WorldWideScience
1

Algorithm for Training a Recurrent Multilayer Perceptron  

Science.gov (United States)

An improved algorithm has been devised for training a recurrent multilayer perceptron (RMLP) for optimal performance in predicting the behavior of a complex, dynamic, and noisy system multiple time steps into the future. [An RMