deposited by J pulsed-laser deposition (PLD) at room temperature, and fully stress-relieved by a short thermal anneal at 600°C. A thick multilayer is built up by repeated deposition and annealing steps. We measured 88 GPa hardness, 1100 GPa Young's modulus, and 0.1 friction coefficient (under high load). Significantly, these results are all well within the range reported for crystalline diamond. In fact, this material, if considered separate from crystalline diamond, is the 2nd hardest material known to man. Stress-free a-tC also has important advantages over thin film diamond; namely, it is smooth, processed at lower temperature, and can be grown on a much broader range of substrates. This breakthrough will enable a host of applications that we are actively pursuing in MEMs, sensors, LIGA, etc.

Chrzan, D.C.; Dugger, M.; Follstaedt, D.M.; Friedman, Lawrence H.; Friedmann, T.A.; Knapp, J.A.; McCarty, K.F.; Medlin, D.L.; Mirkarimi, P.B.; Missert, N.; Newcomer, P.P.; Sullivan, J.P.; Tallant, D.R.

1999-05-01

210

Magnetic metallic multilayers  

Energy Technology Data Exchange (ETDEWEB)

Utilizing self-consistent Hartree-Fock calculations, several aspects of multilayers and interfaces are explored: enhancement and reduction of the local magnetic moments, magnetic coupling at the interfaces, magnetic arrangements within each film and among non-neighboring films, global symmetry of the systems, frustration, orientation of the various moments with respect to an outside applied field, and magnetic-field induced transitions. Magnetoresistance of ferromagnetic-normal-metal multilayers is found by solving the Boltzmann equation. Results explain the giant negative magnetoresistance encountered in these systems when an initial antiparallel arrangement is changed into a parallel configuration by an external magnetic field. The calculation depends on (1) geometric parameters (thicknesses of layers), (2) intrinsic metal parameters (number of conduction electrons, magnetization, and effective masses in layers), (3) bulk sample properties (conductivity relaxation times), (4) interface scattering properties (diffuse scattering versus potential scattering at the interfaces, and (5) outer surface scattering properties (specular versus diffuse surface scattering). It is found that a large negative magnetoresistance requires considerable asymmetry in interface scattering for the two spin orientations. Features of the interfaces that may produce an asymmetrical spin-dependent scattering are studied: varying interfacial geometric random roughness with no lateral coherence, correlated (quasi-periodic) roughness, and varying chemical composition of the interfaces. The interplay between these aspects of the interfaces may enhance or suppress the magnetoresistance, depending on whether it increases or decreases the asymmetry in the spin-dependent scattering of the conduction electrons.

Hood, R.Q.

1994-04-01

211

Ultrahard Multilayer Coatings  

International Nuclear Information System (INIS)

We have developed a new multilayer a-tC material that is thick stress-free, adherent, low friction, and with hardness and stiffness near that of diamond. The new a-tC material is deposited by J pulsed-laser deposition (PLD) at room temperature, and fully stress-relieved by a short thermal anneal at 600 ampersand deg;C. A thick multilayer is built up by repeated deposition and annealing steps. We measured 88 GPa hardness, 1100 GPa Young's modulus, and 0.1 friction coefficient (under high load). Significantly, these results are all well within the range reported for crystalline diamond. In fact, this material, if considered separate from crystalline diamond, is the 2nd hardest material known to man. Stress-free a-tC also has important advantages over thin film diamond; namely, it is smooth, processed at lower temperature, and can be grown on a much broader range of substrates. This breakthrough will enable a host of applications that we are actively pursuing in MEMs, sensors, LIGA, etc

1999-01-01

212

Recurrent leiomyoma of the vagina.  

Science.gov (United States)

A rare case of huge vaginal leiomyoma recurrence is reported. Vaginal leiomyoma is a rare entity and recurrence after its removal is extremely rare. However, if recurrence occurs with intact ovarian function ovariectomy should also be done. PMID:1350544

Dhaliwal, L K; Das, I; Gopalan, S

1992-04-01

213

Pterygium surgery without recurrence  

Directory of Open Access Journals (Sweden)

Full Text Available Pterigium is a frequent cause of consultation in our environment and presents to the ophthalmologist an entity that can only be treated surgically, with the well known problem of recurrences. We did a search in literature based on evidence to try to explain the pathophysiologic phenomena involved in the genesis of pterigium and by this means propose a surgical technique with no recurrences. To a group of 82 patients was done resection of pterigium with free graft, mytomicin C and viscoelastic was done with follow up of 6 months and 0% recurrences.

de La Torre Alejandro

2004-09-01

214

Ultrasonic NDE of Multilayered Structures  

Energy Technology Data Exchange (ETDEWEB)

This project developed ultrasonic nondestructive evaluation techniques based on guided and bulk waves in multilayered structures using arrays. First, a guided wave technique was developed by preferentially exciting dominant modes with energy in the layer of interest via an ultrasonic array. Second, a bulk wave technique uses Fermat's principle of least time as well as wave-based properties to reconstruct array data and image the multilayered structure. The guided wave technique enables the inspection of inaccessible areas of a multilayered structure without disassembling it. Guided waves propagate using the multilayer as a waveguide into the inaccessible areas from an accessible position. Inspecting multi-layered structures with a guided wave relies on exciting modes with sufficient energy in the layer of interest. Multilayered structures are modeled to determine the possible modes and their distribution of energy across the thickness. Suitable modes were determined and excited by designing arrays with the proper element spacing and frequency. Bulk wave imaging algorithms were developed to overcome the difficulties of multiple reflections and refractions at interfaces. Reconstruction algorithms were developed to detect and localize flaws. A bent-ray algorithm incorporates Fermat's principle to correct time delays in the ultrasonic data that result from the difference in wave speeds in each layer and refractions at the interfaces. A planar wave-based algorithm was developed using the Green function for the multilayer structure to enhance focusing on reception for improved imaging.

Quarry, M J; Fisher, K A; Lehman, S K

2005-02-14

215

Diffusion Processes on Multilayer Networks  

CERN Document Server

Several systems can be modelled as sets of interdependent networks or networks with multiple types of connections, here generally called multilayer networks. Diffusion processes like the propagation of information or the spreading of diseases are fundamental phenomena occurring in these networks. However, while the study of diffusion processes in single networks has received a great deal of interest from various disciplines for over a decade, diffusion on multilayer networks is still a young and promising research area presenting many challenging research issues. In this paper we review the main models, results and applications of multilayer diffusion and discuss some promising research directions.

Salehi, Mostafa; Marzolla, Moreno; Montesi, Danilo; Siyari, Payam; Magnani, Matteo

2014-01-01

216

Dealing with Recurrence  

Medline Plus

Full Text Available ... News & Events Make a Difference Resources Donate Now Resources Brochures & Videos Resource Links Books & Periodicals Cancer Centers print email Resources » Brochures & Videos Dealing with Recurrence We know that ...

217

Recurrent congenital chylothorax.  

Science.gov (United States)

Congenital chylothorax is an uncommon but well-described condition. Recurrent congenital chylothorax is extremely rare. Yancy and Spock (1967) reviewed 31 reported cases of spontaneous chylothorax which occurred in the first 2 months of life and noted that male infants were affected twice as commonly as females. Two other cases of recurrent congenital chylothorax in male offspring (Defoort and Thiery, 1978; Reece et al., 1987) led to the suggestion of possible X-linked recessive inheritance. We describe a case of recurrent congenital chylothorax in which two consecutive female infants in a sibship were affected. The underlying cause of this disorder remains unknown. Inheritance as an X-linked recessive is not possible and this case is suggestive of autosomal recessive inheritance. The case also serves to emphasize the need for caution in counselling for recurrence risks when the underlying aetiology of the disorder is unknown. PMID:1800993

King, P A; Ghosh, A; Tang, M H; Lam, S K

1991-10-01

218

Multilayer cylindrical magnetic screens  

International Nuclear Information System (INIS)

The design is described of a horizontal multilayer cylindrical magnetic screen with end covers, which substantially reduces the mechanical stresses in the cylinders in experiments on particle beams. Two permalloy screens have been made for use in nuclear physics and magnetobiological studies: five-layer and eight-layer ones with internal volumes of 1.4 and 0.02 m3 correspondingly. The screen characteristics have been examined: the transverse and longitudinal screening coefficients, and also the distribution and stability of the residual magnetic field. A simple method is proposed for magnetizing the screens, which greatly increases the screening coefficients. A method is also described for increasing the longitudinal screening coefficient by means of two-layer end covers. Such cylindrical screens enable the introduction and extraction of the particle beam in a simple fashion, and also the location and extraction of measuring equipment and specimens

1985-06-01

219

Multi-layers castings  

Directory of Open Access Journals (Sweden)

Full Text Available In paper is presented the possibility of making of multi-layers cast steel castings in result of connection of casting and welding coating technologies. First layer was composite surface layer on the basis of Fe-Cr-C alloy, which was put directly in founding process of cast carbon steel 200–450 with use of preparation of mould cavity method. Second layer were padding welds, which were put with use of TIG – Tungsten Inert Gas surfacing by welding technology with filler on Ni matrix, Ni and Co matrix with wolfram carbides WC and on the basis on Fe-Cr-C alloy, which has the same chemical composition with alloy, which was used for making of composite surface layer. Usability for industrial applications of surface layers of castings were estimated by criterion of hardness and abrasive wear resistance of type metal-mineral.

J. Szajnar

2010-01-01

220

Multilayered folding with voids  

CERN Document Server

In the deformation of layered materials such as geological strata, or stacks of paper, mechanical properties compete with the geometry of layering. Smooth, rounded corners lead to voids between the layers, while close packing of the layers results in geometrically-induced curvature singularities. When voids are penalized by external pressure, the system is forced to trade off these competing effects, leading to sometimes striking periodic patterns. In this paper we construct a simple model of geometrically nonlinear multi-layered structures under axial loading and pressure confinement, with non-interpenetration conditions separating the layers. Energy minimizers are characterized as solutions of a set of fourth-order nonlinear differential equations with contact-force Lagrange multipliers, or equivalently of a fourth-order free-boundary problem. We numerically investigate the solutions of this free boundary problem, and compare them with the periodic solutions observed experimentally.

Dodwell, Timothy; Peletier, Mark; Budd, Chris

2011-01-01

 
 
 
 
221

Recurrent Urinary Bladder Paraganglioma  

Digital Repository Infrastructure Vision for European Research (DRIVER)

A 39-year-old male presented with recurrent attacks of painless haematuria. The patient has a history of partial cystectomy for bladder paraganglioma 10 years prior to the presentation. Imaging study and cystoscopic examination revealed a small anterior wall bladder tumor. The histological examination of the lesion confirmed that it was a urinary paraganglioma. Partial cystectomy was performed to this recurrent lesion. This case report stresses the importance of life-long follow-up of these l...

Al-zahrani, Ali A.

2010-01-01

222

Integrated Multilayer Insulation  

Science.gov (United States)

Integrated multilayer insulation (IMLI) is being developed as an improved alternative to conventional multilayer insulation (MLI), which is more than 50 years old. A typical conventional MLI blanket comprises between 10 and 120 metallized polymer films separated by polyester nets. MLI is the best thermal- insulation material for use in a vacuum, and is the insulation material of choice for spacecraft and cryogenic systems. However, conventional MLI has several disadvantages: It is difficult or impossible to maintain the desired value of gap distance between the film layers (and consequently, it is difficult or impossible to ensure consistent performance), and fabrication and installation are labor-intensive and difficult. The development of IMLI is intended to overcome these disadvantages to some extent and to offer some additional advantages over conventional MLI. The main difference between IMLI and conventional MLI lies in the method of maintaining the gaps between the film layers. In IMLI, the film layers are separated by what its developers call a micro-molded discrete matrix, which can be loosely characterized as consisting of arrays of highly engineered, small, lightweight, polymer (typically, thermoplastic) frames attached to, and placed between, the film layers. The term "micro-molded" refers to both the smallness of the frames and the fact that they are fabricated in a process that forms precise small features, described below, that are essential to attainment of the desired properties. The term "discrete" refers to the nature of the matrix as consisting of separate frames, in contradistinction to a unitary frame spanning entire volume of an insulation blanket.

Dye, Scott

2009-01-01

223

SOM-MLP Multi-Layered Neural Network with False-Alarming Nodes for Large Scale Pattern Recognition  

Energy Technology Data Exchange (ETDEWEB)

In this paper, an SOM-MLP multi-layered neural network was studied for the large-scale pattern recognition problem such as the multilingual character recognition. The multi-layered neural network is made of the preclassification and the fine recognition modes. We constructed clusters for the preclassification mode using self-organizing map (SOM) learning and performed modifying steps for reducing the number of clusters. The clusters contain patterns that have the similar characteristics. We adopted the multi-layer perceptron(MLP) networks to the corresponding clusters for the fine recognition mode. And we proposed the use of false-alarming nodes in output layer of the MLP network, which could be constructed on error-prone negative examples quite similar to the patterns of the selected cluster but actually belonging to different nearby clusters through SOM`s topology-preserving mapping. The proposed system could be successfully adopted for recognizing the large number of printed Korean/Chinese characters database as well as IRIS database. (author). 14 refs., 13 figs., 2 tabs.

Kang, B.S.; Lim, K.T.; Chien, S.I. [Kyungpook National University, Taegu (Korea, Republic of)

1999-04-01

224

Perceptron learning of pairwise contact energies for proteins incorporating the amino acid environment  

Science.gov (United States)

Although a coarse-grained description of proteins is a simple and convenient way to attack the protein folding problem, the construction of a global pairwise energy function which can simultaneously recognize the native folds of many proteins has resulted in partial success. We have sought the possibility of a systematic improvement of this pairwise-contact energy function as we extended the parameter space of amino acids, incorporating local environments of amino acids, beyond a 20×20 matrix. We have studied the pairwise contact energy functions of 20×20 , 60×60 , and 180×180 matrices depending on the extent of parameter space, and compared their effect on the learnability of energy parameters in the context of a gapless threading, bearing in mind that a 20×20 pairwise contact matrix has been shown to be too simple to recognize the native folds of many proteins. In this paper, we show that the construction of a global pairwise energy function was achieved using 1006 training proteins of a homology of less than 30%, which include all representatives of different protein classes. After parametrizing the local environments of the amino acids into nine categories depending on three secondary structures and three kinds of hydrophobicity (desolvation), the 16290 pairwise contact energies (scores) of the amino acids could be determined by perceptron learning and protein threading. These could simultaneously recognize all the native folds of the 1006 training proteins. When these energy parameters were tested on the 382 test proteins of a homology of less than 90%, 370 (96.9%) proteins could recognize their native folds. We set up a simple thermodynamic framework in the conformational space of decoys to calculate the unfolded fraction and the specific heat of real proteins. The different thermodynamic stabilities of E.coli ribonuclease H (RNase H) and its mutants were well described in our calculation, agreeing with the experiment.

Heo, Muyoung; Kim, Suhkmann; Moon, Eun-Joung; Cheon, Mookyung; Chung, Kwanghoon; Chang, Iksoo

2005-07-01

225

Combined multilayer-multilayer grating monochromator in soft X-ray region  

International Nuclear Information System (INIS)

The diffuse properties and combination methods of monochromator by combined multilayer-multilayer grating in soft X-ray region were deduced on the basis of diffraction properties of multi-layers and multilayer-gratings. If there is an appropriate angle, which is determined by the periods of the elements between reflection faces of multilayer and multilayer-gratings, the monochromator can afford higher resolution homogeneous light beam which is parallel to incident rays

2001-07-01

226

Multilayer coatings on flexible substrates  

Energy Technology Data Exchange (ETDEWEB)

Thin-film optical and non-optical multilayer coatings are deposited onto flexible substrates using a vacuum web coater developed at Pacific Northwest Laboratory. The coater`s primary application is rapid prototyping of multilayer (1) polymer coatings, (2) polymer/metal coatings, (3) ceramic/metal coatings, and (4) hybrid polymer, ceramic, and metal coatings. The coater is fully automated and incorporates polymer evaporation and extrusion heads, high-rate magnetron sputtering cathodes, and e-beam evaporation sources. Polymer electrolytes are deposited by extrusion techniques. Flexible plastic, metal, and ceramic substrates can be coated using roll-to-roll or closed-loop configurations. Examples of multilayer optical coatings demonstrated to date are solar reflectors, heat mirrors, Fabry-Perot filters, and alpha particle sensors. Nonoptical coatings include multilayer magnetic metal/ceramic and lamellar composites.

Martin, P.M.; Affinito, J.D.; Gross, M.E.; Coronado, C.A.; Bennett, W.D.; Stewart, D.C.

1995-04-01

227

Controlling light with plasmonic multilayers  

DEFF Research Database (Denmark)

Recent years have seen a new wave of interest in layered media - namely, plasmonic multilayers - in several emerging applications ranging from transparent metals to hyperbolic metamaterials. In this paper, we review the optical properties of such subwavelength metal-dielectric multilayered metamaterials and describe their use for light manipulation at the nanoscale. While demonstrating the recently emphasized hallmark effect of hyperbolic dispersion, we put special emphasis to the comparison between multilayered hyperbolic metamaterials and more broadly defined plasmonic-multilayer metamaterials A number of fundamental electromagnetic effects unique to the latter are identified and demonstrated. Examples include the evolution of isofrequency contour shape from elliptical to hyperbolic, all-angle negative refraction, and nonlocality-induced optical birefringence. Analysis of the underlying physical causes, which are spatial dispersion and optical nonlocality, is also reviewed. These recent results are extremely promising for a number of applications ranging from nanolithography to optical cloaking. © 2014 Elsevier B.V.

Zhukovsky, Sergei

2014-01-01

228

Controlling light with plasmonic multilayers  

Science.gov (United States)

Recent years have seen a new wave of interest in layered media - namely, plasmonic multilayers - in several emerging applications ranging from transparent metals to hyperbolic metamaterials. In this paper, we review the optical properties of such subwavelength metal-dielectric multilayered metamaterials and describe their use for light manipulation at the nanoscale. While demonstrating the recently emphasized hallmark effect of hyperbolic dispersion, we put special emphasis to the comparison between multilayered hyperbolic metamaterials and more broadly defined plasmonic-multilayer metamaterials A number of fundamental electromagnetic effects unique to the latter are identified and demonstrated. Examples include the evolution of isofrequency contour shape from elliptical to hyperbolic, all-angle negative refraction, and nonlocality-induced optical birefringence. Analysis of the underlying physical causes, which are spatial dispersion and optical nonlocality, is also reviewed. These recent results are extremely promising for a number of applications ranging from nanolithography to optical cloaking.

Orlov, Alexey A.; Zhukovsky, Sergei V.; Iorsh, Ivan V.; Belov, Pavel A.

2014-06-01

229

On the conditions for the existence of Perfect Learning and power law in learning from stochastic examples by Ising perceptrons  

CERN Document Server

In a previous letter, we studied learning from stochastic examples by perceptrons with Ising weights in the framework of statistical mechanics. Under the one-step replica symmetry breaking ansatz, the behaviours of learning curves were classified according to some local property of the rules by which examples were drawn. Further, the conditions for the existence of the Perfect Learning together with other behaviors of the learning curves were given. In this paper, we give the detailed derivation about these results and further argument about the Perfect Learning together with extensive numerical calculations.

Uezu, T

2001-01-01

230

Recurrent Escherichia coli bacteremia.  

Science.gov (United States)

Escherichia coli is the most common gram-negative organism associated with bacteremia. While recurrent E. coli urinary tract infections are well-described, recurrent E. coli bacteremia appears to be uncommon, with no episodes noted in multiple series of patients with gram-negative bacteremias. We report on 5 patients with recurrent bloodstream infections identified from a series of 163 patients with E. coli bacteremia. For each patient, the isolates from each episode were analyzed by pulsed-field gel electrophoresis (PFGE) and ribotyping and for the presence of E. coli virulence factors. For each of four patients, the index and recurrent episodes of bacteremia represented the same strain as defined by PFGE, and the strains were found to carry one or more virulence factors. The remaining patient, with two episodes of bloodstream infection separated by a 4-year interval, was infected with two isolates that did not carry any virulence factors and that were clonally related by ribotype analysis but differed by PFGE. All five patients had either a local host defense defect (three patients) or impaired systemic defenses (one patient) or both (one patient). Thus, recurrent E. coli bacteremia is likely to represent a multifactorial process that occurs in patients with impaired host defenses who are infected with virulent isolates. Images

Maslow, J N; Mulligan, M E; Arbeit, R D

1994-01-01

231

Legendre expansion of neutron flux over entire multilayer slab geometry  

International Nuclear Information System (INIS)

The monoenergetic integral transport equation for a multilayer slab geometry has been solved by Legendre expansion method. The method utilizes an expansion of the neutron flux over entire multilayer slab geometry in Legendre polynomials of the position co-ordinate (Single Expansion Method - SEM). This formulation is an extension of Carlvik's (1968) method for a homogeneous slab. Earlier (Raghav, 1984) the expansion of the neutron flux was done in each layer in Legendre polynomials of the position co-ordinate (Multi Expansion Method - MEM). The aim in this paper is to compare both the approaches of SEM and MEM. A few multilayer slab systems with vacuum boundary conditions have been selected for this purpose and Ksub(eff), the effective multiplication factor of the system, has been compared. SEM requires the evaluation of the integrals where the limits are not -1 to + 1 (as they are in MEM and where analytical expressions can be derived), in these cases we have derived recurrence relations (which are described in the Appendix) to evaluate such integrals. (author)

1987-01-01

232

Multi-Layer Perceptrons and Support Vector Machines for Detection Problems with Low False Alarm Requirements: an Eight-Month Progress Report  

Energy Technology Data Exchange (ETDEWEB)

In this project, the basic problem is to automatically separate test samples into one of two categories: clean or corrupt. This type of classification problem is known as a two-class classification problem or detection problem. In what follows, we refer to clean examples as negative examples and corrupt examples as positive examples. In a detection problem, a classifier decision on any one sample can be grouped into one of four decision categories: true negative, true positive, false negative and false positive. These four categories are illustrated by Table 1. True negatives and true positives are cases where the classifier has made the correct decision. False positives are cases where the classifier decides positive when the true nature of the sample was negative, and false negatives are cases where the classifier decides negative when the sample was actually positive. To evaluate the performance of a classifier, we run the classifier on all the samples of a data set and then count all the instances of true negatives, true positives, false negatives, and false positives. All of the performance metrics in this report are then formed from a combination of these four basic decision categories.

Chen, B; Hickling, T; Krnjajic, M; Hanley, W; Clark, G; Nitao, J; Knapp, D; Hiller, L; Mugge, M

2007-01-09

233

Recurrent Novae - A Review  

CERN Document Server

In recent years, recurrent nova eruptions are often observed very intensely in wide range of wavelengths from radio to optical to X-rays. Here I present selected highlights from recent multi-wavelength observations. The enigma of T Pyx is at the heart of this paper. While our current understanding of CV and symbiotic star evolution can explain why certain subset of recurrent novae have high accretion rate, that of T Pyx must be greatly elevated compared to the evolutionary mean. At the same time, we have extensive data to be able to estimate how the nova envelope was ejected in T Pyx, and it turns to be a rather complex tale. One suspects that envelope ejection in recurrent and classical novae in general is more complicated than the textbook descriptions. At the end of the review, I will speculate that these two may be connected.

Mukai, Koji

2014-01-01

234

Irreversible Multilayer Adsorption  

CERN Multimedia

Random sequential adsorption (RSA) models have been studied due to their relevance to deposition processes on surfaces. The depositing particles are represented by hard-core extended objects; they are not allowed to overlap. Numerical Monte Carlo studies and analytical considerations are reported for 1D and 2D models of multilayer adsorption processes. Deposition without screening is investigated, in certain models the density may actually increase away from the substrate. Analytical studies of the late stage coverage behavior show the crossover from exponential time dependence for the lattice case to the power law behavior in the continuum deposition. 2D lattice and continuum simulations rule out some "exact" conjectures for the jamming coverage. For the deposition of dimers on a 1D lattice with diffusional relaxation we find that the limiting coverage (100%) is approached according to the ~1/t**0.5 power-law preceded, for fast diffusion, by the mean-field crossover regime with the intermediate ~1/t behavior...

Nielaba, P; Wang, J S

1993-01-01

235

Optimized multilayer oxalate biosensor.  

Science.gov (United States)

The optimization of a biosensor prepared by the immobilization of oxalate oxidase (OOX) with a cross-linking agent onto a multilayer inorganic/organic modified electrode, is presented. A very thin Prussian Blue (PB) film covered by a self-doped polyaniline (SPAN) layer acts as very sensitive amperometric sensor for the H(2)O(2) formed by the enzymatic reaction. The electrode allows the very reliable and sensitive oxalate detection in the 0.08 to 0.45mmoll(-1) concentration range. The observed sensitivity was 131.3muAmmol(-1)cm(-2) at the operation potential of 0.05V versus Ag/AgCl in a succinate buffer solution (pH=3.8). The bilayer Prussian blue/SPAN leads to a very stable, sensitive and selective system that not only minimizes the interference caused by ascorbic and uric acids but also forms a very adherent sensing film that allows repetitive successive determinations. PMID:18969343

Fiorito, Pablo A; Córdoba de Torresi, Susana I

2004-02-27

236

Recurrent Pneumonia in Children  

Directory of Open Access Journals (Sweden)

Full Text Available Objective: The aim of this study was to determine the relative frequency and describe the predisposing causes of recurrent pneumonia in children. Material and methods: We retrospectively reviewed the medical records of patients with pneumonia at Uludag University Medical Faculty, Department of Pediatrics, between January 1998 and December 2007. Recurrent pneumonia was defined as at least two episodes in a 1 year period or at least three episodes over a lifetime. Patients with recurrent pneumonia were included in this study.Results: During the study period, 1617 children were admitted to hospital with a diagnosis of pneumonia, 185 (11.4% met the criteria for recurrent pneumonia. The mean age of patients was 16±32 months (3 months-14 years and 61% were male. An underlying cause was identified in 143 patients (77%. Of these, the underlying cause was diagnosed prior the pneumonia in 25 patients (17%, during the first episode in 30 (21%, and during recurrence in 88 (62%. Underlying causes included congenital cardiac defects in 32 patients (17.2%, gastroesophageal reflux in 31 patients (16.7%, aspiration syndrome in 27 patients (14.5%, asthma in 16 patients (8.6%, cystic fibrosis in 12 patients (6.4% immune disorders in 10 patients (5.4%, tuberculosis in 9 patients (4.8% and anomalies of the chest and lung in 6 patients (3.2%. No predisposing illness could be demonstrated in 42 patients (33%. Conclusion: Recurrent pneumonia occurred in 11.4% of all children hospitalized for pneumonia. The underlying cause was identified in 77% of the children. The most common causes were congenital cardiac defects, gastroesophageal reflux and aspiration syndrome.

Solmaz Çelebi

2010-06-01

237

Recurrent aphthous stomatitis.  

Science.gov (United States)

Recurrent aphthous stomatitis (RAS) is the most common ulcerative disease affecting the oral mucosa. RAS occurs mostly in healthy individuals and has an atypical clinical presentation in immunocompromised individuals. The etiology of RAS is still unknown, but several local, systemic, immunologic, genetic, allergic, nutritional, and microbial factors, as well as immunosuppressive drugs, have been proposed as causative agents. Clinical management of RAS using topical and systemic therapies is based on severity of symptoms and the frequency, size, and number of lesions. The goals of therapy are to decrease pain and ulcer size, promote healing, and decrease the frequency of recurrence. PMID:24655523

Akintoye, Sunday O; Greenberg, Martin S

2014-04-01

238

Recurrent Gliosarcoma in Pregnancy  

Science.gov (United States)

Gliosarcoma is a rare tumor of the central nervous system and it constitutes about 1 to 8% of all malignant gliomas. In this report we are presenting a recurrent gliosarcoma case during a pregnancy in a 30-year-old woman. This is the first report presenting gliosarcoma in the pregnancy.

Gulsen, Ismail; Ak, Hakan; Yilmaz, Tevfik; Bulut, Mehmet Deniz; Alk?s, Ismet; Bayram, Irfan

2014-01-01

239

Recurrence in acousmatic music  

Digital Repository Infrastructure Vision for European Research (DRIVER)

This doctoral research concerns recurrent phenomena in acousmatic works, investigating aspects of correspondence among the constituent sound materials, illuminating the temporal relationships existing among them, and providing concepts to help rationalise compositional structuring processes. While the main focus is on acousmatic music, many of the ideas developed in the research have broader scope and are relevant to other areas of music composition.

2013-01-01

240

Unfolding single- and multilayers  

Science.gov (United States)

When planar structures (e.g. sedimentary layers, veins, dykes, cleavages, etc.) are subjected to deformation, they have about equal chances to be shortened or stretched. The most common shortening and stretching structures are folds and boudinage, respectively. However, boudinage requires additional deformation mechanisms apart from viscous flow, like formation of fractures or strain localization. When folded layers are subjected to extension, they could potentially unfold back to straight layers. Although probably not uncommon, this would be difficult to recognize. Open questions are whether folded layers can unfold, what determines their mechanical behaviour and how we can recognize them in the field. In order to approach these questions, we present a series of numerical experiments that simulate stretching of previously folded single- and multi-layers in simple shear, using the two dimensional numerical modelling platform ELLE, including the finite element module BASIL that calculates viscous deformation. We investigate the parameters that affect a fold train once it rotates into the extensional field. The results show that the unfolding process strongly depends on the viscosity contrast between the layer and matrix (Llorens et al., 2013). Layers do not completely unfold when they experience softening before or during the stretching process or when other neighbouring competent layers prevent them from unfolding. The foliation refraction patterns are the main indicators of unfolded folds. Additionally, intrafolial folds and cusp-like folds adjacent to straight layers, as well as variations in fold amplitudes and limb lengths of irregular folds can also be used as indicators of stretching of a layer after shortening and folding. References: Llorens, M-.G., Bons, P.D., Griera, A. and Gomez-Rivas, E. 2013. When do folds unfold during progressive shear?. Geology, 41, 563-566.

Llorens, Maria-Gema; Bons, Paul D.; Griera, Albert; Gomez-Rivas, Enrique

2014-05-01

 
 
 
 
241

Persistent and recurrent hyperparathyroidism.  

Science.gov (United States)

More than 95% of patients with primary hyperparathyroidism (HPT) will be cured at initial operation by an experienced surgeon. Despite this success rate, persistent and recurrent HPT remain challenging clinical entities. The most cost effective and safest treatment for persistent and recurrent HPT is avoidance by successful first operation. The contributors to treatment failure can be categorized into factors related to the initial surgical procedure, anatomic variability, and the biology of disease. An understanding of the factors that commonly contribute to treatment failure can help prevent persistent and recurrent disease and plays an integral role in planning subsequent surgical approaches. Once a biochemical diagnosis of persistent or recurrent HPT is confirmed, a thorough evaluation of previous operative, pathology, and radiology reports is essential. Localization procedures supplement this information and help direct the reoperative approach. When complementary noninvasive studies, such as ultrasound, sestamibi, and magnetic resonance imaging are negative, equivocal, or discordant, invasive tests (eg, selective venous sampling for parathyroid hormone levels) are warranted. Intraoperative ultrasound and gamma-probe localization are of questionable value, but intraoperative parathyroid hormone assays help facilitate these challenging repeat dissections. Repeat parathyroid exploration is associated with more complications and fewer cures compared to the initial explorations and should only be undertaken by an experienced surgeon in a center that can provide expert preoperative localization, adjunctive intraoperative tools, and cryopreservation of parathyroid tissue when necessary. Although controversy exists regarding indications for reoperative treatment for persistent or recurrent HPT, parathyroidectomy remains the only curative treatment option. Surgery should be considered first-line treatment in most circumstances. PMID:15233910

Caron, Nadine R; Sturgeon, Cord; Clark, Orlo H

2004-08-01

242

Perfect absorption in graphene multilayers  

Science.gov (United States)

We demonstrate that 100% light absorption can be achieved in a graphene-based hyperbolic metamaterial, consisting of periodically arranged graphene layers which are tilted with respect to the interface. The geometrical parameters of the multilayered structure and the chemical potential of graphene are chosen in such a way that the in-plane relative effective permittivity is close to -1. Under this condition, the graphene multilayer exhibits asymmetry which appears as a very large difference between waves propagating upward and downward with respect to multilayer boundaries. One of them has a very high attenuation constant and neither of the waves undergo reflection at slab interfaces, resulting in total absorption even for an optically ultra-thin slab.

Nefedov, Igor S.; Valaginnopoulos, Constantinos A.; Melnikov, Leonid A.

2013-11-01

243

Multilayer adsorption on fractal surfaces.  

Science.gov (United States)

Multilayer adsorption is often observed in liquid chromatography. The most frequently employed model for multilayer adsorption is the BET isotherm equation. In this study we introduce an interpretation of multilayer adsorption measured on liquid chromatographic stationary phases based on the fractal theory. The fractal BET isotherm model was successfully used to determine the apparent fractal dimension of the adsorbent surface. The nonlinear fitting of the fractal BET equation gives us the estimation of the adsorption equilibrium constants and the monolayer saturation capacity of the adsorbent as well. In our experiments, aniline and proline were used as test molecules on reversed phase and normal phase columns, respectively. Our results suggest an apparent fractal dimension 2.88-2.99 in the case of reversed phase adsorbents, in the contrast with a bare silica column with a fractal dimension of 2.54. PMID:24315680

Vajda, Péter; Felinger, Attila

2014-01-10

244

Multilayer optics design and characterization  

International Nuclear Information System (INIS)

The development of multilayer reflectors is aimed at applying to x-ray optical systems such as beam line optics of synchrotron radiation, x-ray microscope, x-ray telescope and so on in the wavelength region 1-300A. Multilayers are designed to get high reflectivity in the incidence angle and wavelength concerned by selecting the material combinations, number of layer pairs and thickness of a layer pair. The fabrication was done by using an electron beam deposition, ion beam sputtering, RF sputtering and so on. The characterization was carried out by measuring the reflectivity. Bragg angle and wavelength resolution with characteristic x-rays and monochromatized synchrotron radiation. The reflectivity strongly depends on the interfacial roughness, related to the decrease of a layer thickness and increase of number of layer pairs. Multilayers have been already applied to Schwarzschild microscope, Cassegrain telescope, double crystal spectrometer and reflective grating for practical use. (author). 10 refs., 4 figs

1993-01-01

245

Stress analysis in multilayer structures  

Science.gov (United States)

The magnitude and distribution of thermal stresses in multilayer thin film structures have been modeled using a analytical solution method (ASM) and a newly developed hybrid finite element method (HFEM). This combined approach treats stress singularity as well as nonsingularity with equal ease. The use of hybrid elements based on an analytical solution of the stress singularity at the free edge has been found to provide accurate thermal stress solutions with fast convergence. Modeling of stress behavior in multilayer structures has been extended to include solutions for non-90sp° wedges (so called sharp edges) and solutions for multimaterial wedges. The dependence of the order of the stress singularity as well as the intensity of the stress singularity on the specific free edge geometry has been worked out as well. The results of theoretical analysis and calculations have made feasible the development of a software program, titled "Multilayer Structures" (MLS). The program is Windows-based. It is user friendly, allowing efficient and rapid thermal stress analysis of virtually any multilayer structure. It is seen as a valuable tool in design and for manufacturing and quality control functions in areas in which multilayer structures play a vital role. With a specially designed automesh engine and a simplified procedure for residual stress calculations, tedious preprocessing procedures need not be of concern. The program still provides the opportunity to use conventional finite element analysis. The MLS program has been applied and evaluated in various areas, such as in the optimization of substrate and film thicknesses in Multi Chip Modules (MCM's), the design of functionally gradient transition layers required in the bonding of dissimilar materials, and the identification of suitable substrates or buffer layers in diamond film deposition. The work reported in this dissertation constitutes a first step towards a full understanding of the mechanical behavior of multilayer structures and the development of a complete and comprehensive tool to predict performance.

White, Dongming Yuan

1997-12-01

246

Electrochromism and electrocatalysis in viologen polyelectrolyte multilayers  

Energy Technology Data Exchange (ETDEWEB)

Polyelectrolyte multilayers were constructed from a polyviologen and poly(styrene sulfonate) using an alternating polyion solution deposition technique. In situ absorption spectroscopy showed multilayers to be strongly electrochromic. Oxygen reduction at multilayer-coated conducting glass electrodes was also shown to be facilitated.

Stepp, J.; Schlenoff, J.B. [Florida State Univ., Tallahassee, FL (United States)

1997-06-01

247

Computing and fabricating multilayer models  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We present a method for automatically converting a digital 3D model into a multilayer model: a parallel stack of high-resolution 2D images embedded within a semi-transparent medium. Multilayer models can be produced quickly and cheaply and provide a strong sense of an object's 3D shape and texture over a wide range of viewing directions. Our method is designed to minimize visible cracks and other artifacts that can arise when projecting an input model onto a small number of parallel planes, a...

Holroyd, Michael; Baran, Ilya; Lawrence, Jason; Matusik, Wojciech

2011-01-01

248

Elasticity of polyelectrolyte multilayer microcapsules  

CERN Multimedia

We present a novel approach to probe elastic properties of polyelectrolyte multilayer microcapsules. The method is based on measurements of the capsule load-deformation curves with the atomic force microscope. The experiment suggests that at low applied load deformations of the capsule shell are elastic. Using elastic theory of membranes we relate force, deformation, elastic moduli, and characteristic sizes of the capsule. Fitting to the prediction of the model yields the lower limit for Young's modulus of the polyelectrolyte multilayers of the order of a few MPa. This value corresponds to Young's modulus of a highly elastic polymer.

Lulevich, V V; Vinogradova, O I

2003-01-01

249

Risk for Recurrence in Depression  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Depression is a highly recurrent disorder with significant personal and public health consequences. Prevention of recurrence would be extremely desirable, and thus researchers have begun to identify risk factors that are specific to recurrence, which may be different from risk factors for first-onset of depression. Methodological issues in this area of research are briefly reviewed (e.g., the various definitions of “recurrence” and “depression”), followed by a review of studies on spe...

Burcusa, Stephanie L.; Iacono, William G.

2007-01-01

250

Image quality of figured multilayered optics  

International Nuclear Information System (INIS)

The reflectivity and resolution of a multilayer structure is strongly affected by the roughness at the interfaces between two successive layers and by the amount that the constituent materials will diffuse into one another at the interfaces. Performance is also affected by the variations in individual layer thicknesses and by inhomogeneities in the materials. These deviations from the ideal multilayer will also affect the quality of the image from a figured multilayer optical element. The theory used to model the effects of non-ideal multilayers on the image quality of figured optics will be discussed. The relationship between image quality and multilayer structure quality will be illustrated with several examples

1985-08-18

251

New developments in Ni/Ti multilayers  

Energy Technology Data Exchange (ETDEWEB)

It is now 20 years since super-mirrors were first used as a neutron optical element. Since then the field of multilayer neutron-optics has matured with multilayers finding their way to application in many neutron scattering instruments. However, there is still room for progress in terms of multilayer quality, performance and application. Along with work on multilayers for neutron polarisation Ni/Ti super-mirrors have been optimised. The state-of-the-art Ni/Ti super-mirror performance and the results obtained in two neutron-optics applications of Ni/Ti multilayers are presented. (author).

Anderson, I.; Hoghoj, P. [Institut Max von Laue - Paul Langevin (ILL), 38 - Grenoble (France)

1997-04-01

252

Ultrathin multilayer capsules in drug delivery  

Directory of Open Access Journals (Sweden)

Full Text Available Ultra thin multilayer capsules are attractive and stable systems capable of delivering the bioactives. Ultra thin multilayer capsules consist of polyelectrolytic materials that are formed in the presence of a template. This is achieved through layer-by-layer adsorption of oppositely charged macromolecules on to colloidal particles. Upon extraction, the resulting cavities retain affinity for the bioactives. This review considers the fabrication, of ultra thin multilayer capsules, physiochemical properties and role of ultra thin multilayer capsules within a pharmaceutical remit. Ultrathin multilayer capsules have potential for creating satisfactory drug dosage forms.

Jain Arti

2007-01-01

253

Recurrent hyperphosphatemic tumoural calcinosis.  

Science.gov (United States)

Tumoural calcinosis (TC) is a benign gradually developing disorder that can occur in a variety of clinical settings, characterised by subcutaneous deposition of calcium phosphate with or without giant cell reaction. We describe a case of 11-year-old girl presenting with recurrent hard swellings in the vicinity of shoulder and hip joints associated with elevated serum phosphate and normal serum calcium levels. TC has been mainly reported from Africa, with very few cases reported from India. After the diagnosis of hyperphosphatemic TC was established, the patient was treated with oral sevelamer and is under constant follow-up to detect recurrence, if any. The present case highlights the fact that although an uncommon lesion, TC must be considered in the differential diagnosis of subcutaneous hard lump in the vicinity of a joint. PMID:23010461

Amit, Sonal; Agarwal, Asha; Nigam, Anand; Rao, Yashwant Kumar

2012-01-01

254

Recurrent Retrorectal Teratoma  

Science.gov (United States)

Retrorectal tumors are a rare group of neoplasms that occur most commonly in the neonatal and infant population. They vary in presentation, but teratomas are the most common and often present as a protruding mass from the sacrococcygeal region. Immediate surgical resection is indicated when found and coccygectomy is performed to prevent recurrence. When teratomas recur, the patients most often have vague symptoms and the tumors usually have malignant transformation. Here, we present the case of a young woman who underwent surgical resection of a sacrococcygeal teratoma at 3 days of age where the coccyx was not removed. She presented at 31 years of age with lower extremity paresthesias and radiography revealed a cystic mass extending from the sacrum. After resection, pathology revealed a recurrent teratoma with nests of adenocarcinoma.

Vana, P. Geoff; Yong, Sherri; Hayden, Dana; Saclarides, Theodore; Slogoff, Michelle; Boblick, William; Eberhardt, Joshua

2014-01-01

255

Recurrent retrorectal teratoma.  

Science.gov (United States)

Retrorectal tumors are a rare group of neoplasms that occur most commonly in the neonatal and infant population. They vary in presentation, but teratomas are the most common and often present as a protruding mass from the sacrococcygeal region. Immediate surgical resection is indicated when found and coccygectomy is performed to prevent recurrence. When teratomas recur, the patients most often have vague symptoms and the tumors usually have malignant transformation. Here, we present the case of a young woman who underwent surgical resection of a sacrococcygeal teratoma at 3 days of age where the coccyx was not removed. She presented at 31 years of age with lower extremity paresthesias and radiography revealed a cystic mass extending from the sacrum. After resection, pathology revealed a recurrent teratoma with nests of adenocarcinoma. PMID:24778657

Vana, P Geoff; Yong, Sherri; Hayden, Dana; Saclarides, Theodore; Slogoff, Michelle; Boblick, William; Eberhardt, Joshua

2014-01-01

256

Recurrent Partial Words  

Directory of Open Access Journals (Sweden)

Full Text Available Partial words are sequences over a finite alphabet that may contain wildcard symbols, called holes, which match or are compatible with all letters; partial words without holes are said to be full words (or simply words. Given an infinite partial word w, the number of distinct full words over the alphabet that are compatible with factors of w of length n, called subwords of w, refers to a measure of complexity of infinite partial words so-called subword complexity. This measure is of particular interest because we can construct partial words with subword complexities not achievable by full words. In this paper, we consider the notion of recurrence over infinite partial words, that is, we study whether all of the finite subwords of a given infinite partial word appear infinitely often, and we establish connections between subword complexity and recurrence in this more general framework.

Francine Blanchet-Sadri

2011-08-01

257

Recurrent oral thrush.  

Science.gov (United States)

Autoimmune polyendocrinopathy syndrome type 1 (APS-1) is characterized by the presence of at least two out of three clinical features, which include chronic mucocutaneous candidiasis (CMC), Addison's disease and hypoparathyroidism. The authors' present an one and a half year old girl with recurrent oral thrush who presented with generalised afebrile seizure. Evaluation revealed severe hypocalcemia with low parathormone and normal vitamin D level consistent with hypoparathyroidism. In view of the oral candidiasis and hypoparathyroidism, a clinical possibility of autoimmune polyglandular syndrome (type 1) was strongly considered. Her mother, on subsequent pregnancy was subjected to gene analysis of the fetus (chorionic villus sampling) and also for this child (index case). Both the fetus and index child were confirmed to have the AIRE gene mutation of APS1. After detailed counseling the parents opted for medical termination of the pregnancy. In children who present with recurrent oral thrush we need to consider but also look beyond immunodeficiency. PMID:24081895

Sivabalan, Somu; Mahadevan, Shriraam; Srinath, M V

2014-04-01

258

Recurrent Gallstone Ileus  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Mechanical small bowel obstructions caused by gallstones account for 1% to 3% of cases. In these patients, 80% to 90% of residual gallstones in these patients will pass through a remaining fistula without consequence. Recurrent gallstone ileus has been reported in 5% of patients. We report the case of a woman, aged 72 years, who presented with mechanical small bowel obstruction caused by gallstone ileus. After successful surgical therapy for gallstone ileus, the patient's symptoms recurred, a...

Hayes, Nicolas; Saha, Sanjoy

2012-01-01

259

Multilayer Thermionic Refrigerator and Generator  

CERN Document Server

A new method of refrigeration is proposed. Cooling is obtained by thermionic emission of electrons over periodic barriers in a multilayer geometry. These could be either Schottky barriers between metals and semiconductors or else barriers in a semiconductor superlattice. The same device is an efficient power generator. A complete theory is provided.

Mahan, G D; Bartkowiak, M

1998-01-01

260

Multilayer printed wiring board lamination  

Energy Technology Data Exchange (ETDEWEB)

The relationship of delamination resistance of multilayer PWBs made from GF material to manufacturing process variables was investigated. A unique quantitative test method developed during this project shows that delamination resistance is highly sensitive to material conditioning, to innerlayer surface treatment, and to post-lamination storage conditions, but is relatively insensitive to cure cycle variations.

Lula, J.W.

1980-06-01

 
 
 
 
261

Multilayer Controller for Outdoor Vehicle  

DEFF Research Database (Denmark)

A full software and hardware solution has been designed, implemented and tested for control of a small agricultural automatic tractor. The objective was to realise a user-friendly, multi-layer controller architecture for an outdoor platform. The collaborative research work was done as a part of a research project within the field of automated agriculture and precision farming.

Reske-Nielsen, Anders; Mejnertsen, Asbjørn

2006-01-01

262

Multilayer thermionic refrigerator and generator  

International Nuclear Information System (INIS)

A new method of refrigeration is proposed. Cooling is obtained by thermionic emission of electrons over periodic barriers in a multilayer geometry. These could be either Schottky barriers between metals and semiconductors or else barriers in a semiconductor superlattice. The same device is an efficient power generator. A complete theory is provided. copyright 1998 American Institute of Physics

1998-05-01

263

Multilayer thermionic refrigerator and generator  

Energy Technology Data Exchange (ETDEWEB)

A new method of refrigeration is proposed. Cooling is obtained by thermionic emission of electrons over periodic barriers in a multilayer geometry. These could be either Schottky barriers between metals and semiconductors or else barriers in a semiconductor superlattice. The same device is an efficient power generator. A complete theory is provided. {copyright} {ital 1998 American Institute of Physics.}

Mahan, G.D.; Sofo, J.O.; Bartkowiak, M. [Department of Physics and Astronomy, University of Tennessee, Knoxville, Tennessee37996-1200 and Solid State Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee37831-6030 (United States)

1998-05-01

264

High performance EUV multilayer optics  

Science.gov (United States)

The demand for enhanced optical resolution in order to structure and observe ever smaller details has pushed optics development in recent years. There is increasing interest in optical components for the extreme ultraviolet (EUV) spectral region mainly as a result of the production of more powerful electronic circuits with the aid of projection lithography. Due to absorption at wavelengths below 100 nm the penetration depth of EUV radiation into matter is only a few nano-meters. Hence, reflective optics must be used for imaging and light collection such as EUV multilayer mirrors which consist of alternating thin films with different refractive indices. This basic idea can be compared to the classic, high reflective ?/4 systems: the constructive interference of all beams reflected at the film interfaces. At Fraunhofer IOF Jena multilayer optics development cover the full range between the soft X-rays around 2 nm wave-length and the vacuum ultraviolet. However, the paper will focus on multilayer optics for EUV lithography applications at 13.5 nm. Besides the development of high-reflective multilayers with enhanced thermal and radiation stability using interface engineering and optimized capping layers collector and imaging optics for diverse applications in the EUV spectral range have been realized. The deposition of EUV collector mirrors for high-power laser produced plasma (LPP) sources is discussed. The paper summarizes recent progress and the present knowledge in preparation and characterization of multilayer optics for the EUV spectral range with regard to maximum optical performance, minimization of structure imperfections, reduc-tion of residual stresses as well as enhanced thermal and radiation stability.

Kaiser, Norbert; Yulin, Sergiy; Perske, Marco; Feigl, Torsten

2008-09-01

265

Treatment of recurrent mandibular ameloblastoma  

Science.gov (United States)

Ameloblastoma is a locally invasive benign odontogenic tumor with a high rate of recurrence in the long term. The authors conducted a retrospective study of patients with mandibular ameloblastoma in order to evaluate recurrent ameloblastoma management. The study included data from 31 patients over a period of 10 years. Data collected included age, gender, tumor location, histological findings, initial treatment, number of recurrences and year of onset, type of treatment of recurrence, reconstruction and follow-up. Recurrences were detected in nine patients (29%). Tumor recurrences appeared at 32 months on average following the initial surgical procedure. Recurrences were associated mainly to inadequate initial therapeutic approach and were treated by bone resection with a safety margin of at least 1 cm beyond the radiographically visible margins. Immediate reconstruction of bone defects was performed with grafts or free flaps.

INFANTE-COSSIO, PEDRO; PRATS-GOLCZER, VICTORIA; GONZALEZ-PEREZ, LUIS-MIGUEL; BELMONTE-CARO, RODOLFO; MARTINEZ-DE-FUENTES, RAFAEL; TORRES-CARRANZA, EUSEBIO; GACTO-SANCHEZ, PURIFICACION; GOMEZ-CIA, TOMAS

2013-01-01

266

Multilayer Composite Pressure Vessels  

Science.gov (United States)

A method has been devised to enable the fabrication of lightweight pressure vessels from multilayer composite materials. This method is related to, but not the same as, the method described in gMaking a Metal- Lined Composite-Overwrapped Pressure Vessel h (MFS-31814), NASA Tech Briefs, Vol. 29, No. 3 (March 2005), page 59. The method is flexible in that it poses no major impediment to changes in tank design and is applicable to a wide range of tank sizes. The figure depicts a finished tank fabricated by this method, showing layers added at various stages of the fabrication process. In the first step of the process, a mandrel that defines the size and shape of the interior of the tank is machined from a polyurethane foam or other suitable lightweight tooling material. The mandrel is outfitted with metallic end fittings on a shaft. Each end fitting includes an outer flange that has a small step to accommodate a thin layer of graphite/epoxy or other suitable composite material. The outer surface of the mandrel (but not the fittings) is covered with a suitable release material. The composite material is filament- wound so as to cover the entire surface of the mandrel from the step on one end fitting to the step on the other end fitting. The composite material is then cured in place. The entire workpiece is cut in half in a plane perpendicular to the axis of symmetry at its mid-length point, yielding two composite-material half shells, each containing half of the foam mandrel. The halves of the mandrel are removed from within the composite shells, then the shells are reassembled and bonded together with a belly band of cured composite material. The resulting composite shell becomes a mandrel for the subsequent steps of the fabrication process and remains inside the final tank. The outer surface of the composite shell is covered with a layer of material designed to be impermeable by the pressurized fluid to be contained in the tank. A second step on the outer flange of each end fitting accommodates this layer. Depending on the application, this layer could be, for example, a layer of rubber, a polymer film, or an electrodeposited layer of metal. If the fluid to be contained in the tank is a gas, then the best permeation barrier is electrodeposited metal (typically copper or nickel), which can be effective at a thickness of as little as 0.005 in (.0.13 mm). The electrodeposited metal becomes molecularly bonded to the second step on each metallic end fitting. The permeation-barrier layer is covered with many layers of filament-wound composite material, which could be the same as, or different from, the composite material of the inner shell. Finally, the filament-wound composite material is cured in an ov

DeLay, Tom

2005-01-01

267

[Treatment of recurrent gliomas].  

Science.gov (United States)

In operation for gliomas, it is our principle to remove extensively by sucker dissection technique. But, in many cases, we cannot achieve total removal because of invasion of tumor cells into the deep or vital structure. Postoperatively we apply irradiation, chemotherapy and immunotherapy in every cases. Even after multimodality treatment, recurrence may be inevitable. In order to check the recurrence as early as possible, we took follow-up CT scan regularly. When the recurrence appeared on CT scan, we actively performed reoperation. In this paper, we present characteristics of follow-up CT scan and result of the reoperation. Since introduction of CT scan in 1977, we have followed 30 supratentorial malignant gliomas and 16 supratentorial low grade gliomas postoperatively. CT scan was taken in every three months to check the course of contrast enhancement. After removal of the tumor, round low density area appeared on CT scan showing residual cavity. By contrast enhancement, various shape of high density area were seen. We divide the postoperative CT scan in 4 types by mode of contrast enhancement. In the type 1, enhanced area was persistent around the low density area. In the type 2, enhanced area was present around the low density area just after operation, but gradually disappeared. In the type 3, no enhanced area was present. In the type 4, dissemination occurring late after operation. Among the malignant gliomas, 12 cases belonged to the type 1, 6 cases to the type 2, 10 cases to the type 3, and 2 cases to the type 4. Among the low grade gliomas, 3 cases belonged to the type 1, 2 cases to the type 2, and 9 cases to the type 3.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:6547513

Kyuma, Y; Yamashita, T; Ishiwata, Y; Murai, M; Kuwabara, T

1984-03-01

268

Recurrence Relations and Determinants  

CERN Document Server

We examine relationships between two minors of order n of some matrices of n rows and n+r columns. This is done through a class of determinants, here called $n$-determinants, the investigation of which is our objective. We prove that 1-determinants are the upper Hessenberg determinants. In particular, we state several 1-determinants each of which equals a Fibonacci number. We also derive relationships among terms of sequences defined by the same recurrence equation independently of the initial conditions. A result generalizing the formula for the product of two determinants is obtained. Finally, we prove that the Schur functions may be expressed as $n$-determinants.

Janjic, Milan

2011-01-01

269

Developed player for multilayer disk  

Science.gov (United States)

Based on nm fabrication technology, a developed player for dual and multilayer disk is proposed in this paper. A multifocus device with focus 8.5 mm is used. The distance between two neighbor focal plane is 0.45 mm. The numeral aperture of the developed player is 0.59, the focusing spot is 0.93 um. The developed player with the multifocus device is not only simple in structure, light in weight, but also can focus automatically at any layer of multilayer disk eve, no mechanical movement. Compared to the common CD player, the developed player is characteristic of only one multifocus device to focus and split beam, where the prism and the grating in common CD player are displaced, but the focusing and the tracing error signals can be obtained conveniently for servo detection.

Huang, Guoliang; Xu, Duanyi; Pan, Longfa; Lu, Dajin; Qi, Guosheng

1996-09-01

270

Metallic multilayers at the nanoscale  

Energy Technology Data Exchange (ETDEWEB)

The development of multilayer structures has been driven by a wide range of commercial applications requiring enhanced material behaviors. Innovations in physical vapor deposition technologies, in particular magnetron sputtering, have enabled the synthesis of metallic-based structures with nanoscaled layer dimensions as small as one-to-two monolayers. Parameters used in the deposition process are paramount to the Formation of these small layer dimensions and the stability of the structure. Therefore, optimization of the desired material properties must be related to assessment of the actual microstructure. Characterization techniques as x-ray diffraction and high resolution microscopy are useful to reveal the interface and layer structure-whether ordered or disordered crystalline, amorphous, compositionally abrupt or graded, and/or lattice strained Techniques for the synthesis of metallic multilayers with subnanometric layers will be reviewed with applications based on enhancing material behaviors as reflectivity and magnetic anisotropy but with emphasis on experimental studies of mechanical properties.

Jankowski, A.F.

1994-11-01

271

Thermally induced delamination of multilayers  

DEFF Research Database (Denmark)

Steady-state delamination of multilayered structures, caused by stresses arising during processing due to thermal expansion mismatch, is analyzed by a fracture mechanics model based on laminate theory. It is found that inserting just a few interlayers with intermediate thermal expansion coefficients may be an effective way of reducing the delamination energy release rate. Uneven layer thickness and increasing elastic mismatch are shown to raise the energy release rate. Experimental work confirms important trends of the model.

Sørensen, Bent F.; Sarraute, S.

1998-01-01

272

On Concircularly Recurrent Finsler Manifolds  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Two special Finsler spaces have been introduced and investigated, namely $R^h$-recurrent Finsler space and consircularly recurrent Finsler space. The defining properties of these spaces are formulated in terms of the first curvature tensor of Cartan connection. The following three results constitute the main object of the present paper: 1. A concircularly flat Finsler manifold is necessarily of constant curvature (Theorem A); 2. Every $R^h$-recurrent Finsler manifold is conc...

Youssef, Nabil L.; Soleiman, A.

2012-01-01

273

MRI of cerebral tumor recurrences  

International Nuclear Information System (INIS)

40 patients were examined with magnetic resonance imaging (MRI) after treatment of primary brain tumors. In 13 cases recurrences could be confirmed which were evaluated retrospectively. In 10 cases a comparison between MRI and CT was possible. Obliteration of the surgical defects due to signal intensive (inhomogenous) structures and signs of mass effects, possibly with a perifocal edema, are the most reliable signs of recurrence. In case of adjuvant radiotherapy diagnosis is difficult as sequelae and recurrences cannot always be differentiated. (orig.)

1988-01-01

274

Multilayered Transducers Using Polyurea Film  

Science.gov (United States)

We have been investigating ultrasonic transducers using a polyurea piezoelectric material, which is fabricated by vapor deposition. To enhance the transducer performance, a multilayered configuration is studied in this work. First, the fabrication and transducer design of the multilayered structure are described. A special twin-vacuum chamber is used for laminating the polyurea layers and aluminum electrodes alternately without breaking vacuum. We fabricate two- and four-layered transducers with 1.5 ?m polyurea films. The calculation results show that the force factor and electromechanical coupling coefficient increase as the number of layers increases. Second, to evaluate the transducer performance, we measure the electromechanical coupling factors and electric admittances. The coupling coefficients also increase as the number of layers increases at the resonant frequencies of about 30, 65, and 100 MHz. The pulse/echo measurements are conducted to determine the transmission and receiving characteristics using a reflector. The results of the experiment show that the voltage amplitudes of the received signal increase because of multilayer lamination.

Nakazawa, Marie; Tabaru, Masaya; Nakamura, Kentaro; Ueha, Sadayuki; Maezawa, Akihiro

2007-07-01

275

Epidemiology of recurrent venous thrombosis  

Scientific Electronic Library Online (English)

Full Text Available SciELO Brazil | Language: English Abstract in english Venous thrombosis, including deep vein thrombosis and pulmonary embolism, is a common disease that frequently recurs. Recurrence can be prevented by anticoagulants, but this comes at the risk of bleeding. Therefore, assessment of the risk of recurrence is important to balance the risks and benefits [...] of anticoagulant treatment. This review briefly outlines what is currently known about the epidemiology of recurrent venous thrombosis, and focuses in more detail on potential new risk factors for venous recurrence. The general implications of these findings in patient management are discussed.

D.D., Ribeiro; W.M., Lijfering; S.M., Barreto; F.R., Rosendaal; S.M., Rezende.

276

Ultrathin multilayer capsules in drug delivery  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Ultra thin multilayer capsules are attractive and stable systems capable of delivering the bioactives. Ultra thin multilayer capsules consist of polyelectrolytic materials that are formed in the presence of a template. This is achieved through layer-by-layer adsorption of oppositely charged macromolecules on to colloidal particles. Upon extraction, the resulting cavities retain affinity for the bioactives. This review considers the fabrication, of ultra thin multilayer capsules, physiochemica...

Jain Arti; Kumar P; Jain N

2007-01-01

277

Multilayer Analysis and Visualization of Networks  

CERN Multimedia

Multilayer relationships among and information about biological entities must be accompanied by the means to analyze, visualize, and obtain insights from such data. We report a methodology and a collection of algorithms for the analysis of multilayer networks in our new open-source software (muxViz). We demonstrate the ability of muxViz to analyze and interactively visualize multilayer data using empirical genetic and neuronal networks.

De Domenico, Manlio; Arenas, Alex

2014-01-01

278

Multi-layer seal for electrochemical devices  

Energy Technology Data Exchange (ETDEWEB)

Multi-layer seals are provided that find advantageous use for reducing leakage of gases between adjacent components of electrochemical devices. Multi-layer seals of the invention include a gasket body defining first and second opposing surfaces and a compliant interlayer positioned adjacent each of the first and second surfaces. Also provided are methods for making and using the multi-layer seals, and electrochemical devices including said seals.

Chou, Yeong-Shyung [Richland, WA; Meinhardt, Kerry D [Kennewick, WA; Stevenson, Jeffry W [Richland, WA

2010-11-16

279

Multi-layer seal for electrochemical devices  

Energy Technology Data Exchange (ETDEWEB)

Multi-layer seals are provided that find advantageous use for reducing leakage of gases between adjacent components of electrochemical devices. Multi-layer seals of the invention include a gasket body defining first and second opposing surfaces and a compliant interlayer positioned adjacent each of the first and second surfaces. Also provided are methods for making and using the multi-layer seals, and electrochemical devices including said seals.

Chou, Yeong-Shyung [Richland, WA; Meinhardt, Kerry D [Kennewick, WA; Stevenson, Jeffry W [Richland, WA

2010-09-14

280

Repair of high performance multilayer coatings  

Energy Technology Data Exchange (ETDEWEB)

Fabrication and environmental damage issues may require that the multilayer x-ray reflection coatings used in soft x-ray projection lithography be replaced or repaired. Two repair strategies were investigated. The first was to overcoat defective multilayers with a new multilayer. The feasibility of this approach was demonstrated by depositing high reflectivity (61% at 130 {Angstrom}) molybdenum silicon (Mo/Si) multilayers onto fused silica figured optics that had already been coated with a Mo/Si multilayer. Because some types of damage mechanisms and fabrication errors are not repairable by this method, a second method of repair was investigated. The multilayer was stripped from the optical substrate by etching a release layer which was deposited onto the substrate beneath the multilayer. The release layer consisted of a 1000 {Angstrom} aluminum film deposited by ion beam sputtering or by electron beam evaporation, with a 300 {Angstrom} SiO{sub 2} protective overcoat. The substrates were superpolished zerodur optical flats. The normal incidence x-ray reflectivity of multilayers deposited on these aluminized substrates was degraded, presumably due to the roughness of the aluminum films. Multilayers, and the underlying release layers, have been removed without damaging the substrates.

Gaines, D.P. [Brigham Young Univ., Provo, UT (United States). Dept. of Physics and Astronomy; Ceglio, N.M. [Lawrence Livermore National Lab., CA (United States); Vernon, S.P. [Vernon Applied Physics, Torrance, CA (United States); Krumrey, M.; Mueller, P. [Physikalisch-Technische Bundesanstalt, Berlin (Germany). VUV Radiometric Lab.

1991-07-01

 
 
 
 
281

Recurrent Rotor-Router Configurations  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We prove the existence of recurrent initial configurations for the rotor walk on many graphs, including Z^d, and planar graphs with locally finite embeddings. We also prove that recurrence and transience of rotor walks are invariant under changes in the starting vertex and finite changes in the initial configuration.

Angel, Omer; Holroyd, Alexander E.

2011-01-01

282

Multi-Layer E-Textile Circuits  

Science.gov (United States)

Stitched e-textile circuits facilitate wearable, flexible, comfortable wearable technology. However, while stitched methods of e-textile circuits are common, multi-layer circuit creation remains a challenge. Here, we present methods of stitched multi-layer circuit creation using accessible tools and techniques.

Dunne, Lucy E.; Bibeau, Kaila; Mulligan, Lucie; Frith, Ashton; Simon, Cory

2012-01-01

283

Multilayer Graphene for Waveguide Terahertz Modulator  

DEFF Research Database (Denmark)

We study terahertz to infrared electromagnetic properties of multilayer graphene/dielectric artificial medium and present a novel concept of terahertz modulation at midinfrared wavelengths. This approach allows the realization of high-speed electrically controllable terahertz modulators based on hollow waveguide sections filled with multilayer graphene.

Andryieuski, Andrei; Lavrinenko, Andrei

2014-01-01

284

The damping capacity of a multilayer steel  

Energy Technology Data Exchange (ETDEWEB)

Damping capacities have been compared for multilayer steel specimens (substrate steel AK), which have various strengths in the joints between the layers and various dispositions of the joint zones relative to the surface; a multilayer steel containing a cobalt-base foil has also been examined. With that steel, there is a direct relationship between the strength of the joint and the damping characteristics.

Bovsunovskii, A.P.; Tsykulenko, K.A. [Strength Problems Institute, Kiev (Ukraine)

1995-03-01

285

Dynamic materials from microgel multilayers.  

Science.gov (United States)

Multilayer coatings made from hydrogel microparticles (microgels) are conceptually very simple materials: thin films composed of microgel building blocks held together by polyelectrolyte "glue". However, the apparent simplicity of their fabrication and structure belies extremely complex properties, including those of "dynamic" coatings that display rapid self-healing behavior in the presence of solvent. This contribution covers our work with these materials and highlights some of the key findings regarding damage mechanisms, healing processes, film structure/composition, and how the variation of fabrication parameters can impact self-healing behavior. PMID:24295444

Spears, Mark William; Herman, Emily S; Gaulding, Jeffrey C; Lyon, L Andrew

2014-06-10

286

Polyelectrolyte Multilayers: Towards Single Cell Studies  

Directory of Open Access Journals (Sweden)

Full Text Available Single cell analysis (SCA is nowadays recognized as one of the key tools for diagnostics and fundamental cell biology studies. The Layer-by-layer (LbL polyelectrolyte assembly is a rather new but powerful technique to produce multilayers. It allows to model the extracellular matrix in terms of its chemical and physical properties. Utilization of the multilayers for SCA may open new avenues in SCA because of the triple role of the multilayer film: (i high capacity for various biomolecules; (ii natural mimics of signal molecule diffusion to a cell and (iii cell patterning opportunities. Besides, light-triggered release from multilayer films offers a way to deliver biomolecules with high spatio-temporal resolution. Here we review recent works showing strong potential to use multilayers for SCA and address accordingly the following issues: biomolecule loading, cell patterning, and light-triggered release.

Dmitry Volodkin

2014-05-01

287

Vulvovaginitis candidiasis recurrence during pregnancy.  

Science.gov (United States)

Vulvovaginitis is the most common gynecologic condition seen by practitioners rendering primary care to women. Vulvovaginitis Candidiasis (VVC) is the most common type of vaginitis and this study aimed at specifying VVC recurrence during pregnancy. In this prospective study, 150 pregnant women suffering from vaginal excretion, morsus and itching were studied. Initially, the patients were treated using clotrimazole local cream (5 g) for 7 successive days. After initial treatment, the patients were freely visited once a month until delivery considering vaginitis symptoms and VVC recurrence was examined during pregnancy. Mean age of the understudy mothers was 27.26 +/- 3.76. Mean of recurrence number was 0.17 +/- 0.48 during the first trimester. Mean of recurrence number was 0.92 +/- 0.76 during the second trimester. Mean of recurrence number was 2.16 +/- 0.63 during the third trimester. Statistically significant difference was between recurrences during three trimesters of pregnancy (p < 0.001). There is statistically significant difference between mean number of recurrences during three trimesters of pregnancy. PMID:24199471

Fardiazar, Z; Ronaci, F; Torab, R; Goldust, M

2012-04-15

288

Vulvovaginitis Candidiasis Recurrence During Pregnancy  

Directory of Open Access Journals (Sweden)

Full Text Available Vulvovaginitis is the most common gynecologic condition seen by practitioners rendering primary care to women. Vulvovaginitis Candidiasis (VVC is the most common type of vaginitis and this study aimed at specifying VVC recurrence during pregnancy. In this prospective study, 150 pregnant women suffering from vaginal excretion, morsus and itching were studied. Initially, the patients were treated using clotrimazole local cream (5 g for 7 successive days. After initial treatment, the patients were freely visited once a month until delivery considering vaginitis symptoms and VVC recurrence was examined during pregnancy. Mean age of the understudy mothers was 27.26±3.76. Mean of recurrence number was 0.17±0.48 during the first trimester. Mean of recurrence number was 0.92±0.76 during the second trimester. Mean of recurrence number was 2.16±0.63 during the third trimester. Statistically significant difference was between recurrences during three trimesters of pregnancy (p<0.001. There is statistically significant difference between mean number of recurrences during three trimesters of pregnancy.

R. Torab

2012-01-01

289

Classical and Recurrent Novae  

Science.gov (United States)

The physical nature and principal observational properties of novae are reviewed. Suggested improvments to optical photometry and discovery strategies are discussed. Nova eruptions occur in close binary systems, in which a white dwarf (WD) steadily accretes material on its surface from a lower mass cool companion. The accreted envelope is in electron degenerate conditions and grows steadily in mass with time, until a critical amount is accreted (which is inversely related to the WD mass). At that point, a fast evolving thermo-nuclear runaway starts burning hydrogen, in a short flash lasting about a hundred seconds, which is terminated by the violent ejection into the surrounding space (at a speed in excess of the escape velocity) of the whole accreted envelope (or a sizeable fraction of it). The nova is discovered only when, several hours or a few days later, the expansion and cooling of the fireball ejecta make them emit profusely at optical wavelengths; the later decline in brightness is regulated by interplay between dilution of the ejecta into surrounding space, gas and dust opacities, and temperature/luminosity of the central WD when the ejecta eventually become optically thin. The time interval between consecutive outbursts from the same nova is usually (far) longer than recorded history, but for a small number of objects (named recurrent novae) it is short enough that more than one outburst has been observed for them.

Munari, U.

2012-06-01

290

Recurrence After Operative Management of Intrahepatic Cholangiocarcinoma  

Digital Repository Infrastructure Vision for European Research (DRIVER)

INTRODUCTION: Data on recurrence after operation for intrahepatic cholangiocarcinoma (ICC) are limited. We sought to investigate rates and patterns of recurrence in patients after operative intervention for ICC.

Hyder, O.; Hatzaras, I.; Sotiropoulos, G.; Paul, A.; Alexandrescu, S.; Marques, H.; Pulitano, C.; Barroso, E.; Clary, B.; Aldrighetti, L.; Ferrone, C.; Zhu, A.; Bauer, T.; Walters, D.; Groeschl, R.

2013-01-01

291

Dynamical diffraction in periodic multilayers  

CERN Multimedia

Exact reflectivity curves are calculated numerically for various periodic multilayers using the optical matrix method in order to test the dynamical theory of diffraction. The theory is generally valid for values of the bilayer thickness d up to about 100 A. For somewhat larger values of d, where the theory begins to break down, the initial discrepancy is in the phase of the oscillations in the wings of the peaks. For very large values of d, where the first-order Bragg peak approaches the edge of the mirror reflection, two general types of multilayers can be distinguished. In the first (typified in the present work by Ni/Ti), there is a large (30% or more) reduction in the actual value of the critical wave vector for total reflection while, in the second (typified here by Fe/Ge), there is very little reduction (3 % or so). The origin of these two very different types of behavior is explained. It is also shown that, within the dynamical theory of diffraction, the change in the position of the center of the Dar...

Sears, V F

1997-01-01

292

Imetelstat Sodium in Treating Younger Patients With Recurrent or Refractory Brain Tumors  

Science.gov (United States)

Recurrent Childhood Anaplastic Astrocytoma; Recurrent Childhood Anaplastic Ependymoma; Recurrent Childhood Diffuse Astrocytoma; Recurrent Childhood Ependymoma; Recurrent Childhood Giant Cell Glioblastoma; Recurrent Childhood Glioblastoma; Recurrent Childhood Gliosarcoma; Recurrent Childhood Oligodendroglioma; Recurrent Childhood Brain Stem Glioma

2014-03-21

293

Management Science and Recurrent Education  

Science.gov (United States)

Attempts to apply management science techniques to educational planning. Advocates "recurrent education." Asserts that deterministic linear programing formulations of educational planning models could form a sound base from which to develop toward stochastic representation. (Author/WM)

Houghton, V. P.; Gear, T. E.

1974-01-01

294

Treatment of recurrent biliary pancreatitis  

Directory of Open Access Journals (Sweden)

Full Text Available Objective: The effect of timing of cholecystectomy procedure for the definitive treatment of acute biliary pancreatitis on recurrent episodes is reviewed. Material and Method: 277 patients were admitted to our hospital for acute biliary pancreatitis between January 2007 and January 2009. We reviewed the medical records of 42 patients who have been proven to have a recurrent episode among these 277 patients. Results: Of these 42 patients, 8 (%21 had the recurrent episode within the 8 week interval. The rest had been scheduled for cholecystectomy procedure, however, they either ignored or postponed their appointment, and had the recurrent episode within the long term. Conclusion: We advocate early cholecystectomy that is performed prior to discharge for the definitive treatment of acute biliary pancreatitis, unless the disease have a severe course, and if the procedure can be carried out with acceptable complication rates.

Ahmet Nuray Turhan

2009-01-01

295

Recurrent ameloblastoma of the mandible  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Ameloblastoma is an agressive locally recurring neoplasm of odentogenic epithelium. Here we describe a case of mandibular ameloblastoma with 12 yrs. history of local recurrences followed with history of excision twice (10 yrs. and 7 years back).

Joshi, C. P.; Vyas, K. C.; Deedwania, Seema; Jain, Sanjeev; Mangal, M. M.

1999-01-01

296

Recurrence Quantification of Fractal Structures  

Directory of Open Access Journals (Sweden)

Full Text Available By definition, fractal structures possess recurrent patterns. At different levels repeating patterns can be visualized at higher magnifications. The purpose of this chapter is threefold. First, general characteristics of dynamical systems are addressed from a theoretical mathematical perspective. Second, qualitative and quantitative recurrence analysis is reviewed in brief, but the reader is directed to other sources for explicit details. Third, example mathematical systems that generate strange attractors are explicitly defined, giving the reader the ability to reproduce the rich dynamics of continuous chaotic flows or discrete chaotic iterations. The challenge is then posited for the reader to study for themselves the recurrent structuring of these different dynamics. With a firm appreciation of the power of recurrence analysis, the reader will be prepared to turn their sights on real world systems (physiological, psychological, mechanical, etc..

CharlesWebber

2012-10-01

297

Poincaré recurrences of DNA sequences  

Science.gov (United States)

We analyze the statistical properties of Poincaré recurrences of Homo sapiens, mammalian, and other DNA sequences taken from the Ensembl Genome data base with up to 15 billion base pairs. We show that the probability of Poincaré recurrences decays in an algebraic way with the Poincaré exponent ??4 even if the oscillatory dependence is well pronounced. The correlations between recurrences decay with an exponent ??0.6 that leads to an anomalous superdiffusive walk. However, for Homo sapiens sequences, with the largest available statistics, the diffusion coefficient converges to a finite value on distances larger than one million base pairs. We argue that the approach based on Poncaré recurrences determines new proximity features between different species and sheds a new light on their evolution history.

Frahm, K. M.; Shepelyansky, D. L.

2012-01-01

298

Recurrence for random dynamical systems  

CERN Multimedia

This paper is a first step in the study of the recurrence behavior in random dynamical systems and randomly perturbed dynamical systems. In particular we define a concept of quenched and annealed return times for systems generated by the composition of random maps. We moreover prove that for super-polynomially mixing systems, the random recurrence rate is equal to the local dimension of the stationary measure.

Marie, Philippe

2009-01-01

299

Recurrent limb pain in schoolchildren.  

Digital Repository Infrastructure Vision for European Research (DRIVER)

OBJECTIVES: To determine the prevalence, causes and clinical features of short lasting recurrent limb pain (recurrent limb pain) in children. DESIGN: Population-based study in two stages, with an initial screening questionnaire followed by clinical interviews and physical examination of symptomatic children. SETTING: 67 primary and secondary schools in the city of Aberdeen. SUBJECTS: 2165 children representing a random 10% sample of all schoolchildren aged between 5-15 years. MAIN OUTCOME MEA...

Abu-arafeh, I.; Russell, G.

1996-01-01

300

Tunable optical properties of multilayers black phosphorus  

CERN Document Server

We calculated the optical conductivity tensor of multilayers black phosphorus using the Kubo formula within an effective low-energy Hamiltonian. The optical absorption spectra of multilayers black phosphorus are shown to vary sensitively with thickness, doping, and light polarization. In conjunction with experimental spectra obtained from infrared absorption spectroscopy, we discuss the role of interband coupling and disorder on the observed anisotropic absorption spectra. Multilayers black phosphorus might offer attractive alternatives to narrow gap compound semiconductors for optoelectronics across mid- to near-infrared frequencies.

Low, Tony; Carvalho, A; Jiang, Yongjin; Wang, Han; Xia, Fengnian; Neto, A H Castro

2014-01-01

 
 
 
 
301

Gilbert Damping in Magnetic Multilayers  

CERN Document Server

We study the enhancement of the ferromagnetic relaxation rate in thin films due to the adjacent normal metal layers. Using linear response theory, we derive the dissipative torque produced by the s-d exchange interaction at the ferromagnet-normal metal interface. For a slow precession, the enhancement of Gilbert damping constant is proportional to the square of the s-d exchange constant times the zero-frequency limit of the frequency derivative of the local dynamic spin susceptibility of the normal metal at the interface. Electron-electron interactions increase the relaxation rate by the Stoner factor squared. We attribute the large anisotropic enhancements of the relaxation rate observed recently in multilayers containing palladium to this mechanism. For free electrons, the present theory compares favorably with recent spin-pumping result of Tserkovnyak et al. [Phys. Rev. Lett. \\textbf{88},117601 (2002)].

Simanek, E

2002-01-01

302

Multilayers with tailored blurred interfaces  

International Nuclear Information System (INIS)

Monochromators used in neutron or x-ray experiments often have higher-order contributions, which have to be reduced by filters. Multilayer monochromators produced by dc-magnetron sputtering, with intentionally blurred interfaces, have reduced these higher-order contributions. The approach is to substitute the bilayer structure by several layers with individual thicknesses per period. A Ni/Ti monochromator was prepared where higher-order contributions were reduced below 0.1% of the first-order reflectivity of 93% (measured up to the seventh order). In order to determine the lifetime of such a structure, the interdiffusion of the constituents was measured with thermal annealing (interface diffusion activation energy: 0.16(1) eV)

2006-09-11

303

Ion transport through polyelectrolyte multilayers.  

Science.gov (United States)

Polyelectrolyte multilayer (PEM) films and capsules loaded with ion-sensitive fluorophores can be used as ion-sensors for many applications including measurements of intracellular ion concentration. Previous studies have shown the influence of the PEM films/shells on the specific response of encapsulated ion-sensitive fluorophores. PEM shells are considered as semipermeable barriers between the environment and the encapsulated fluorophores. Parameters such as the time response of the encapsulated sensor can be affected by the porosity and charge of the PEM shell. In this study, the time response of an encapsulated pH-sensitive fluorophore towards pH changes in the surrounding environment is investigated. Furthermore, the conductance of PEM films for potassium ions is determined. PMID:24327382

Carregal-Romero, Susana; Rinklin, Philipp; Schulze, Susanne; Schäfer, Martin; Ott, Andrea; Hühn, Dominik; Yu, Xiang; Wolfrum, Bernhard; Weitzel, Karl-Michael; Parak, Wolfgang J

2013-12-01

304

Thermionic cooling in semiconductor multilayers  

International Nuclear Information System (INIS)

Full text: A solid-state refrigerator in which electrons transport heat has advantages over the conventional vapour-cycle, compressor-based domestic refrigerator since it has no moving parts, it is low-maintenance, silent, vibration-free and does not require the use of refrigerant gases. The usual approach to making an all-electrical refrigerator is by thermoelectric refrigeration. After a period of intense research in the 1950s and 60s it was realised that the efficiency of thermoelectric devices was less than, and unlikely to exceed, that of conventional compressor units. While thermoelectric cooling has found specialised applications in cases where reliability, compactness and weight are important considerations, it does not appear that thermo-electrics will ever successfully compete in the domestic market, in spite of recent advances in the design and fabrication of thermoelectric materials. A new approach to an all-electric refrigerator is to employ thermionic emission over potential barriers. A key difference between a thermoelectric device and a thermionic device is that in the former the electrons are scattered in their motion and in the latter they are not. Thus thermionic cooling, in principle, can be much more efficient than thermoelectric cooling. A radical new realisation of the thermionic refrigerator was suggested recently in which a multilayer semiconductor structure would be used. We discuss the optimisation of such a multilayer semiconductor cooling system by considering (1) electron-phonon interactions in the barriers and electrodes; (2) the detailed treatment of thermal conductivity; (3) an exact numerical solution of the heat and energy currents (in contrast to the previous approximate analytic solutions); (4) the effect of varying layer thickness across the device; and (5) the effect of varying current density across the device

2000-12-10

305

Highly Efficient Multilayer Thermoelectric Devices  

Science.gov (United States)

Multilayer thermoelectric devices now at the prototype stage of development exhibit a combination of desirable characteristics, including high figures of merit and high performance/cost ratios. These devices are capable of producing temperature differences of the order of 50 K in operation at or near room temperature. A solvent-free batch process for mass production of these state-of-the-art thermoelectric devices has also been developed. Like prior thermoelectric devices, the present ones have commercial potential mainly by virtue of their utility as means of controlled cooling (and/or, in some cases, heating) of sensors, integrated circuits, and temperature-critical components of scientific instruments. The advantages of thermoelectric devices for such uses include no need for circulating working fluids through or within the devices, generation of little if any noise, and high reliability. The disadvantages of prior thermoelectric devices include high power consumption and relatively low coefficients of performance. The present development program was undertaken in the hope of reducing the magnitudes of the aforementioned disadvantages and, especially, obtaining higher figures of merit for operation at and near room temperature. Accomplishments of the program thus far include development of an algorithm to estimate the heat extracted by, and the maximum temperature drop produced by, a thermoelectric device; solution of the problem of exchange of heat between a thermoelectric cooler and a water-cooled copper block; retrofitting of a vacuum chamber for depositing materials by sputtering; design of masks; and fabrication of multilayer thermoelectric devices of two different designs, denoted I and II. For both the I and II designs, the thicknesses of layers are of the order of nanometers. In devices of design I, nonconsecutive semiconductor layers are electrically connected in series. Devices of design II contain superlattices comprising alternating electron-acceptor (p)-doped and electron-donor (n)-doped, nanometer- thick semiconductor layers.

Boufelfel, Ali

2006-01-01

306

Review of the multilayer coating model  

CERN Document Server

The recent theoretical study on the multilayer-coating model published in Applied Physics Letters [1] is reviewed. Magnetic-field attenuation behavior in a multilayer coating model is different from a semi-infinite superconductor and a superconducting thin film. This difference causes that of the vortex-penetration field at which the Bean-Livingston surface barrier disappears. A material with smaller penetration depth, such as a pure Nb, is preferable as the substrate for pushing up the vortex-penetration field of the superconductor layer. The field limit of the whole structure of the multilayer coating model is limited not only by the vortex-penetration field of the superconductor layer, but also by that of the substrate. Appropriate thicknesses of superconductor and insulator layers can be extracted from contour plots of the field limit of the multilayer coating model given in Ref.[1].

Kubo, Takayuki; Saeki, Takayuki

2014-01-01

307

Design of multilayered systems with desirable properties  

CERN Multimedia

We present an analytical method to deal with multilayered systems (MSs), which helps to design them with desirable properties. In particular, we show how to prepare a periodic MS with forbidden second-order Bragg diffraction. (orig.)

Ignatovich, V K

2002-01-01

308

Plasma etchback of multilayer printed wiring boards  

Energy Technology Data Exchange (ETDEWEB)

Removal of epoxy smear and glass fiber protrusions in multilayer printed wiring board holes was investigated. Gas plasma techniques, using a mixture of carbon tetrafluoride and oxygen, removed the eposies; however, the glass fibers were not affected.

Gentry, F.L.

1980-06-01

309

Local Recurrence of Osteosarcoma After 17 Years  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The recurrence of osteosarcoma is rare. Local recurrence occurs in 4–10% of patients following effective treatment. So far, recurrences as late as 15 years have been reported in the literature. We report a unique case of local recurrence of intramedullary osteosarcoma 17 years from initial diagnosis and treatment. Regular long-term follow-up of patients with this diagnosis is crucial to ensure early detection and treatment of potential recurrences.

2009-01-01

310

Local recurrence of osteosarcoma after 17 years.  

Science.gov (United States)

The recurrence of osteosarcoma is rare. Local recurrence occurs in 4-10% of patients following effective treatment. So far, recurrences as late as 15 years have been reported in the literature. We report a unique case of local recurrence of intramedullary osteosarcoma 17 years from initial diagnosis and treatment. Regular long-term follow-up of patients with this diagnosis is crucial to ensure early detection and treatment of potential recurrences. PMID:19416582

Welck, M J; Gikas, P D; Pearce, P; Bhumbra, R; Briggs, T W R; Cannon, S

2009-05-01

311

Multilayer recording in microholographic data storage  

Science.gov (United States)

The potential of multilayer recording in microholographic data storage is investigated. Micrometer-scaled depth localization of resolution-limited microgratings is achieved in photopolymers sensitized to green and violet light. Confocal readout results in an optical depth of approximately 2 ?m. The spatial Bragg selectivity of resolution-limited micrograting structures allows reducing their longitudinal depth spacing down to 4 ?m. Multilayer recording is demonstrated as depth multiplexing of microgratings written in 50 layer locations within a 300 ?m thick photopolymer.

Orlic, Susanna; Rass, Jens; Dietz, Enrico; Frohmann, Sven

2012-07-01

312

Nuclear multilayer structure with antireflection coating  

International Nuclear Information System (INIS)

A combined application of resonant Bragg diffraction by nuclear multilayer structure and specular antireflection by coating film to provide a beam of synchrotron radiation with super narrow ?E/E = 10-11 bandwidth is studied. A proposed structure includes two antireflecting films above and below the nuclear multilayer. Computer simulation shows the possibility to reach a high nuclear reflectivity with a suppression of electronic scattering down to 4x10-7 at the angular position of nuclear Bragg reflection

1993-08-01

313

The visco-elastic multilayer program VEROAD:  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The mathematical principles and derivation of a linear visco-elastic multilayer computer program are described. The mathematical derivation is based on Fourier Transformation. The program is called VEROAD, which is an acronym for Visco-Elastic ROad Analysis Delft. The program allows calculation of physical quantities like time-dependent displacements, stresses and strains, permanent deformations and dissipated energies in a multi-layer system built of visco-elastic materials. All the quantiti...

1996-01-01

314

Design and properties of multilayered ceramic composites  

Energy Technology Data Exchange (ETDEWEB)

The design of multilayered ceramic composites is reviewed, with the aim of relating the properties that can be achieved to the microstructure of the composite. Limitations on some properties, such as damage tolerance and strength, are discussed. Failure mechanism maps that define some of these limits are given. The purpose of the multilayered microstructure is to make use of interactions between the layers to introduce nonlinear behavior and thereby overcome the inherent brittleness of the materials within the individual layers.

Marshall, D.B. [Rockwell Science Center, Thousand Oaks, CA (United States)

1996-12-31

315

Multilayer Nanofilms as Substrates for Hepatocellular Applications  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Multilayer nanofilms, formed by the layer-by-layer (LbL) adsorption of positively and negatively charged polyelectrolytes, are promising substrates for tissue engineering. We investigate here the attachmemt and function of hepatic cells on multilayer films in terms of film composition, terminal layer, rigidity, charge, and presence of biofunctional species. Human hepatocellular carcinoma cells (HepG2), adult rat hepatocytes (ARH), and human fetal hepatoblasts (HFHb) are studied on films compo...

Wittmer, Corinne R.; Phelps, Jennifer A.; Lepus, Christin M.; Saltzman, W. Mark; Harding, Martha J.; Tassel, Paul R.

2008-01-01

316

Histopathological evaluation of recurrent goiter.  

Science.gov (United States)

The recurrent goiter is the regrowth of thyroid tissue after thyroidectomy. An inadequate surgical removal of the thyroid gland, lack of substitution therapy and pathological stimulation of the thyroid growth can all promote the recurrence. The aim of this study was to find the connection between the histopathological findings during the first and second operation and the recurrence of goiter. The study group consisted of 29 women and 1 man. The mean time to recurrence was 15 years. The most frequent histopathological finding during the first and second operation was struma nodosa. According to our observations different histopathological findings were found in 63.4% cases after primary and secondary thyroidectomy. Some genetic investigations showed that nodules in recurrent goiters did not derive from nodules left during the first operation but from a group of cells which had high growth potential. Thus, not only the operation technique and substitution after operation are key factors of successful therapy of goiter, but also other factors which stimulate the re-growth of thyroid tissue. PMID:21071350

Rudnicki, J; Agrawal, A K; Jelen, M; Sebastian, M; Sroczy?ski, M; Zy?ko, D

2010-09-30

317

Recurrence Statistics of Great Earthquakes  

CERN Multimedia

We investigate the sequence of great earthquakes over the past century. To examine whether the earthquake record includes temporal clustering, we identify aftershocks and remove those from the record. We focus on the recurrence time, defined as the time between two consecutive earthquakes. We study the variance in the recurrence time and the maximal recurrence time. Using these quantities, we compare the earthquake record with sequences of random events, generated by numerical simulations, while systematically varying the minimal earthquake magnitude Mmin. Our analysis shows that the earthquake record is consistent with a random process for magnitude thresholds 7.0<=Mmin<=8.3, where the number of events is larger. Interestingly, the earthquake record deviates from a random process at magnitude threshold 8.4<=Mmin<= 8.5, where the number of events is smaller; however, this deviation is not strong enough to conclude that great earthquakes are clustered. Overall, the findings are robust both qualitat...

Ben-Naim, E; Johnson, P A

2013-01-01

318

Pigmented villonodular synovitis: extrasynovial recurrence.  

Science.gov (United States)

A 32-year-old female athlete underwent arthroscopy for a second recurrence of pigmented villonodular synovitis (PVNS), which was extrasynovial, seen on magnetic resonance imaging. It was noted on arthroscopy that (1) the nodules moved medially with joint insufflation, (2) the nodules were less prominent than on magnetic resonance imaging, and (3) more than 95% of the recurrent tumor was hidden by neosynovium. We believe that the extrasynovial location is because of the more rapid proliferation of the neosynovium relative to the growth of the remaining tumor cells after the previous resection. In resecting pigmented villonodular synovitis with a high risk of recurrence, a layer of periarticular fat should be removed and the surgeon should be wary of change in position with insufflation. PMID:21889289

Jobe, Christopher M; Raza, Anwar; Zuckerman, Lee

2011-10-01

319

Learning temporal dependencies in connectionist speech recognition  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Hybrid connectionist/HMM systems model time using both a Markov chain and through properties of a connectionist network. In this paper, we discuss the nature of the time dependence currently employed in our systems using recurrent networks (RNs) and feed-forward multi-layer perceptrons (MLPs). In particular, we introduce local recurrences into an MLP to produce an enhanced input representation. This is in the form of an adaptive gamma filter and incorporates an automatic approach for learning...

Renals, Steve; Hochberg, Mike; Robinson, Tony

1994-01-01

320

[Sclerotherapy for recurrent glomus tumors].  

Science.gov (United States)

We report the cases of two women aged 28 and 34 years who presented recurrent glomus tumors of the hand after surgery for marginal resection of the tumor mass. The pathological study of the surgical specimen confirmed the diagnosis of recurrent glomus tumor. Due to the vascular origin of this tumor, sclerotherapy was delivered. The functional outcomes were good with dramatic pain relief within a few days. At 3-year mean follow-up, the cosmetic and functional results were very satisfactory. PMID:23660495

Benchakroun, M; Zaddoug, O; Boussouga, M; Boukhris, J; Jaafar, A

2013-05-01

 
 
 
 
321

Classical and Recurrent Nova Outbursts  

CERN Document Server

Over the last 40 years, multi-frequency observations, coupled with advances in theoretical modelling, have led to a much fuller understanding of the nova phenomenon. Here I give a brief review of the current state of knowledge of Classical and Recurrent Novae including their central systems; the causes and consequences of their outbursts; sub-types, and possible relationships to Type Ia Supernovae. Particular attention is paid to the Recurrent Nova RS Ophiuchi as it shows a wealth of phenomena associated with its 2006 outburst. Finally, some open questions and avenues for future work are summarised.

Bode, M F

2011-01-01

322

Galactosemia presenting as recurrent sepsis.  

Science.gov (United States)

Galactosemia is a treatable metabolic disorder caused by the deficiency of enzyme galactose-1-phosphate uridyl transferase (GALT) and inherited as an autosomal recessive trait. A case of neonate manifesting with recurrent Escherichia coli sepsis is presented here which turned out to be a classic galactosemia. No other common presenting features were observed in this infant except cataract on slit lamp examination. To the best of our knowledge, there is no case of galactosemia reported in literature which presented with recurrent neonatal sepsis without hepatomegaly, hyperbilirubinemia, bleeding disorder, vomiting, diarrhea, failure to thrive, hypoglycemia, coagulopathy, hemolysis or renal tubular acidosis. PMID:21321007

Rathi, Narendra; Rathi, Akanksha

2011-12-01

323

Ellipsometric monitoring of multilayer coatings  

Science.gov (United States)

The spectral performance requirements of optical thin film coatings continue to be increasingly demanding. Optical thin film design programs are now so sophisticated that they can meet the majority of these specifications. However, producing these designs is often very difficult. Many of the resulting designs have many layers (>50) of unequal optical thicknesses (non-quarter-waves) including both very thin layers (thick layers. The tolerances on layer thicknesses and refractive indices are usually very tight (coatings range from crystal oscillator thickness and rate monitoring, time monitoring for sputtered films, single- wavelength turning point monitoring (particularly narrow-band interference filters such as DWDMs), and multiwavelength monitoring for multilayers having complex designs with possible real time re-optimization. This presentation will describe the use of ellipsometry for optical monitoring. Advantages of the technique are that both refractive index and thickness are measured during deposition, meaning that accurate design re-optimization is possible after each layer is terminated. Very thin layers can be measured accurately, and unlike photometric monitoring the technique has high sensitivity for all layer thicknesses. Examples will be given that illustrate the advantages of ellipsometric monitoring, including a laser notch plus band-blocker filter and a very broadband antireflection coating.

Netterfield, Roger P.

2005-09-01

324

Topographic eddies in multilayer flow  

Science.gov (United States)

This paper considers the evolution of an inviscid initially uniform multilayer flow passing over a flat-topped cylindrical obstacle in a rotating system. The quasigeostrophic flow field at any instant is determined solely by the position at that time of the boundary of the region in the bottom layer containing fluid originally above the cylinder. Contour dynamics is used to follow numerically the development of this boundary. For a fast oncoming flow the boundary is swept downstream, enclosing a vortex, whereas for a slower flow some fluid remains trapped above the topography. The critical value of the relevant trapping parameter, ?/Ro (where ? is the fractional height of the obstacle and Ro is a Rossby number for the flow), and its dependence on layer depths and the Rossby radius of deformation are calculated for two-layer flows. It is shown that trapping of fluid is inhibited as the horizontal extent of the obstacle increases (relative to the Rossby radius)_or as ?/Ro decreases. The problem is extended to the case of a sheared oncoming flow, and to the possible capture of incident eddies from upstream.

Davey, M. K.; Hurst, R. G. A.; Johnson, E. R.

1993-06-01

325

Supraclavicular recurrence of breast cancer  

International Nuclear Information System (INIS)

Between January 1970 and December 1978 39 patients with isolated supraclavicular recurrence of breast cancer were referred to the Department of Radiotherapy and Radiobiology, University of Vienna. All patients have had mastectomy as primary treatment. In 46% of the patients a surgical excision of involved lymph node has been performed before irradiation. The median interval between mastectomy and supraclavicular recurrence was 26 months. The cumulative incidence after three years was 75%. 15 patients have shown complete local response during the whole follow-up time. In 38 patients, osseous and/or visceral metastasis were observed after a median interval of eight months. After two years, 87% of the patients presented distant disease. 15 patients suffered on local pain in the supraclavicular region or in the ipsilateral shoulder with lymph oedema of the arm. The median survival after therapy was 18 months. The death rate after three years was 77%. Patients with a recurrence-free intervall after mastectomy less than two years had a median survival time of eleven months whereas patients with a recurrence-free interval had 26 months. (orig.)

1990-01-01

326

[Ovarian irradiation in recurrent endometriosis].  

Science.gov (United States)

We describe a case of a young woman with a history of an aplastic anaemia in which pelvic radiotherapy was used successfully in the management of a recurrent and inoperable endometriosis. The use of therapeutic pelvic or ovarian irradiation in endometriosis may be considered, when surgical and medical treatments have been exhausted and have failed. PMID:16176883

Kochbati, L; Chaari, N; Néji, K; Ben Romdhane, N-K; Ben Amara, F; Besbes, M; Maalej, M

2005-09-01

327

Ovarian irradiation in recurrent endometriosis  

International Nuclear Information System (INIS)

We describe a case of a young woman with a history of an aplastic anaemia in which pelvic radiotherapy was used successfully in the management of a recurrent and inoperable endometriosis. The use of therapeutic pelvic or ovarian irradiation in endometriosis may be considered, when surgical and medical treatments have been exhausted and have failed. (authors)

2005-09-01

328

Gadolinium induced recurrent acute pancreatitis.  

Science.gov (United States)

Acute pancreatitis is a sudden swelling and inflammation of the pancreas. The two most common causes are alcohol use and biliary stones. Drug-induced acute pancreatitis are rare (1.4-2%). In this present study, we present a case of recurrent acute pancreatitis induced by a specific magnetic-resonance-imaging (MRI) contrast agent called gadobenate dimeglumine. PMID:23395575

Blasco-Perrin, H; Glaser, B; Pienkowski, M; Peron, J M; Payen, J L

2013-01-01

329

Recurrent meningitis due to epidermoid  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Aseptic meningitis is characterized by noninfective serous inflammation of the meninges. It can occur in a recurrent fashion when associated with dermoid and epidermoid cysts due to rupture of cyst contents into subarachnoid space resulting in aseptic chemical meningitis. Bacterial meningitis in association with these tumors is commonly related to a coexisting dermal sinus tract and the most common organism is Staphylococcus aureus.

Cherian, Ajith; Baheti, Neeraj N.; Easwar, H. V.; Nair, Divya S.; Iype, Thomas

2012-01-01

330

Recurrent asymptomatic right atrial myxoma.  

Science.gov (United States)

Cardiac myxoma is the most common primary tumor of the heart. The clinical presentation ranges from asymptomatic to symptomatic with constitutional symptoms, obstructive symptoms, or evidence of embolism. Most cases are sporadic; recurrence rates are low after surgical excision for these cases. We present a case of an asymptomatic right atrial myxoma which recurred 1 year after its resection. PMID:21045771

Funk, Michael; Santana, Orlando; Lamelas, Joseph

2010-01-01

331

Pseudoprimes in certain linear recurrences.  

Directory of Open Access Journals (Sweden)

Full Text Available Let b > 1 be a ?xed positive integer. We study the distributionof pseudoprimes to base b in certain linear recurrence sequences. We prove,in e?ective form, that most terms of these sequences are not pseudoprimes tobase b.

Florian Luca

2007-09-01

332

Recurrent processing during object recognition  

Directory of Open Access Journals (Sweden)

Full Text Available How does the brain learn to recognize objects visually, and perform this difficult feat robustly in the face of many sources of ambiguity and variability? We present a computational model based on the biology of the relevant visual pathways that learns to reliably recognize 100 different object categories in the face of of naturally-occurring variability in location, rotation, size, and lighting. The model exhibits robustness to highly ambiguous, partially occluded inputs. Both the unified, biologically plausible learning mechanism and the robustness to occlusion derive from the role that recurrent connectivity and recurrent processing mechanisms play in the model. Furthermore, this interaction of recurrent connectivity and learning predicts that high-level visual representations should be shaped by error signals from nearby, associated brain areas over the course of visual learning. Consistent with this prediction, we show how semantic knowledge about object categories changes the nature of their learned visual representations, as well as how this representational shift supports the mapping between perceptual and conceptual knowledge. Altogether, these findings support the potential importance of ongoing recurrent processing throughout the brain's visual system and suggest ways in which object recognition can be understood in terms of interactions within and between processes over time.

DeanWyatte

2013-04-01

333

Recurrence Formulas for Fibonacci Sums  

CERN Document Server

In this article we present a new recurrence formula for a finite sum involving the Fibonacci sequence. Furthermore, we state an algorithm to compute the sum of a power series related to Fibonacci series, without the use of term-by-term differentiation theorem

Brandao, Adilson J V

2008-01-01

334

A Recurrent Neural Network Approach to Rear Vehicle Detection Which Considered State Dependency  

Directory of Open Access Journals (Sweden)

Full Text Available Experimental vision-based detection often fails in cases when the acquired image quality is reduced by changing optical environments. In addition, the shape of vehicles in images that are taken from vision sensors change due to approaches by vehicle. Vehicle detection methods are required to perform successfully under these conditions. However, the conventional methods do not consider especially in rapidly varying by brightness conditions. We suggest a new detection method that compensates for those conditions in monocular vision-based vehicle detection. The suggested method employs a Recurrent Neural Network (RNN, which has been applied for spatiotemporal processing. The RNN is able to respond to consecutive scenes involving the target vehicle and can track the movements of the target by the effect of the past network states. The suggested method has a particularly beneficial effect in environments with sudden, extreme variations such as bright sunlight and shield. Finally, we demonstrate effectiveness by state-dependent of the RNN-based method by comparing its detection results with those of a Multi Layered Perceptron (MLP.

Kayichirou Inagaki

2003-08-01

335

Does circumcision influence recurrences in herpes genitalis?  

Directory of Open Access Journals (Sweden)

Full Text Available Background and Aims: The effect of therapeutic circumcision in men for preventing recurrences of herpes genitalis remains largely unelucidated despite its well documented albeit conflicting role in reducing the risk of acquiring sexually transmitted infections, including genital herpes. Methods: Twenty volunteer adult males with a history of recurrent herpes genitalis were included in the study after informed consent and circumcision was carried out. Twenty more adult males having recurrent herpes genitalis and registered in the clinic during the same period were selected as controls. All patients and controls were followed-up for recurrences of herpes genitalis. Results and Conclusions: Six patients and six controls did not follow-up. Seven patients reported no recurrences during 3-18 years, seven patients had two to six recurrences during 11-27 years of postcircumcision follow-up, 0.0080 (average recurrences per person per year as compared with 0.20 (average recurrences per person per year recorded before the circumcision. Two patients had first recurrence 11 years after the circumcision. In comparison, 14 controls had 0.17 (average recurrences per person per year, comparable with the number of recurrences in uncircumcised patients, and frequently at shorter intervals. Despite being a small study, the circumcision appears to reduce the number of recurrences on an average and evidently prolongs the disease-free period in between two recurrences.

Jerath V

2009-01-01

336

Perceptron Learning of SAT  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Boolean satisfiability (SAT) as a canonical NP-complete decision problem is one of the most important problems in computer science. In practice, real-world SAT sentences are drawn from a distribution that may result in efficient algorithms for their solution. Such SAT instances are likely to have shared characteristics and substructures. This work approaches the exploration of a family of SAT solvers as a learning problem. In particular, we relate polynomial time solvability of a SAT subset t...

Flint, Alex; Blaschko, Matthew

2012-01-01

337

Genetics Home Reference: Benign recurrent intrahepatic cholestasis  

Science.gov (United States)

... benign recurrent intrahepatic cholestasis? Benign recurrent intrahepatic cholestasis (BRIC) is characterized by episodes of liver dysfunction called ... a lack of appetite. A common feature of BRIC is the reduced absorption of fat in the ...

338

Recurrent and non-recurrent trajectories in a chaotic system  

Directory of Open Access Journals (Sweden)

Full Text Available The dynamics of a system subjected to a potential equal to the sum of the Henon-Heiles potential and that of thehydrogen atom in a uniform magnetic field has been studied. Depending on the energy of the system, the Poincaresurface is characterised by regions of regular motion, appearing and disappearing regions of regular motion, regions ofrecurrent (regular and chaotic trajectories and those of non-recurrent trajectories.

A. O. Akala

2010-09-01

339

Recurrent MRSA skin infections in atopic dermatitis.  

Science.gov (United States)

Methicillin-resistant Staphylococcus aureus (MRSA) is a frequent cause of recurrent skin and soft tissue infections. For patients with atopic dermatitis, recurrent skin infections with MRSA often lead to eczema exacerbation. There currently is no standard practice in the prevention of recurrent MRSA soft tissue infections in the general and the atopic dermatitis populations. The current article reviews recent data on S aureus decolonization treatments for the prevention of recurrent MRSA soft tissue infections in the community setting. PMID:25017526

Ong, Peck Y

2014-01-01

340

Risk factors that affect recurrence in strokes  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Introduction: Recurrent stroke is defined as a new cerebrovascular event which occurs after the stabilization of the previous stroke. Recurrence of stroke increases likelihood of disability-mortality associated with stroke. Systematic evaluation of stroke cases can help to reduce the risk of recurrence. Objective: In order to predict strokes which carry the risk of recurrence, we aimed to compare data related to risk factors, stroke type, etiology and disability-mortality rates associated wit...

Sema Demirci; Yalc??ner, Betu?l Z.; Göksel Bakaç; Cengiz Dayan; Fikret Aysal; Sevim Bayba?

2010-01-01

 
 
 
 
341

Thermal performance of multilayer insulation. Part 2  

International Nuclear Information System (INIS)

A new heat-flux model that is able to explain the two thermal-conduction terms in the prediction-based heat-flux equation of multilayer insulation is proposed. Based on the new model, the expansion and applicability of the equation to various parameters of multilayer insulation are examined in detail. The prediction equation was derived from various parameters and the predicted heat-flux values were evaluated. The treatment parameters were the mesh size of the net, the number of layers of net inserted between films, film thickness, single- vs. double-aluminized films, the winding method for the multilayer insulation, the layer density, and the hot and cold boundary temperatures. Predicted values for the various parameters coincided well with measured values

1995-05-01

342

Magnetic characterization of U/Co multilayers  

Energy Technology Data Exchange (ETDEWEB)

With the aim of expanding the studies on 2D systems containing uranium, U/Co multilayers with layer thickness ranging from 50 to 200 A were recently prepared by dc magnetron sputtering onto glass. The multilayers were characterized by Grazing-Incidence X-Ray Diffraction (GIXRD) and Rutherford Backscattering Spectrometry (RBS). Magnetization measurements performed with a squid magnetometer showed that the multilayers have a ferromagnetic behaviour, with the magnetic signal increasing with the thickness of the layers. The analysis of magnetic anisotropy evidenced an easy magnetic direction in the film plane with large anisotropy fields, which increase with the thickness of the layers and suggests a positive contribution of surface anisotropy to the effective anisotropy K{sub eff}. (Abstract Copyright [2003], Wiley Periodicals, Inc.)

Rosa, M.A.; Diego, M. [Departamento de Quimica, Instituto Tecnologico e Nuclear, P-2686-953 Sacavem (Portugal); Departamento de Fisica, Faculdade de Ciencias da Universidade de Lisboa, Ed. C8 Campo Grande, P-1749-016 Lisboa (Portugal); Alves, E.; Barradas, N.P. [Departamento de Fisica, Instituto Tecnologico e Nuclear, P-2686-953 Sacavem (Portugal); Godinho, M. [Departamento de Fisica, Faculdade de Ciencias da Universidade de Lisboa, Ed. C8 Campo Grande, P-1749-016 Lisboa (Portugal); Almeida, M.; Goncalves, A.P. [Departamento de Quimica, Instituto Tecnologico e Nuclear, P-2686-953 Sacavem (Portugal)

2003-03-01

343

Multilayer neural networks a generalized net perspective  

CERN Document Server

The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a special sort of the optimal control problem. In this way, the optimal control problem methodology, like dynamic programming, with modifications, can yield a new class of learning algorithms for multilayer neural networks. Another purpose of this book is to show that the generalized net theory can be successfully used as a new description of multilayer neural networks. Several generalized net descriptions of neural networks functioning processes are considered, namely: the simulation process of networks, a system of neural networks and the learning algorithms developed in this book. The generalized net approach to modelling of real systems may be used successfully for the description of a variety of technological and intellectual problems, it can be used not only for representing the parallel functioning of homogen...

Krawczak, Maciej

2013-01-01

344

Imaging Schwarzschild multilayer X-ray microscope  

Science.gov (United States)

We have designed, analyzed, fabricated, and tested Schwarzschild multilayer X-ray microscopes. These instruments use flow-polished Zerodur mirror substrates which have been coated with multilayers optimized for maximum reflectivity at normal incidence at 135 A. They are being developed as prototypes for the Water Window Imaging X-Ray Microscope. Ultrasmooth mirror sets of hemlite grade sapphire have been fabricated and they are now being coated with multilayers to reflect soft X-rays at 38 A, within the biologically important 'water window'. In this paper, we discuss the fabrication of the microscope optics and structural components as well as the mounting of the optics and assembly of the microscopes. We also describe the optical alignment, interferometric and visible light testing of the microscopes, present interferometrically measured performance data, and provide the first results of optical imaging tests.

Hoover, Richard B.; Baker, Phillip C.; Shealy, David L.; Core, David B.; Walker, Arthur B. C., Jr.; Barbee, Troy W., Jr.; Kerstetter, Ted

1993-01-01

345

Mucosal irritation potential of polyelectrolyte multilayer capsules.  

Science.gov (United States)

Polyelectrolyte multilayer capsules have recently gained interest as carriers for drug delivery. When envisioning mucosal administration, one is focused with potential concerns such as tissue irritation and tissue damage, induced by the carrier itself. In this paper we demonstrate the use of a slug-based (Arion lusitanicus) assay to evaluate the mucosal irritation potential of different types of polyelectrolytes, their complexes and multilayer capsules. This assay allows to assess in a simple yet efficient way mucosal tissue irritation without using large numbers of vertebrates such as mice, rabbits or non-human primates. We found that although single polyelectrolyte components do induce tissue irritation, this response is dramatically reduced upon complexation with an oppositely charged polyelectrolyte, rendering fairly inert polyelectrolyte complexes. These findings put polyelectrolyte multilayer capsules further en route towards drug delivery applications. PMID:21126762

De Cock, Liesbeth J; Lenoir, Joke; De Koker, Stefaan; Vermeersch, Vincent; Skirtach, Andrei G; Dubruel, Peter; Adriaens, Els; Vervaet, Chris; Remon, Jean Paul; De Geest, Bruno G

2011-03-01

346

Noncommutative recurrence over locally compact Hausdorff groups  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We extend previous results on noncommutative recurrence in unital *-algebras over the integers, to the case where one works over locally compact Hausdorff groups. We derive a generalization of Khintchine's recurrence theorem, as well as a form of multiple recurrence. This is done using the mean ergodic theorem in Hilbert space, via the GNS construction.

Beer, Richard; Duvenhage, Rocco; Stroh, Anton

2005-01-01

347

Treatment Strategy for Recurrent Multiple Hepatocellular Carcinoma  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Hepatocellular carcinoma (HCC) has some unique characteristics in the digestive organ cancer. Therefore it is very important to select an appropriate treatment for recurrent HCC according to several situations such as the type of recurrence, previous treatments and conditions of patient. This article is a review of the concept of recurrent multiple HCC and its therapeutic strat...

Toru Ishikawa

2013-01-01

348

Recurrent Idiopathic Facial Paralysis: A Case Report  

Directory of Open Access Journals (Sweden)

Full Text Available Idiopathic facial paralysis is the mononeuropathy Multiple recurrences of idiopathic facial paralysis in a patient may be the sign or sympton of a serious illness. therefore; in recurrent cases, family history, systemic diseases and malignancy must be investigated. In this report, a case of recurrent idiopathic facial paralysis is presented.

Hale Hekim Balo?lu

2010-09-01

349

Yield stress and scaling of polyelectrolyte multilayer modified suspensions: effect of polyelectrolyte conformation during multilayer assembly.  

Science.gov (United States)

The yield stress of polyelectrolyte multilayer modified suspensions exhibits a surprising dependence on the polyelectrolyte conformation of multilayer films. The rheological data scale onto a universal master curve for each polyelectrolyte conformation as the particle volume fraction, ?, and the ionic strength of the background fluid, I, are varied. It is shown that rough films with highly coiled, brushy polyelectrolytes significantly enhance the yield stress. Moreover, via the ionic strength I of the background fluid, the dynamic yield stress of brushy polyelectrolyte multilayers can be finely adjusted over 2 decades. PMID:23952570

Hess, Andreas; Aksel, Nuri

2013-09-10

350

Calculation of nuclear resonant scattering spectra of magnetic multilayers  

International Nuclear Information System (INIS)

Calculations of the angle- and time-dependent photon reflectivity of multilayers are presented, using the technique of characteristic matrices. Spectra of 56Fe/57Fe and Cr/57Fe multilayers are calculated under various conditions. The parameters of the multilayers are optimized for suitable test samples of reflectometry measurements. (author) 10 refs.; 6 figs

1993-08-08

351

Multilayer recording in microholographic data storage  

International Nuclear Information System (INIS)

The potential of multilayer recording in microholographic data storage is investigated. Micrometer-scaled depth localization of resolution-limited microgratings is achieved in photopolymers sensitized to green and violet light. Confocal readout results in an optical depth of approximately 2 ?m. The spatial Bragg selectivity of resolution-limited micrograting structures allows reducing their longitudinal depth spacing down to 4 ?m. Multilayer recording is demonstrated as depth multiplexing of microgratings written in 50 layer locations within a 300 ?m thick photopolymer. (fast track communication)

2012-07-01

352

Developments in ion-assisted multilayer coatings  

Science.gov (United States)

The advantages of high current, low voltage ion assisted deposition (IAD) previously demonstrated for single layer films were extended to complex multilayer oxide coatings for medium to large scale applications. Optimization of the IAD parameters led to low absorptance coatings from the IR to the UV. Stress adjustment and matching of layers provided greater cohesive strength and mechanical integrity throughout the stacks. In addition near bulk indices gave enhanced optical performance. Examples of multilayer high reflector stacks for UV, visible, and near IR laser application are given with emphasis on absorption, optical performance in band, elimination of physisorbed water, and at the waterband, environmental stability, and coating durability.

Culver, Thomas R.; Pawlewicz, Walter T.; Zachistal, John H.; McCandless, James A.; Chiello, Michael W., Sr.; Walters, Sherman R.

1993-06-01

353

YBCO based multilayers for optoelectronic devices  

International Nuclear Information System (INIS)

YBCO based multilayers have been deposited independently by three techniques: laser ablation, inverted cylindrical target sputtering (ICM) and on-axis planar D.C. Magnetron Sputtering. The last technique is used to cover uniformly R-plane sapphire and LaAlO3 2 inch wafers with YBCO or multilayers to achieve optoelectronic devices such as infrared detectors. Very thin (- 3 nm) YSZ and MgO dielectric films have been studied as tunnel barriers for making such high Tc tunnel junctions. 14 refs., 11 figs

1991-05-27

354

X-rays look through multilayers  

International Nuclear Information System (INIS)

What was originally a one- or two-layer printed circuit-board has turned into multilayer boards of high complexity. Production of boards of this type place high requirements on production engineering and process reliability. One important quality criterion of the multilayer is e.g. a sufficient width of the copper ring around a plated-through hole, the so-called residual ring width. Printed circuit-boards can be measured exactly and scrap prevented by employing an X-ray tester with integrated image processing within the various production steps. (orig.)

1990-01-01

355

Magnetic multilayers : fundamental and practical aspects  

Digital Repository Infrastructure Vision for European Research (DRIVER)

After a brief introduction we describe the preparation of the multilayers by evaporation under ultra high vacuum conditions and their characterisation. We then discuss the magnetic and magneto-optical properties of some multilayer systems such as, Ni/Ag, Fe/Ag, Co/Ag and Co/Pt. The last one is quite interesting and is a potential candidate for magneto-optical information storage, particularly capable of working in the shorter wave length of light. We describe particularly the various anisotro...

Krishnan, R.

1992-01-01

356

Nanoporous silicon multilayers for terahertz filtering.  

Science.gov (United States)

We describe the fabrication, simulation, and measurement of a terahertz (THz) filter composed of nanoporous silicon multilayers. Using electrochemical etching, we fabricated a structure composed of alternating high- and low-index layers that achieves 93% power reflectivity at the target wavelength of 1.17 THz, with a stopband of 0.26 THz. The measured reflection and transmission spectra of the multilayer filter show excellent agreement with calculations based on the refractive indices determined separately from single-layer measurements. This technique could provide a convenient, flexible, and economical way to produce THz filters, which are essential in a variety of future applications. PMID:19794768

Lo, Shu-Zee A; Murphy, Thomas E

2009-10-01

357

Physical and chemical characterization of multilayered structures  

Energy Technology Data Exchange (ETDEWEB)

It is important to know the physical and chemical properties of a multilayer if its performance is to be compared to theoretical predictions, or if guidance is needed for the production of superior multilayers. Accurate, nondestructive analytical methods, such as neutron activation analysis, are restricted to certain elements. Certain destructive methods, such as total carbon analysis by combustion, can be sensitive enough for use with very small samples. The method of choice depends upon sensitivity and specificity, both of which are discussed in this paper. 6 refs., 3 figs., 2 tabs.

Thorne, J.M.; Knight, L.V.; Peterson, B.G.

1985-01-01

358

Exchange interactions in Fe/Y multilayers  

International Nuclear Information System (INIS)

The magnetization of Fe/Y multilayers has been measured as a function of temperature. A bulk-like T 3/2 temperature dependence of the magnetization is observed for all multilayers in the temperature range 5-300 K. The spin-wave constant B is found to decrease inversely with t Fe. A simple theoretical model with exchange interactions only, and with non-interacting magnons, has been used to explain the temperature dependence of the magnetization and the approximate values for the bulk exchange interaction J b, surface exchange interaction J s and the interlayer exchange interaction J I for various Fe layer thicknesses have been obtained

2005-05-17

359

YBCO based multilayers for optoelectronic devices  

Energy Technology Data Exchange (ETDEWEB)

YBCO based multilayers have been deposited independently by three techniques: laser ablation, inverted cylindrical target sputtering (ICM) and on-axis planar D.C. Magnetron Sputtering. The last technique is used to cover uniformly R-plane sapphire and LaAlO3 2 inch wafers with YBCO or multilayers to achieve optoelectronic devices such as infrared detectors. Very thin ({sup -} 3 nm) YSZ and MgO dielectric films have been studied as tunnel barriers for making such high Tc tunnel junctions. 14 refs., 11 figs.

Villegier, J.C.; Moriceau, H.; Boucher, H.; Di Cioccio, L.; Ghis, A.; Jaeger, A.; Levis, M.; Pourtier, F.; Schwerdtfeger, M.; Vabre, M.; Villard, C. [CEA Centre d`Etudes de Grenoble, 38 (France). Direction des Technologies Avancees; Chicault, R. [Grenoble-1 Univ., 38 (France)

1991-12-31

360

Training recurrent networks by Evolino.  

Science.gov (United States)

In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for training RNNs, due to numerous local minima. For such cases, we present a novel method: EVOlution of systems with LINear Outputs (Evolino). Evolino evolves weights to the nonlinear, hidden nodes of RNNs while computing optimal linear mappings from hidden state to output, using methods such as pseudo-inverse-based linear regression. If we instead use quadratic programming to maximize the margin, we obtain the first evolutionary recurrent support vector machines. We show that Evolino-based LSTM can solve tasks that Echo State nets (Jaeger, 2004a) cannot and achieves higher accuracy in certain continuous function generation tasks than conventional gradient descent RNNs, including gradient-based LSTM. PMID:17298232

Schmidhuber, Jürgen; Wierstra, Daan; Gagliolo, Matteo; Gomez, Faustino

2007-03-01

 
 
 
 
361

Recurrent pyogenic granuloma with satellitosis.  

Science.gov (United States)

A 26-year-old woman was treated by curettage and cautery for a pyogenic granuloma on her left shoulder. This recurred 3 months later and was excised. After a further 5 months, she developed three vascular papules and one lobulated vascular lesion at the site. These ranged in size from 1-4 mm and the largest of these bled easily on minimal trauma. The authors treated the four vascular lesions with curettage and cautery and took a punch biopsy from an erythematous area in the scar. Histology was identical to the original lesion, confirming a diagnosis of recurrent pyogenic granuloma with satellitosis. One year later she had no evidence of recurrence of the lesions. PMID:22605705

George, Susannah Mary Creighton; Gossain, Sunita R; Morrison, Iain K; Coburn, Peter R

2012-01-01

362

Pointwise-recurrent dendrite maps  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Let D be a dendrite and f:D-> D a continuous map. Denote by E(D) and B(D) the sets of endpoints and branch points of D respectively. We show that if E(D) is countable (resp. B(D) is discrete) then f is pointwise-recurrent if and only if f is pointwise periodic homeomorphism (resp. every pointin D\\E(D) is periodic).

Naghmouchi, Issam

2011-01-01

363

Management of Recurrent Ventricular Pseudoaneurysm  

Digital Repository Infrastructure Vision for European Research (DRIVER)

A 49-year-old man suffered multiple recurrences of pseudoaneurysm following ventricular aneurysmectomy in which Teflon felt strips had been used to reinforce the closure. The pseudoaneurysm was secondary to infection of the cardiac suture line, caused by a pathogen resident in the multifilamented Teflon strips. The patient was treated successfully by removal of all residual foreign material and reinforcement of the suture line with an omental pedicle graft. (Texas Heart Institute Journal 1991...

Bluett, Michael; Bolling, Steven F.; Kirsh, Marvin M.

1991-01-01

364

Recurrent pseudotumoral hemicerebellitis: neuroimaging findings  

International Nuclear Information System (INIS)

We present the case of a 13-year-old girl with pseudotumoral hemicerebellitis that recurred 22 months after the first episode together with conventional MR imaging findings and diffusion-weighted imaging and MR spectroscopy findings. A mirror pattern of involvement was present with the contralateral hemisphere affected in the second episode. Recurrent hemicerebellitis is unique and recognition of the radiological findings allows accurate diagnosis that can be a challenge clinically. (orig.)

2008-04-01

365

Recurrent pseudotumoral hemicerebellitis: neuroimaging findings  

Energy Technology Data Exchange (ETDEWEB)

We present the case of a 13-year-old girl with pseudotumoral hemicerebellitis that recurred 22 months after the first episode together with conventional MR imaging findings and diffusion-weighted imaging and MR spectroscopy findings. A mirror pattern of involvement was present with the contralateral hemisphere affected in the second episode. Recurrent hemicerebellitis is unique and recognition of the radiological findings allows accurate diagnosis that can be a challenge clinically. (orig.)

Oguz, Kader K. [Hacettepe University, Department of Radiology, Faculty of Medicine, Ankara (Turkey); Haliloglu, Goknur; Topcu, Meral [Hacettepe University, Department of Paediatric Neurology, Faculty of Medicine, Ankara (Turkey); Alehan, Dursun [Hacettepe University, Department of Paediatric Cardiology, Faculty of Medicine, Ankara (Turkey)

2008-04-15

366

Uncommon cause of recurrent infections  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We descibe the case of a girl of Indian origin who presented with recurrent infections. The only abnormality detected in the armoury of the immune system was consistent neutropenia. Mutation analysis revealed ELA2 (neutrophil elastase) gene mutation that has been associated with severe congenital neutropenia phenotype. Patient was treated with the granulocyte-colony stimulating factor (G-CSF) as prevention of infectious manifestations along with appropriate measure to curb secondary complicat...

Deotare, Uday R.; Patel, Pranav D.; Parikh, Rohan P.; Bhagat, Eva A.

2012-01-01

367

Vulvovaginitis Candidiasis Recurrence During Pregnancy  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Vulvovaginitis is the most common gynecologic condition seen by practitioners rendering primary care to women. Vulvovaginitis Candidiasis (VVC) is the most common type of vaginitis and this study aimed at specifying VVC recurrence during pregnancy. In this prospective study, 150 pregnant women suffering from vaginal excretion, morsus and itching were studied. Initially, the patients were treated using clotrimazole local cream (5 g) for 7 successive days. After initial treatment, the pat...

Fardiazar, Z.; Ronaci, F.; Torab, R.; Goldust, M.

2012-01-01

368

Recurrent frequency-size distribution  

CERN Document Server

Many complex systems, including a sand-pile model, a slider-block model, and actual earthquakes, have been discussed whether they obey the principles of self-organized criticality. Behavior of these systems can be investigated from two different points of view: interoccurrent behavior in a region and recurrent behavior at a given point on a fault or at a given fault. The interoccurrent frequency-size statistics are known to be scale-invariant and obey the power-law Gutenberg-Richter distribution. This paper investigates the recurrent frequency-size behavior at a given point on a fault or at a given fault. For this purpose sequences of creep events at a creeping section of the San Andreas fault are investigated. The applicability of Brownian passage-time, lognormal, and Weibull distributions to the recurrent frequency-size statistics of slip events is tested and the Weibull distribution is found to be a best-fit distribution. To verify this result the behavior of the numerical slider-block and sand-pile models...

Abaimov, S G

2008-01-01

369

Erlotinib and Temozolomide in Treating Young Patients With Recurrent or Refractory Solid Tumors  

Science.gov (United States)

Previously Treated Childhood Rhabdomyosarcoma; Recurrent Childhood Brain Tumor; Recurrent Childhood Cerebellar Astrocytoma; Recurrent Childhood Cerebral Astrocytoma; Recurrent Childhood Ependymoma; Recurrent Childhood Malignant Germ Cell Tumor; Recurrent Childhood Medulloblastoma; Recurrent Childhood Rhabdomyosarcoma; Recurrent Childhood Soft Tissue Sarcoma; Recurrent Childhood Supratentorial Primitive Neuroectodermal Tumor; Recurrent Neuroblastoma; Recurrent Osteosarcoma

2013-06-04

370

Stress Reduction in Improving Quality of Life in Patients With Recurrent Gynecologic or Breast Cancer  

Science.gov (United States)

Anxiety Disorder; Depression; Fatigue; Leydig Cell Tumor; Ovarian Sarcoma; Ovarian Stromal Cancer; Pain; Peritoneal Carcinomatosis; Pseudomyxoma Peritonei; Recurrent Breast Cancer; Recurrent Cervical Cancer; Recurrent Endometrial Carcinoma; Recurrent Fallopian Tube Cancer; Recurrent Gestational Trophoblastic Tumor; Recurrent Ovarian Epithelial Cancer; Recurrent Ovarian Germ Cell Tumor; Recurrent Primary Peritoneal Cavity Cancer; Recurrent Uterine Sarcoma; Recurrent Vaginal Cancer; Recurrent Vulvar Cancer

2014-05-20

371

Chain recurrence rates and topological entropy  

CERN Multimedia

We investigate the properties of chain recurrent, chain transitive, and chain mixing maps (generalizations of the well-known notions of non-wandering, topological transitivity, and topological mixing). We describe the structure of chain transitive maps. These notions of recurrence are defined using $\\epsilon$-chains, and the minimal lengths of these $\\epsilon$-chains give a way to measure recurrence time (chain recurrence and chain mixing times). We give upper and lower bounds for these recurrence times and relate the chain mixing time to topological entropy.

Richeson, David

2008-01-01

372

Product recurrent properties, disjointness and weak disjointness  

CERN Document Server

Let $\\F$ be a collection of subsets of $\\Z_+$ and $(X,T)$ be a dynamical system. $x\\in X$ is $\\F$-recurrent if for each neighborhood $U$ of $x$, $\\{n\\in\\Z_+:T^n x\\in U\\}\\in \\F$. $x$ is $\\F$-product recurrent if $(x,y)$ is recurrent for any $\\F$-recurrent point $y$ in any dynamical system $(Y,S)$. It is known that $x$ is $\\{infinite\\}$-product recurrent if and only if it is minimal and distal. In this paper it is proved that the closure of a $\\{syndetic\\}$-product recurrent point (i.e. weakly product recurrent point) has a dense minimal points; and a $\\{piecewise syndetic\\}$-product recurrent point is minimal. Moreover, it is observed that if $(X,T)$ is disjoint from all minimal systems, then each transitive point of $(X,T)$ is weakly product recurrent. Results on product recurrence when the closure of an $\\F$-recurrent point has zero entropy are obtained. Several results on disjointness are given, and results on weak disjointness are described when considering disjointness.

Dong, Pandeng; Ye, Xiangdong

2009-01-01

373

Structural and magnetic aspects of multilayer interfaces  

Energy Technology Data Exchange (ETDEWEB)

We show that it is possible to obtain quantitative information about the interface quality by considering the magnetic moments of Fe/V multilayers. We derive a parameter space describing the quality of interfaces and argue that most of the experimentally grown samples lie within a smaller segment of this space.

Holmstroem, Erik E-mail: erik.holmstrom@fysik.uu.se; Bergqvist, L.; Skubic, B.; Eriksson, O

2004-05-01

374

Structural and magnetic aspects of multilayer interfaces  

International Nuclear Information System (INIS)

We show that it is possible to obtain quantitative information about the interface quality by considering the magnetic moments of Fe/V multilayers. We derive a parameter space describing the quality of interfaces and argue that most of the experimentally grown samples lie within a smaller segment of this space

2004-05-01

375

EduXs: Multilayer Educational Services Platforms  

Science.gov (United States)

How to use the online social learning communities to improve quality and quantity of interactions in physical social learning communities is an important issue. This work describes the design and implementation of multilayer educational services platforms that enable learners to establish their own online social learning communities and integrate…

Chang, Li-Jie; Yang, Jie-Chi; Deng, Yi-Chan; Chan, Tak-Wai

2003-01-01

376

Multilayers gratings for X-UV optics  

International Nuclear Information System (INIS)

Multilayer gratings are thin film structures possessing periodicities both in the normal and lateral directions. They combine the properties of surface gratings and planar multilayers thus providing a high throughput and high spectral resolution on higher diffraction orders. The unique diffraction properties are utilized in the X-ray and ultraviolet optics where no lenses or mirrors comparable with those for visible light are available. Multilayer gratings act as constant resolution dispersion elements in a broad spectral range. A fan of grating diffractions in real space is represented by a set of points on equidistant truncation rods in the reciprocal space. The kinematical theory of X-ray scattering explains well the positions of the grating truncation rods while the dynamical theory is inevitable to calculate the intensities along the truncation rods (grating efficiency). The properties of multilayer gratings are exemplified on two differently prepared lamellar gratings with the nominal normal and lateral periods of 8 nm and 800 nm, respectively. The fabrication steps are described in detail. The specular and non-specular X-ray reflectivities at wavelength 0.15418 nm were measured on one of the samples. The dynamical theory of X-ray scattering with a matrix modal eigenvalue approach was applied to extract the real structural parameters such as the surface and interface roughnesses, individual layer thicknesses, and the lamella width to the grating period ratio. The X-ray reflectometry is completed by microscopy observations which provide complementary and direct information on the local surface profile. (Authors)

2000-08-01

377

Diffraction Gratings Based on Multilayer Structures  

International Science & Technology Center (ISTC)

Development of High Efficiency Diffraction Gratings on the Basis of Multilayer Structures for Monochromators and Polychromators of X-Ray Synchrotron Radiation and for Ultra-High Spectral Resolution X-Ray Diagnostics in the 0.1 – 10 Kev Energy Range

378

Guided wave sensing of polyelectrolyte multilayers  

DEFF Research Database (Denmark)

A planar optical waveguide configuration is proposed to monitor the buildup of thick polyelectrolyte multilayers on the surface of the waveguide in aqueous solutions. Instead of detecting the layer by the electromagnetic evanescent field the polyelectrolyte layer acts as an additional waveguiding film that is sensed by guided waves instead of evanescent waves. This leads to a considerably improved sensitivity and dynamic range.

Horvath, R.; Pedersen, H.C.

2006-01-01

379

Zinc oxide multilayers for solar collector coatings  

Energy Technology Data Exchange (ETDEWEB)

A solar selective coating has been fabricated by capping black zinc oxide with a transparent zinc oxide heat mirror film. Deposition onto glass substrates was accomplished by reactive bias sputtering. The zinc oxide multilayer structure had a solar absorptance of 0.90 and an IR emittance of 0.26. Suggestions are made for significant improvement of solar selective performance.

Brett, M.J.; Parsons, R.R.; Baltes, H.P.

1986-08-15

380

Surface superconductivity in multilayered rhombohedral graphene: Supercurrent  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The supercurrent for the surface superconductivity of a flat-band multilayered rhombohedral graphene is calculated. Despite the absence of dispersion of the excitation spectrum, the supercurrent is finite. The critical current is proportional to the zero-temperature superconducting gap, i.e., to the superconducting critical temperature and to the size of the flat band in the momentum space.

Kopnin, N. B.

2011-01-01

 
 
 
 
381

Superconductivity in multilayered Nb/Fe films  

International Nuclear Information System (INIS)

Nb/Fe multilayer structures have been prepared by RF magnetron sputtering technique and variation of the superconducting transition temperature (Tc) has been studied as a function of layer thickness of Fe, keeping Nb layer thickness constant. The results show a monotonic decrease of Tc with increase in layer thickness of Fe. (author)

1999-12-20

382

Cocaine-induced recurrent leukoencephalopathy.  

Science.gov (United States)

Cocaine-induced leukoencephalopathy is a rare neurological complication. It is most likely related to the substances used to adulterate the cocaine. Levamisole is one of the most common adulterants of cocaine and causes reversible leukoencephalopathy. Patients display severe neurological symptoms that resolve at termination of the exposure. MRI shows diffuse white matter involvement with sparing of the U fibers, without brain stem or cerebellar involvement. We describe the case of a woman with three neurologic episodes and remitting and recurrent brain white matter lesions. PMID:24199810

González-Duarte, Alejandra; Williams, Ricardo

2013-10-01

383

Recurrent priapism from therapeutic quetiapine.  

Science.gov (United States)

Priapism is rarely related to use of non-erectile related medications. The objective was to educate about the multiple possible causes of priapism and to provide treatment recommendations for the different types of priapism. We present the case of a 43-year-old African American male with a history of schizoaffective disorder who presented to our emergency department multiple times over a three year period with priapism, each episode related to the ingestion of quetiapine. Following penile aspiration and intercavernosal injection of phenylephrine, this patient had resolution of his priapism. This case demonstrates an unusual case of recurrent priapism. PMID:24578777

Saghafi, Omeed; Kao, Amanda; Druck, Jeffrey

2014-02-01

384

Polyelectrolyte multilayers: An odyssey through interdisciplinary science  

Science.gov (United States)

This dissertation provides an overview of a self assembled multilayer technique based on the alternating deposition of oppositely charged polyelectrolytes onto charged solid supports. The basic principles and methodologies governing this technique are laid down, and new strategies are built upon the latter, in an effort to develop innovative technologies that would be beneficial for making new products or improving the quality of existing ones. Fundamental studies to characterize the water content, efficiency of ion-pairing, differential strength of electrostatic interactions, topology, and viscoelastic properties of polyelectrolyte multilayers, PEMUs, are illustrated and conducted. In addition, polyelectrolyte multilayers that are stimulus responsive, or support active and controlled bio-motor protein interactions are described. Attenuated total reflectance Fourier transform infrared, (ATR), spectroscopy was used to compare the extent of swelling and doping within PAH/PSS and PDADMA/PSS polyelectrolyte multilayers. Unlike PDADMA/PSS, whose water content depended on the solution ionic strength, PAH/PSS was resistant to swelling by salt. It was stable up to 4.0 M sodium chloride, with 6 water molecules per ion-pair. Using the infrared active perchlorate sodium salt, the amount of residual persistent extrinsic sites in both PDADMA/PSS and PAH/PSS was determined to be 3% and 6%, respectively. The free energy of association between the polymer segments, in the presence of sodium perchlorate, was in the order of 4.5 kJ mol-1 and -9.5 kJ mol-1 for PDADMA/PSS and PAH/PSS correspondingly. Thus, indicating the relatively strong electrostatic association between the polymer segments in a PAH/PSS relative to PDADMA/PSS multilayer. Adjusting the pH of the solution in contact with the PAH/PSS multilayer to 11.5 resulted in a first order discontinuous dissociation of the Pol+Pol- bonds. Techniques used to study the mechanical properties of single muscle fiber were adapted to characterize the topology, viscoelastic behavior, complex modulus and loss factor of PDADMA/PSS multilayers, over a range of frequencies and strain amplitudes. Tensile mode (transient uniaxial stretching) of a PEMU microcoupon using a capacitative-type force transducer located on a modified stage of inverted microscope revealed evidence on the viscous-like behavior of polymer chains within PEMU. Dependence of viscosity was primarily on the ionic strength of the bathing solution, with appreciable stress relaxation occurring at high salt concentrations. Dynamic mechanical analysis was then used to determine the damping properties of PEMU where the length was oscillated sinusoidally, and the resulting force, amplitude and phase shift were observed. Compared to other commercially available polymer damping materials such as acrylic and rubber adhesives, PEMU demonstrated up to 250% enhancement in damping properties over the frequency range of 0.3-10 Hz. This was obtained while the multilayer dry thickness was 3000% less then that of the conventional adhesives. The synthesis of charged copolymers of poly(N-isopropylacrylamide), (PNIPAM), and their use in constructing thermally responsive PEMU were demonstrated. The temperature dependent water content of the thin film, studied in situ using ATR-FTIR spectroscopy, revealed microscopic and macroscopic transitions at 33 and 45°C, respectively. About 7 water molecules per NIPAM repeat unit were found to be reversibly lost from, or recovered by, the film upon cycling over a temperature range of 10 to 55°C. Assuming that each ion-pair represents a crosslink, swelling theory was used to translate these results into polymer-solvent interaction parameters and enthalpies of mixing for the various polymer components. In addition, the flux of a charged probe molecule, potassium ferricyanide, through the NIPAM-rich multilayer was assessed with rotating disk electrode voltammetry. Thermally reversible modulation of ion transport was demonstrated. Positive polyelectrolytes were investigated as new surface coatings for promoting in vi

Jaber, Jad A.

385

Design and development of multilayer vascular graft  

Science.gov (United States)

Vascular graft is a widely-used medical device for the treatment of vascular diseases such as atherosclerosis and aneurysm as well as for the use of vascular access and pediatric shunt, which are major causes of mortality and morbidity in this world. Dysfunction of vascular grafts often occurs, particularly for grafts with diameter less than 6mm, and is associated with the design of graft materials. Mechanical strength, compliance, permeability, endothelialization and availability are issues of most concern for vascular graft materials. To address these issues, we have designed a biodegradable, compliant graft made of hybrid multilayer by combining an intimal equivalent, electrospun heparin-impregnated poly-epsilon-caprolactone nanofibers, with a medial equivalent, a crosslinked collagen-chitosan-based gel scaffold. The intimal equivalent is designed to build mechanical strength and stability suitable for in vivo grafting and to prevent thrombosis. The medial equivalent is designed to serve as a scaffold for the activity of the smooth muscle cells important for vascular healing and regeneration. Our results have shown that genipin is a biocompatible crosslinker to enhance the mechanical properties of collagen-chitosan based scaffolds, and the degradation time and the activity of smooth muscle cells in the scaffold can be modulated by the crosslinking degree. For vascular grafting and regeneration in vivo, an important design parameter of the hybrid multilayer is the interface adhesion between the intimal and medial equivalents. With diametrically opposite affinities to water, delamination of the two layers occurs. Physical or chemical modification techniques were thus used to enhance the adhesion. Microscopic examination and graft-relevant functional characterizations have been performed to evaluate these techniques. Results from characterization of microstructure and functional properties, including burst strength, compliance, water permeability and suture strength, showed that the multilayer graft possessed properties mimicking those of native vessels. Achieving these FDA-required functional properties is essential because they play critical roles in graft performances in vivo such as thrombus formation, occlusion, healing, and bleeding. In addition, cell studies and animal studies have been performed on the multilayer graft. Our results show that the multilayer graft support mimetic vascular culture of cells and the acellular graft serves as an artery equivalent in vivo to sustain the physiological conditions and promote appropriate cellular activity. In conclusion, the newly-developed hybrid multilayer graft provides a proper balance of biomechanical and biochemical properties and demonstrates the potential for the use of vascular tissue engineering and regeneration.

Madhavan, Krishna

386

Systemic Treatment of Recurrent Meningioma  

Directory of Open Access Journals (Sweden)

Full Text Available Meningioma is the most frequently diagnosed primary brain tumour. Although only a subset of meningioma patients suffer recurrence after standard therapy, these patients require further rescue treatment. Owing to the fact that meningioma over-expresses a great number of potential therapeutic targets, some systemic therapies have been evaluated in recurrent meningioma patients. Cytostatic agents, including combined chemotherapeutic regimens, hydroxyurea and temozolomide, are generally ineffective. Immunotherapy and hormonal therapy with somatostatin analogues have been suggested as potential therapeutic agents, even though studies have presented contradictory results. Recently, several studies using targeted therapies, such as epidermal growth factor receptor (EGFR, platelet-derived growth factor receptor (PDGFR, and vascular endothelial growth factor (VEGF inhibitors, showed early promising results. However, additional long-term results are still under evaluation. Furthermore, the combination of various medical therapies, such as hydroxyurea and a PDGFR inhibitor, appears to hold some promise. This review provides an overview of the current rationale and evidence base for the various medical therapy approaches tested.

Simo M

2013-01-01

387

Treatment of refractory recurrent pericarditis.  

Science.gov (United States)

We report a difficult case of a 45-year-old woman with refractory recurrent pericarditis, who was treated with several different medical therapies, pericardial window, and pericardiectomy. This case suggests that more invasive diagnostic and therapeutic choices, such as pericardial window and pericardiectomy, should be carefully considered for possible side-effects and the risk of promoting further recurrences. Non-steroidal anti-inflammatory drugs and colchicine are first-choice drugs, whereas corticosteroids should be considered only in patients with a frequent crisis unresponsive to non-steroidal anti-inflammatory drugs, and by using proper dosage and a careful slow tapering. Patience and appropriate medical therapy are the keys to successful management. In true refractory cases, combination therapy with two or three drugs such as non-steroidal anti-inflammatory drugs, colchicine and corticosteroid may be considered before applying other more complex and less safe treatments. Immunosuppressive drugs and steroid sparing agents might be used, but it should be acknowledged that only weak evidence-based data support their use. PMID:17700412

Imazio, Massimo; Cecchi, Enrico; Correndo, Livio; D'Oulx, Emanuele Antonielli; Doronzo, Baldassarre; Trinchero, Rita

2007-09-01

388

Is acute recurrent pancreatitis a chronic disease?  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Whether acute recurrent pancreatitis is a chronic disease is still debated and a consensus is not still reached as demonstrated by differences in the classification of acute recurrent pancreatitis. There is major evidence for considering alcoholic pancreatitis as a chronic disease ab initio while chronic pancreatitis lesions detectable in biliary acute recurrent pancreatitis (ARP) seem a casual association. Cystic fibrosis transmembrane conductance regulator (CFTR) gene mutation, hereditary a...

Mariani, Alberto; Testoni, Pier Alberto

2008-01-01

389

Radiotherapy in Locoregional Recurrent Breast Carcinoma  

International Nuclear Information System (INIS)

Thirty eight women with recurrent breast carcinoma involving chest wall and/or regional lymph nodes after surgery with or without systemic therapy were treated with radiation between 1979 and 1986. Among them, 5 patients were excluded from analysis because of incomplete treatment. The median follow up of survivors was 30 months (ranged 1-79 months). Fifteen (45%) patients had their disease confined to the chest wall and eighteen patients had lymph node involvement as some of their locoregional recurrent disease. Within 36 months after the initial treatment, 87% of recurrences manifested themselves. All patients had radiotherapy to at least the site of involvement. In 8 patients, recurrent tumors were treated with complete excision followed by radiation. Of the remaining 25 patients, 18(72%) had complete response (CR) following radiotherapy. The actuarial 3-year survival of all patients following locoregional recurrence was 50%. Three year survival was 24% in those 25 patients who had recurrences within 24 months of the initial treatment. For those 8 patients whose recurrences occurred after more than 24 month disease free interval, the 3-year survival was 100%. For those patients with recurrences confined to chest wall alone, 3-year survival was 57%. The patients who had lymph node involvement as part of their locoregional recurrences had a 43% 3-year survival. The majority of them developed distant metastases. Those patients who had a CR showed 63% 3-year survival. On the other hand, 1 year survival was only 33% for those patients who had a less than CR. Three patients developed carcinoma of the contralateral breast following radiotherapy. Three year survival following locoregional recurrence was 40% for patients whose initial treatment for their primary breast carcinoma was surgery and adjuvant systemic therapy. For those patients whose primary breast carcinoma was treated by surgery alone, the 3-year survival following locoregional recurrence was 71%. In patients who had subsequent recurrence after radiotherapy, the actuarial survival was 25% at 2 years

1988-12-01

390

CHROMOSOMAL ABNORMALITIES IN PATIENTS WITH RECURRENT MISCARRIAGE  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Chromosomal abnormalities are involved in the etiology of recurrent spontaneous pregnancy loss and sub-fertility. The purpose of this study was to determine the frequency and contribution of chromosomal abnormalities in recurrent miscarriages. The results obtained and literature review are helpful in understanding the importance of cytogenetics analysis of female infertility. To investigate the distribution of chromosomal abnormalities in the Romanian population with recurrent miscarriage,...

Daniela Mierla; Viorica Radoi; Veronica Stoian

2012-01-01

391

Recurrent ameloblastoma of the mandible and maxilla.  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Sixteen cases of recurrent ameloblastomas of the mandible and maxilla seen over a 14 year period at the Tata Memorial Hospital were analysed with emphasis on recurrence patterns, type of primary surgery and surgical management. Seventy-five percent of the cases had conservative surgery at the first instance. In our experience, recurrent tumors could be excised widely even in unusual locations with good results.

Albuquerque K; Mehta S; Sarkar S.; Mehta A

1993-01-01

392

Recurrent Pyogenic Cholangitis Treated by Left Hepatectomy  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Recurrent pyogenic cholangitis is managed mostly by conservative treatment or by clearance of stones and biliary enteric by-pass procedure. Hepatectomy is rarely needed. We report a case of recurrent pyogenic cholangitis in a 34-year old man, who presented with recurrent upper abdominal pain, mild jaundice, and fever since childhood. Contrast enhanced computed tomography of abdomen and magnetic resonance cholangiopancreatography confirmed the diagnosis and showed significant atrophy of the le...

Ray, Sukanta

2011-01-01

393

Interpersonal mechanisms in recurrence of depression  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Depression is serious disease, also because of its recurrent nature. Many people who have become depressed once, will become depressed more often. Moreover, the risk of depression seems to increase with every further episode. These observations underline the importance of gaining a better understanding of the mechanisms behind recurrence of depression. The present multidisciplinary project investigates 5 different types of risk factors for recurrence of depression (factors from the fields of ...

Bos, Elisabeth Henrie?tte

2005-01-01

394

Poincar\\'e recurrences of DNA sequence  

CERN Document Server

We analyze the statistical properties of Poincar\\'e recurrences of Homo sapiens, mammalian and other DNA sequences taken from Ensembl Genome data base with up to fifteen billions base pairs. We show that the probability of Poincar\\'e recurrences decays in an algebraic way with the Poincar\\'e exponent $\\beta \\approx 4$ even if oscillatory dependence is well pronounced. The correlations between recurrences decay with an exponent $\

Frahm, K M

2011-01-01

395

Surgical options for recurrent uterine sarcomas.  

Science.gov (United States)

Leiomyosarcoma, the most frequent pure uterine sarcoma, is an aggressive tumor with a tendency toward early relapse. Survival for patients with recurrent disease is poor. In contrast, endometrial stromal sarcoma, the second most common uterine sarcoma, is a more indolent malignancy with a tendency toward recurrence after a long latency period. The relative infrequency of both diseases makes the study and standardization of treatment for recurrent disease challenging. Treatment of recurrence with cytotoxic chemotherapy, radiation therapy, or hormone therapy produces modest to poor response rates. Surgical resection is one treatment modality offering the potential for cure and perhaps a more durable response than is seen with medical management. Although initial studies focused on pulmonary metastasectomy in recurrent soft tissue sarcoma, an increasingly large body of data specifically evaluating outcomes after both thoracic and extrathoracic metastasectomy in patients with recurrent uterine sarcoma is now available. Though no prospective trials have been conducted, retrospective comparisons of chemotherapy or radiation therapy with surgery for recurrent uterine sarcoma suggest improvement in disease-specific survival for the surgery group. Clearly defined factors are associated with better prognosis after surgical resection of recurrence, including a prolonged disease-free interval and complete resection of disease. In properly selected women, surgery and even repeated metastasectomy for recurrent disease may improve survival and should be considered. PMID:24451764

Korets, Sharmilee B; Curtin, John P

2012-01-01

396

Recurrent odontogenic keratocyst within the masticatory space  

Energy Technology Data Exchange (ETDEWEB)

The odontogenic keratocyst (OKC) is a developmental odontogenic cyst typically occurring in the jaws. Since the first description of OKC was published in 1956, the lesion has been of particular interest because of its specific histopathologic features, high recurrence rate, and aggressive behavior. Recurrences most commonly arise within bone at the site of the original cyst. However, as lining cells may find their way into surrounding tissues either from implantation during surgery or from cortical perforation recurrences may arise at a distance from the original cyst. Here, we report a rare case of recurrent OKC which was first developed in mandible and recurred within the masticatory space.

Lim, Su Yeon; Huh, Kyung Hoe; Yi, Won Jin; Choi, Hyun Bae; Choi, Soon Chul [School of Dentistry, Seoul National University, Seoul (Korea, Republic of)

2008-06-15

397

Recurrent odontogenic keratocyst within the masticatory space  

International Nuclear Information System (INIS)

The odontogenic keratocyst (OKC) is a developmental odontogenic cyst typically occurring in the jaws. Since the first description of OKC was published in 1956, the lesion has been of particular interest because of its specific histopathologic features, high recurrence rate, and aggressive behavior. Recurrences most commonly arise within bone at the site of the original cyst. However, as lining cells may find their way into surrounding tissues either from implantation during surgery or from cortical perforation recurrences may arise at a distance from the original cyst. Here, we report a rare case of recurrent OKC which was first developed in mandible and recurred within the masticatory space.

2008-06-01

398

Mathematical Formulation of Multi-Layer Networks  

CERN Document Server

A network representation is useful for describing the structure of a large variety of complex systems. However, most real and engineered systems have multiple subsystems and layers of connectivity, and the data produced by such systems is very rich. Achieving a deep understanding of such systems necessitates generalizing "traditional" network theory, and the newfound deluge of data now makes it possible to test increasingly general frameworks for the study of networks. In particular, although adjacency matrices are useful to describe traditional single-layer networks, such a representation is insufficient for the analysis and description of multiplex and time-dependent networks. One must therefore develop a more general mathematical framework to cope with the challenges posed by multi-layer complex systems. In this paper, we introduce a tensorial framework to study multi-layer networks, and we discuss the generalization of several important network descriptors and dynamical processes ---including degree centr...

De Domenico, Manlio; Cozzo, Emanuele; Kivelä, Mikko; Moreno, Yamir; Porter, Mason A; Gòmez, Sergio; Arenas, Alex

2013-01-01

399

Optical Bistability in Ag/Dielectric Multilayers  

International Nuclear Information System (INIS)

We numerically study the optical bistability (OBIS) in periodic multilayers of Ag/SiO2. The calculated dependence of the output on the input intensity shows two possible OBIS states at the test wavelength. One is due to the field localization effects in silver layers with nonlinear refractive index modifying resonant tunneling of electromagnetic waves; the other, with about a three times lower threshold input intensity, is attributed to the intensity dependence change of the Ag/SiO2 composite's effective dielectric constant from metallic-like (negative) to dielectric-like (positive). With appropriate design engineering the Ag/SiO2 multilayers could find broad applications in all-optical information processes. (fundamental areas of phenomenology(including applications))

2012-05-01

400

Thermal performance of multilayer insulation. Part 3  

International Nuclear Information System (INIS)

The effects of various parameters on heat flux between room temperature and liquid nitrogen temperature through multilayer insulation (MLI) are examined using prediction equations and experimental results. The investigated parameters were the following: the winding method of multilayer insulation, hot boundary temperature, mesh size of the net, number of layers of net inserted between films, direction of layer installation, film thickness, and use of single- vs. double-aluminized films. To accomplish good thermal performance, laminated winding, larger mesh size, a layer of net inserted between films, thinner film (light weight), and double-aluminized film are needed. The optimum number of layers for different parameters is also discussed. It is found that the optimum number of layers is in the range of 30 to 60 layers in many cases

1995-05-01

 
 
 
 
401

Enhanced diffraction efficiency of gratings in multilayers.  

Science.gov (United States)

Computations with the rigorous differential method show that single gratings made by ion implantation have a diffraction efficiency in the +1 transmitted order under TE illumination of only 0.78%. The insertion of such gratings into multilayer dielectric Fabry-Perot cavities leads to an enhancement of the free-space diffraction efficiency. Different designs for the multilayer are considered. An 18.8% efficiency is reached with 11-layer mirrors. This result is obtained by optimization of the thickness of the spacer of the Fabry-Perot cavity that contains the grating and centering of the wavelength of the mirrors. The dependence of optical properties of the structure on the various optogeometrical parameters of the structure is discussed. PMID:18059826

Escoubas, L; Flory, F; Lemarchand, F; During, A; Roux, L

2000-02-15

402

Multilayer insulation with applications in cryogenic equipment  

International Nuclear Information System (INIS)

It is well known the fact that the most important problem in the cryogenic systems is the heat leak. This study is about the major heat leak of the system, which is the thermal radiation. Our purpose is to find the most suitable shielding method with Multi-Layer Insulation (MLI), using highly reflective foils of aluminium for the reflecting surfaces, interleaved with spacers to minimize conduction. The project proposes theoretical and applied research on methods of cryogenic cooling and control of heat transfer through multilayer thermal insulation at low temperatures and very low (including liquid helium), with applications in detritiation of heavy water and cooled superconducting electromagnetic fusion facility, as well as in general thermal insulation industry. Underlined are the opportunities created to a multidisciplinary team by partnership approach of the research material basis. (authors)

2009-01-01

403

Multi-layer waste containment barrier  

Energy Technology Data Exchange (ETDEWEB)

An apparatus for constructing an underground containment barrier for containing an in-situ portion of earth. The apparatus includes an excavating device for simultaneously (i) excavating earthen material from beside the in-situ portion of earth without removing the in-situ portion and thereby forming an open side trench defined by opposing earthen sidewalls, and (ii) excavating earthen material from beneath the in-situ portion of earth without removing the in-situ portion and thereby forming a generally horizontal underground trench beneath the in-situ portion defined by opposing earthen sidewalls. The apparatus further includes a barrier-forming device attached to the excavating device for simultaneously forming a side barrier within the open trench and a generally horizontal, multi-layer barrier within the generally horizontal trench. The multi-layer barrier includes at least a first layer and a second layer.

Smith, Ann Marie (Pocatello, ID); Gardner, Bradley M. (Idaho Falls, ID); Nickelson, David F. (Idaho Falls, ID)

1999-01-01

404

Static capacitance of some multilayered microstrip capacitors  

Science.gov (United States)

A new unified model, the modified Wolff model (MWM) is presented to determine the lumped capacitance of rectangular, circular, hexagonal and triangular patches on the single layer substrate and under the multilayer condition. Effect of the top shield on the lumped capacitance has also been determined. The MWM is the combination of Wolff-Knoppick model, TTL technique and single layer reduction (SLR) technique. The results of MWM have been compared against the results of SDA, FEM, dual integral method and other forms of the variational methods with accuracy between 0.5-5% for the most of shapes under various conditions. The present model has accuracy of SDA and other rigorous formulations. No single method has been used in the literature to determine the lumped capacitance of patches of several shapes under the multilayer and shielded condition. The MWM is fast even on the desktop computer. Thus, the model is suitable for a unified CAD for the MMIC applications.

Verma, Anand K.; Rostamy, Zargham

1995-05-01

405

Multilayer self-structured bubble memories  

Science.gov (United States)

Research work on multilayer self-structured bubble memories is at an early stage. The coupling of bubbles to stripes is investigated theoretically and experimentally and shown to be adequate for propagation. Propagation of stripes is demonstrated both by current access and field access techniques. These propagation techniques are of prime interest because they can eliminate most photographic features from the storage area. Multilayer films offer great promise for higher-capacity higher-density memories in which most of the photolithography has been eliminated and the minimum feature size of much of the remaining has been increased. Furthermore, stripe propagation can be carried out with current access, providing a significant reduction in packaging cost and power consumption over field access devices.

Kamin, M.; Krawczak, J. A.; Lins, S. J.; Torok, E. J.; Stermer, R. L., Jr.

1979-01-01

406

The structure and dynamics of multilayer networks  

CERN Document Server

In the past years, network theory has successfully characterized the interaction among the constituents of a variety of complex systems, ranging from biological to technological, and social systems. However, up until recently, attention was almost exclusively given to networks in which all components were treated on equivalent footing, while neglecting all the extra information about the temporal- or context-related properties of the interactions under study. Only in the last years, taking advantage of the enhanced resolution in real data sets, network scientists have directed their interest to the multiplex character of real-world systems, and explicitly considered the time-varying and multilayer nature of networks. We offer here a comprehensive review on both structural and dynamical organization of graphs made of diverse relationships (layers) between its constituents, and cover several relevant issues, from a full redefinition of the basic structural measures, to understanding how the multilayer nature of...

Boccaletti, S; Criado, R; del Genio, C I; Gómez-Gardeñes, J; Romance, M; Sendiña-Nadal, I; Wang, Z; Zanin, M

2014-01-01

407

Intermetallic phase formation in bulk multilayered structures  

Energy Technology Data Exchange (ETDEWEB)

The aim of the paper is to present a cross-section of experience on the low temperature processing of intermetallic sheets by extensive cold rolling of elemental metallic foils into bulk multilayered structures and subsequent solid state annealing. An overview is given on results for intermetallic phase formation kinetics in bulk multilayered samples of different Al-based systems (Al-M, M = Ni, Ta, Ti). The influence of structural (mechanical deformation) and annealing parameters on the reactive phase formation sequence will be discussed. Due to the small elemental layer thickness of about 100 nm after cold rolling, intermetallic formation starts at low annealing temperatures and can proceed in different diffusion controlled reaction pathways. However, the control of the reaction kinetics allows the formation of metastable phases and designed phase morphologies. (orig.)

Sieber, H. [Erlangen-Nuernberg Univ., Erlangen (Germany). Lehrstuhl fuer Glas und Keramik; Perepezko, J.H.

2000-07-01

408

Fracture mechanics parameters of multilayer pipes  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Multilayer pipes consisting of different materials are frequently used in praxis because of partial improvement of the properties of pipe systems. To estimate lifetime of these pipes the basic fracture parameters have to be determined. In this work finite element calculations are applied in order to estimate the stress intensity factor K and T-stress values for a new type of non-homogenous C-shape specimen. The application of calculated K and T values to laboratory estimation of fracture toug...

2007-01-01

409

Power consumption modeling in optical multilayer networks  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The evaluation of and reduction in energy consumption of backbone telecommunication networks has been a popular subject of academic research for the last decade. A critical parameter in these studies is the power consumption of the individual network devices. It appears that across different studies, a wide range of power values for similar equipment is used. This is a result of the scattered and limited availability of power values for optical multilayer network equipment. We propose referen...

Heddeghem, Ward; Idzikowski, Filip; Vereecken, Willem; Colle, Didier; Pickavet, Mario; Demeester, Piet

2012-01-01

410

Multi-layer illustrative dense flow visualization  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We present a dense visualization of vector fields on multi-layered surfaces. The method is based on the illustration buffer, which provides a screen space representation of the surface, where each pixel stores a list of all surface layers. This representation is implemented on the GPU using shaders and leads to a fast output sensitive technique. In our approach, we first use procedural noise to create an initial spot pattern on the surface that has both an almost constant screen space frequen...

Carnecky, R.; Schindler, B.; Fuchs, R.; Peikert, R.

2012-01-01

411

Dissipative plasmon-solitons in multilayer graphene  

CERN Document Server

Nonlinear properties of a multi-layer stack of graphene sheets are studied. It is predicted that such a structure may support dissipative plasmon-solitons generated and supported by an external laser radiation. Novel nonlinear equations describing spatial dynamics of the nonlinear plasmons driven by a plane wave in the Otto configuration are derived and the existence of single and multi-hump dissipative solitons in the graphene structure is predicted.

Smirnova, Daria A; Smirnov, Alexander I; Kivshar, Yuri S

2013-01-01

412

Analysis of Fracture Behaviour of Multilayer Pipes.  

Czech Academy of Sciences Publication Activity Database

. Ro?. 36, ?. 5 (2007), s. 207-212. ISSN 1465-8011.[Plastic Pipes /13./. Washington, D. C., 02.10.2006-05.10.2006]Grant CEP: GA ?R GA106/07/1284Výzkumný zám?r: CEZ:AV0Z20410507Klí?ová slova: multi-layer pipesKód oboru RIV: JL - Únava materiálu a lomová mechanikaImpakt faktor: 0.431, rok: 2007

Nezbedová, E.; Knésl, Zden?k; Vlach, B.

413

Magnetism of Semiconductors and Metallic Multilayers  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Magnetic properties of diluted magnetic semiconductors and magnetic metallic multilayers are investigated by SQUID magnetometry. By doping GaAs with magnetic Mn2+ ions under well defined growth conditions, one obtains a diluted magnetic semiconductor, (Ga,Mn)As, in which the randomly-distributed magnetic ions act as acceptor centers. At high enough dopant and hole concentration a carrier-induced ferromagnetic state results between the magnetic ions. Due to peculiarities of the growth process ...

Stanciu, Victor

2005-01-01

414

Interface resistance of disordered magnetic multilayers  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We study the effect of interface disorder on the spin-dependent interface resistances of Co/Cu, Fe/Cr and Au/Ag multilayers using a newly developed method for calculating transmission matrices from first-principles. The efficient implementation using tight-binding linear-muffin-tin orbitals allows us to model interface disorder using large lateral supercells whereby specular and diffuse scattering are treated on an equal footing. Without introducing any free parameters, quan...

Xia, K.; Kelly, P. J.; Bauer, G. E. W.; Turek, I.; Kudrnovsky?, J.; Drchal, V.

2000-01-01

415

Ultrapure Multilayer Graphene in Bromine Intercalated Graphite  

Digital Repository Infrastructure Vision for European Research (DRIVER)

We investigate the optical properties of bromine intercalated highly orientated pyrolytic graphite (Br-HOPG) and provide a novel interpretation of the data. We observe new absorption features below 620 meV which are absent in the absorption spectrum of graphite. Comparing our results with those of theoretical studies on graphite, single and bilayer graphene as well as recent optical studies of multilayer graphene, we conclude that Br-HOPG contains the signatures of ultrapure...

Hwang, J.; Carbotte, J. P.; Tongay, S.; Hebard, A. F.; Tanner, D. B.

2011-01-01

416

Principles of Bragg-Fresnel multilayer optics  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The paper describes the principles and theoretical models of new X-ray optical elements based on the behaviour of Bragg-Fresnel diffraction. The use of volume diffraction permits one to achieve better spatial resolution compared with conventional plane optics and bending mirrors. The construction of Bragg-Fresnel elements combines the advantages of high-resolution Fresnel optics with stability of multilayer mirrors.

Aristov, V. V.; Erko, A. I.; Martynov, V. V.

1988-01-01

417

Adsorption of ammonia on multilayer iron phthalocyanine  

International Nuclear Information System (INIS)

The adsorption of ammonia on multilayers of well-ordered, flat-lying iron phthalocyanine (FePc) molecules on a Au(111) support was investigated by x-ray photoelectron spectroscopy. We find that the electron-donating ammonia molecules coordinate to the metal centers of iron phthlalocyanine. The coordination of ammonia induces changes of the electronic structure of the iron phthalocyanine layer, which, in particular, lead to a modification of the FePc valence electron spin.

2011-03-21

418

Adsorption of ammonia on multilayer iron phthalocyanine.  

Digital Repository Infrastructure Vision for European Research (DRIVER)

The adsorption of ammonia on multilayers of well-ordered, flat-lying iron phthalocyanine (FePc) molecules on a Au(111) support was investigated by x-ray photoelectron spectroscopy. We find that the electron-donating ammonia molecules coordinate to the metal centers of iron phthlalocyanine. The coordination of ammonia induces changes of the electronic structure of the iron phthalocyanine layer, which, in particular, lead to a modification of the FePc valence electron spin.

Isvoranu, Cristina; Knudsen, Jan; Ataman, Evren; Schulte, Karina; Wang, Bin; Bocquet, Marie-laure; Andersen, Jesper N.; Schnadt, Joachim

2011-01-01

419

Control of residual stress in extreme ultraviolet multilayer coatings  

International Nuclear Information System (INIS)

Study of stress in Mo/Si multilayers is carried out for application of extreme ultraviolet multilayer coatings in the diagnosis of high density plasmas and extreme ultraviolet lithography. Stress generating mechanisms is discussed. Precise measurement of stress is taken by ZYGO interferometer. It is observed that the growth of the Mo component in the multilayers is tensile, while that of the Si component is compressive. The residual stress in a 40-bilayer Mo/Si multilayer coating with high reflectivity is -500 MPa (compressive), stress generation may be attributed to the interfacial diffusion. By varying Mo-to Si thickness ratio (?), the stress in multilayers can be compensated to a certain extent. However, the reflectance of Mo/Si multilayers is reduced correspondently. (authors)

2005-03-01

420

Oxaliplatin in Treating Young Patients With Recurrent Solid Tumors That Have Not Responded to Previous Treatment  

Science.gov (United States)

Childhood Central Nervous System Germ Cell Tumor; Childhood Extragonadal Germ Cell Tumor; Childhood Hepatoblastoma; Childhood Hepatocellular Carcinoma; Childhood High-grade Cerebral Astrocytoma; Childhood Low-grade Cerebral Astrocytoma; Childhood Malignant Ovarian Germ Cell Tumor; Childhood Malignant Testicular Germ Cell Tumor; Childhood Teratoma; Recurrent Adrenocortical Carcinoma; Recurrent Childhood Brain Stem Glioma; Recurrent Childhood Cerebellar Astrocytoma; Recurrent Childhood Cerebral Astrocytoma; Recurrent Childhood Ependymoma; Recurrent Childhood Liver Cancer; Recurrent Childhood Malignant Germ Cell Tumor; Recurrent Childhood Rhabdomyosarcoma; Recurrent Childhood Soft Tissue Sarcoma; Recurrent Childhood Visual Pathway and Hypothalamic Glioma; Recurrent Colon Cancer; Recurrent Ewing Sarcoma/Peripheral Primitive Neuroectodermal Tumor; Recurrent Nasopharyngeal Cancer; Recurrent Neuroblastoma; Recurrent Osteosarcoma; Recurrent Rectal Cancer; Recurrent Renal Cell Cancer

2013-06-04

 
 
 
 
421

Infrared Transmission in Porous Silicon Multilayers  

Directory of Open Access Journals (Sweden)

Full Text Available Porous silicon is a nanostructured material and exhibits efficient photo- and electro-luminescence in the visible range at room temperature, as well as a tunable refractive index determined by its porosity. Porous silicon samples can be obtained by etching a crystalline silicon wafer in a solution of hydrofluoric acid. In this work, we report the fabrication of porous silicon multilayers alternating layers with high and low porosities, which correspondingly produce low and high refractive indices. The free-standing multilayers were formed following three different sequences: periodic, Fibonacci and ThueMorse. These structures were verified by scanning electron microscopy and their infrared transmission spectra were measured by means of Fourier-transform infrared spectroscopy. On the other hand, we calculate the light transmittance of porous silicon multilayers by using the transfer matrix method for all directions of incidence and a wide range of wavelengths. The experimental measurements are compared with theoretical results and a good agreement is observed. In addition, an analysis of infrared absorption peaks due to the molecular vibrations at pore surfaces reveals the presence of hydrogen and oxygen atoms.

Alessio Palavicini

2013-06-01

422

Multilayer polymeric color-shifting polarizer films  

Science.gov (United States)

Color-shifts have been used in the field of optical security for many years. Through the use of birefringent polymers, 3M has pioneered highly reflective, multilayer, all-polymeric interference optical films for use as mirrors and polarizers. Polarizer and mirror multilayer films with reflectance bands covering all of the visible wavelengths have found uses in LCD displays and solar light pipes. Color-shifting polarizer (CSP) films may be made by uniaxially orienting a multilayer stack that has sharp band edges and does not cover all of the visible wavelengths. By judicious choice of polymers, the refractive indices of the two polymers have a large difference in refractive index in the stretch direction and match in the transverse direction. The resulting film has a noticeable color shift to the unaided eye, and a readily verifiable feature when viewed with both polarization states. In the pass condition, the film becomes colorless; in the block direction, the color is very saturated and noticeably shifts in hue when the viewing angle is changed. The films may have reverse printing under the CSP films, which hides during verification. The indelible marking of the film for the intended end use and the tamper resistance of labels made from these films will also be discussed.

Jonza, James M.; Dubner, Andrew D.

2004-06-01

423

Performance of multilayer coated silicon pore optics  

DEFF Research Database (Denmark)

The requirements for the IXO (International X-ray Observatory) telescope are very challenging in respect of angular resolution and effective area. Within a clear aperture with 1.7 m > R > 0.25 m that is dictated by the spacecraft envelope, the optics technology must be developed to satisfy simultaneously requirements for effective area of 2.5 m2 at 1.25 keV, 0.65 m2 at 6 keV and 150 cm2 at 30 keV. The reflectivity of the bare mirror substrate materials does not allow these requirements to be met. As such the IXO baseline design contains a coating layout that varies as a function of mirror radius and in accordance with the variation in grazing incidence angle. The higher energy photon response is enhanced through the use of depth-graded multilayer coatings on the inner radii mirror modules. In this paper we report on the first reflectivity measurements of wedged ribbed silicon pore optics mirror plates coated with a depth graded W/Si multilayer. The measurements demonstrate that the deposition and performance of the multilayer coatings is compatible with the SPO production process.

Ackermann, M. D.; Collon, M. J.

2010-01-01

424

Heat Transfer in High Temperature Multilayer Insulation  

Science.gov (United States)

High temperature multilayer insulations have been investigated as an effective component of thermal-protection systems for atmospheric re-entry of reusable launch vehicles. Heat transfer in multilayer insulations consisting of thin, gold-coated, ceramic reflective foils and Saffil(TradeMark) fibrous insulation spacers was studied both numerically and experimentally. A finite volume numerical thermal model using combined conduction (gaseous and solid) and radiation in porous media was developed. A two-flux model with anisotropic scattering was used for radiation heat transfer in the fibrous insulation spacers between the reflective foils. The thermal model was validated by comparison with effective thermal conductivity measurements in an apparatus based on ASTM standard C201. Measurements were performed at environmental pressures in the range from 1x10(exp -4) to 760 torr over the temperature range from 300 to 1300 K. Four multilayer samples with nominal densities of 48 kg/cu m were tested. The first sample was 13.3 mm thick and had four evenly spaced reflective foils. The other three samples were 26.6 mm thick and utilized either one, two, or four reflective foils, located near the hot boundary with nominal foil spacing of 1.7 mm. The validated thermal model was then used to study relevant design parameters, such as reflective foil spacing and location in the stack-up and coating of one or both sides of foils.

Daryabeigi, Kamran; Miller, Steve D.; Cunnington, George R.

2007-01-01

425

Treatment of locally recurrent rectal cancer  

International Nuclear Information System (INIS)

The suggested classifications of locally recurrent rectal cancer are based on the presence of symptoms and the degree of tumour fixation to the pelvic wall, or, otherwise, account for factor T in the TMN system. Although the results of rectal cancer treatment have improved, which may be attributed to total meso rectal excision and application of perioperative radiotherapy and radiochemotherapy, the ratio of cases of locally recurrent rectal cancer still amount from several to over a dozen percent. Among the available diagnostic methods for detecting locally recurrent rectal cancer after anterior rectal resection, endorectal sonography is of special importance. In the estimation of prognostic factors the lack of vascular invasion in recurrent cancer and the long period between the treatment of primary rectal cancer and the development of recurrence are a sign of good prognosis, while pain prior to recurrence treatment and male sex diminish the chances for cure. Locally recurrent rectal cancer impairs the patient's quality of life in all measurable aspects, but even after complete recovery we observe severe disturbances of sexual activity in most patients, and a number of patients require hygiene pads or suffer from chronic pain. Local recurrence of rectal cancer is more commonly qualified for excision after surgical treatment only, than after preoperative radiotherapy. The probability of total recurrent rectal cancer excision increases when the patient is younger, the primary tumours was less advanced and the first operation was sphincter-sparing surgery. Progress in the surgical treatment of recurrent rectal cancer was brought on by the introduction of the composite musculocutaneous flap to compensate the loss of perineal tissue. The application of intraoperative radiotherapy improves treatment results of recurrent rectal cancer, however at the cost of more frequent, serious postoperative complications and intense pain. In inoperable cases high dose regional chemotherapy accounts for some 30% of responses which last for several months. After RO resections of locally recurrent rectal cancer combined with intraoperative radiotherapy and chemotherapy 5-year survival periods are obtained in approx. 35 % of cases. If complete response (pTO) is observed within the excised tissues after preoperative radio- or chemotherapy the likelihood of curability is significantly higher. Recurrence after local excision or electrocoagulation of rectal cancer can be efficiently treated with abdomino-perneal resection. According to various sources, perioperative mortality in patients with locally recurrent rectal cancer ranges from null to 30%. Local recurrence of rectal cancer should be treated in well equipped institutions with a high reference status.(author)

2007-01-01

426

Postmastectomy locoregional recurrence and recurrence-free survival in breast cancer patients  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Abstract Background One essential outcome after breast cancer treatment is recurrence of the disease. Treatment decision is based on assessment of prognostic factors of breast cancer recurrence. This study was to investigate the prognostic factors for postmastectomy locoregional recurrence (LRR) and survival in those patients. Methods 114 patients undergoing mastectomy and adjuvant radiotherapy in Cancer Institute of Tehran University of Medical Sciences were re...

2010-01-01

427

Recurrence after operative management of intrahepatic cholangiocarcinoma  

Science.gov (United States)

Introduction Data on recurrence after operation for intrahepatic cholangiocarcinoma (ICC) are limited. We sought to investigate rates and patterns of recurrence in patients after operative intervention for ICC. Methods We identified 301 patients who underwent operation for ICC between 1990 and 2011 from an international, multi-institutional database. Clinicopathologic data, recurrence patterns, and recurrence-free survival (RFS) were analyzed. Results During the median follow up duration of 31 months (range 1–208), 53.5% developed a recurrence. Median RFS was 20.2 months and 5-year actuarial disease-free survival, 32.1%. The most common site for initial recurrence after operation of ICC was intrahepatic (n = 98; 60.9%), followed by simultaneous intra- and extrahepatic disease (n = 30; 18.6%); 33 (21.0%) patients developed extra-hepatic recurrence only as the first site of recurrence. Macrovascular invasion (hazard ratio [HR], 2.08; 95% confidence interval [CI], 1.34–3.21; P <.001), nodal metastasis (HR, 1.55; 95% CI, 1.01–2.45; P = .04), unknown nodal status (HR, 1.57; 95% CI, 1.10–2.25; P = .04), and tumor size ?5 cm (HR, 1.84; 95% CI, 1.28–2.65; P <.001) were independently associated with increased risk of recurrence. Patients were assigned a clinical score from 0 to 3 according to the presence of these risk factors. The 5-year RFS for patients with scores of 0, 1, 2, and 3 was 61.8%, 36.2%, 19.5%, and 9.6%, respectively. Conclusion Recurrence after operative intervention for ICC was common. Disease recurred both at intra-and extrahepatic sites with roughly the same frequency. Factors such as lymph node metastasis, tumor size, and vascular invasion predict highest risk of recurrence.

Hyder, Omar; Hatzaras, Ioannis; Sotiropoulos, Georgios C.; Paul, Andreas; Alexandrescu, Sorin; Marques, Hugo; Pulitano, Carlo; Barroso, Eduardo; Clary, Bryan M.; Aldrighetti, Luca; Ferrone, Cristina R.; Zhu, Andrew X.; Bauer, Todd W.; Walters, Dustin M.; Groeschl, Ryan; Gamblin, T. Clark; Marsh, J. Wallis; Nguyen, Kevin T.; Turley, Ryan; Popescu, Irinel; Hubert, Catherine; Meyer, Stephanie; Choti, Michael A.; Gigot, Jean-Francois; Mentha, Gilles; Pawlik, Timothy M.

2014-01-01

428

Recurrent Priapism from Therapeutic Quetiapine  

Directory of Open Access Journals (Sweden)

Full Text Available Priapism is rarely related to use of non-erectile related medications. The objective was to educate about the multiple possible causes of priapism and to provide treatment recommendations for the different types of priapism. We present the case of a 43 year-old African American male with a history of schizoaffective disorder who presented to our emergency department multiple times over a three year period with priapism, each episode related to the ingestion of quetiapine. Following penile aspiration and intercavernosal injection of phenylephrine, this patient had resolution of his priapism. This case demonstrates an unusual case of recurrent priapism. [West J Emerg Med. 2014;15(1:114–116.

Omeed Saghafi

2014-02-01

429

Chronic recurrent multifocal osteomyelitis (CRMO)  

International Nuclear Information System (INIS)

Chronic recurrent multifocal osteomyelitis (CRMO) is an unusual clinical entity. More than 200 cases are described in the literature and it is presented here with special reference to its radiological aspects. It is an acquired disease of the skeleton which occurs predominantly during childhood and adolescence. About ten per cent of cases begin in early or, rarely, in later adult life. This variant is described here for the first time and is discussed as 'adult CRMO'. The underlying pathology is a bland, predominantly lympho-plasma cellular osteomyelitis which is self-limiting and leads to bone sclerosis (Garre). It probably involves an abnormal immune process which follows an infection but remains clinically latent and remains aseptic and sterile. In a quarter of cases there is an association with pustulosis palmo-plantaris and its relationship with psoriatic arthropathy is discussed. The clinical, histopathological and imaging features (radiological and particularly MRT) and the bone changes are described. (orig./AJ)

1998-02-01

430

Tensile and fatigue properties of ultrafine Cu-Ni multilayers  

Science.gov (United States)

Tensile and fatigue properties of Cu-Ni multilayers with different nominal individual layer thicknesses (?) (10-100 nm) on a polyimide substrate were investigated. The nominal yield strength and fatigue strength of the multilayer/polyimide composite as a function of ? were determined. The experimental results indicate that both yield and fatigue strengths increase as ? decreases until ? is less than 20 nm. Tensile and fatigue cracking behaviour were examined to understand the damage mechanism of the ultrafine metallic multilayers.

Zhu, X F; Zhang, G P

2009-03-01

431

Hall Effect in Multilayers Based on Pd and Fe  

Directory of Open Access Journals (Sweden)

Full Text Available The paper presents results of experimental investigations of singularities of the Hall effect in multilayers based on Pd and Fe. It is shown that the value of the Hall coefficient depends on the total thickness of the multilayer (the number of fragments, thickness of the nonmagnetic layer and the range of annealing studied film samples. A satisfactory agreement between experimental and calculated data of based on the model of parallel connection of individual fragments of a multilayer.

O.P. ?kach

2011-01-01

432

High temperature stability multilayers for EUV condenser optics  

Energy Technology Data Exchange (ETDEWEB)

We investigate the thermal stability of Mo/SiC multilayer coatings at elevated temperatures. Transmission electron microscopy and x-ray diffraction studies show that upon annealing a thermally-induced structural relaxation occurs that transforms the polycrystalline Mo and amorphous SiC layers in as-deposited multilayers into amorphous Mo-Si-C alloy and crystalline SiC, respectively. After this relaxation process is complete the multilayer is stable at temperatures up to 400 C.

Bajt, S; Stearns, D G

2005-05-03

433

Young's modulus of polyelectrolyte multilayers from microcapsule swelling  

CERN Multimedia

We measure Young's modulus of a free polyelectrolyte multilayer film by studying osmotically induced swelling of polyelectrolyte multilayer microcapsules filled with the polyelectrolyte solution. Different filling techniques and core templates were used for the capsule preparation. Varying the concentration of the polyelectrolyte inside the capsule, its radius and the shell thickness yielded an estimate of an upper limit for Young's modulus of the order of 100 MPa. This corresponds to an elastomer and reflects strong interactions between polyanions and polycations in the multilayer.

Vinogradova, O I; Lulevich, V V; Nordschild, S; Sukhorukov, G B

2003-01-01

434

Periodic Planar Multilayered Substrates Analysis Using Wave Concept Iterative Process  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Due to the practical importance and difficulties associated with their closed form solutions, the experimental and computational study of periodic planar multilayered structures, such as FSS in multilayered configuration and Multilayered Planar antennas array, are in complementary progress. During the past two decades, the widespread use of such methods has allowed a broad range of important scattering problems involving non-standard shapes, boundary conditions and material composition to be ...

2012-01-01

435

Polymerization of amphiphilic dienes in Langmuir-Blodgett multilayers  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Amphiphilic derivatives of octadiene and docosadiene were investigated in monolayers and Langmuir-Blodgett multilayers, with respect to their self-organization and their polymerization behavior. All amphiphiles investigated form monolayers. However, only acid and alcohol derivatives were able to build up multilayers. Those multilayers are rapidly photopolymerized in the layers via a two-step process: Irradiation with long-wavelength UV light yields soluble polymers, whereas additional irradia...

1988-01-01

436

Stress in tungsten carbide-diamond like carbon multilayer coatings:  

Digital Repository Infrastructure Vision for European Research (DRIVER)

Tungsten carbide-diamond like carbon (WC-DLC) multilayer coatings have been prepared by sputter deposition from a tungsten-carbide target and periodic switching on and off of the reactive acetylene gas flow. The stress in the resulting WC-DLC multilayers has been studied by substrate curvature. Periodicity and microstructure have been studied by transmission electron microscopy. It has been observed that compressive stress in the multilayers decreases when the bilayer thickness is reduced. Re...

2007-01-01

437

Recurrence models of volcanic events  

International Nuclear Information System (INIS)

An assessment of the risk of future volcanism has been conducted for isolation of high-level radioactive waste at the potential Yucca Mountain site in southern Nevada. Volcanism studies for the Yucca Mountain Site Characterization Project have progressed to a sufficient degree that it is now prudent to work toward concluding aspects of the work. An advantage of a probabilistic approach to volcanic risk is that it assigns a structured formalism to the problem. This formalism subdivides a complex issue into logical sections. The significance of uncertainty or differences in scientific opinion concerning volcanism issues can be tested for each section of a probabilistic problem. The perspective for making judgement of significance for volcanism studied are the regulatory requirements for assessing the suitability of the potential Yucca Mountain site. This paper attempts to begin the process of helping establish the probabilistic framework for making those judgement. There are three objectives. First, the authors describe the tripartite probability used to define the risk of volcanism and the geologic assumptions required for the probability model. Second, the authors examine and define the first part of this probability, the recurrence of volcanic events. Studies are reviewed from the volcanological literature where time-volume behavior of volcanic centers and fields have been evaluated. These evaluations include both conventional statistical analysis of time-series of volcanic events and applications using newly developing concepts of fractal analysis and deterministic chaos. Third, the authors tabulate past calculations and derive new values for the recurrence of volcanic events using a simple Poison model

1992-04-12

438

76 FR 92 - Multilayered Wood Flooring From the People's Republic of China: Postponement of Preliminary...  

Science.gov (United States)

...Administration [C-570-971] Multilayered Wood Flooring From the People's Republic of...initiated an investigation of multilayered wood flooring from the People's Republic of China (``PRC''). See Multilayered Wood Flooring From the People's Republic...

2011-01-03

439

76 FR 13357 - Multilayered Wood Flooring from the People's Republic of China: Postponement of Preliminary...  

Science.gov (United States)

...Administration [A-570-970] Multilayered Wood Flooring from the People's Republic of...antidumping duty investigation on multilayered wood flooring from the People's Republic of...1\\ See Multilayered Wood Flooring from the People's Republic...

2011-03-11

440

78 FR 46318 - Multilayered Wood Flooring From the People's Republic of China: Initiation of Antidumping Duty...  

Science.gov (United States)

...Administration [A-570-970] Multilayered Wood Flooring From the People's Republic of...antidumping duty order on multilayered wood flooring from the People's Republic of...antidumping duty order on multilayered wood flooring from the PRC on December 8,...

2013-07-31

 
 
 
 
441

Multilayer relaxation in metallic surfaces as demonstrated by LEED analysis  

Energy Technology Data Exchange (ETDEWEB)

Theoretical motivations are reviewed for investigation of multilayer relaxation in relatively simple metallic surfaces. Results from LEED analyses are presented which serve to demonstrate that multilayer relaxation measurably exists in Cu(100) and Cu(110) surfaces. The results from two independent LEED analyses for Cu(110) are shown to be in much better agreement with each other than the LEED results are with multilayer relaxation results obtained by high energy ion scattering. Multilayer relaxation results for other metallic surfaces also are reviewed briefly, and all available results are discussed in relationship to those obtained by a theoretical, model-type, inquiry of Landman, Hill and Mostoller.

Davis, H.L.; Noonan, J.R.

1982-07-01

442

New layer-by-layer multilayer design method.  

Science.gov (United States)

A new layer-by-layer multilayer design method is presented. The method is demonstrated mathematically and makes possible the optimization of the multilayer for the highest possible reflectance either at normal incidence or at nonnormal incidence for s- or p-polarized radiation. With the current method multilayers can be designed regardless of the number of different materials used. The optimum layer thickness is determined by means of functions suitable for implementation in a computer code. The new multilayer design method is fast and accurate. PMID:11822602

Larruquert, Juan I

2002-02-01

443

Molecular dynamics simulations of multilayer films of polyelectrolytes and nanoparticles.  

Science.gov (United States)

We performed molecular dynamics simulations of multilayer assemblies of flexible polyelectrolytes and nanoparticles. The film was constructed by sequential adsorption of oppositely charged polymers and nanoparticles in layer-by-layer fashion from dilute solutions. We have studied multilayer films assembled from oppositely charged polyelectrolytes, oppositely charged nanoparticles, and mixed films containing both nanoparticles and polyelectrolytes. For all studied systems, the multilayer assembly proceeds through surface overcharging after completion of each deposition step. There is almost linear growth in the surface coverage and film thickness. The multilayer films assembled from nanoparticles show better layer stratification but at the same time have higher film roughness than those assembled from flexible polyelectrolytes. PMID:16649774

Jeon, Junhwan; Panchagnula, Venkateswarlu; Pan, Jessica; Dobrynin, Andrey V

2006-05-01

444

High activity iodine 125 endocurietherapy for recurrent skull base tumors  

International Nuclear Information System (INIS)

Experience with endocurietherapy of skull base tumors is reviewed. We present our cases of recurrent pituitary hemangiopericytoma, radiation-induced recurrent meningioma, recurrent clival chordoma, recurrent nasopharyngeal cancer involving the cavernous sinus, and recurrent parotid carcinoma of the skull base which were all successfully retreated with high-activity 125-iodine (I-125) permanent implantation.76 references

1988-04-15

445

High activity iodine 125 endocurietherapy for recurrent skull base tumors  

Energy Technology Data Exchange (ETDEWEB)

Experience with endocurietherapy of skull base tumors is reviewed. We present our cases of recurrent pituitary hemangiopericytoma, radiation-induced recurrent meningioma, recurrent clival chordoma, recurrent nasopharyngeal cancer involving the cavernous sinus, and recurrent parotid carcinoma of the skull base which were all successfully retreated with high-activity 125-iodine (I-125) permanent implantation.76 references.

Kumar, P.P.; Good, R.R.; Leibrock, L.G.; Mawk, J.R.; Yonkers, A.J.; Ogren, F.P.

1988-04-15

446

Recurrent Malignant Pleural Mesothelioma: Case Report  

Digital Repository Infrastructure Vision for European Research (DRIVER)

A 42-year-old woman with malignant pleural mesothelioma was admitted initially to the Texas Heart Institute in 1967 for removal of a chest wall tumor. She subsequently underwent 17 additional thoracotomies for removal of recurrent localized tumor during a 15-year period. She died in 1982 at age 56 from cardiopulmonary failure secondary to extensive recurrent mesothelioma.

Cooley, Denton A.; Frazier, O. Howard

1983-01-01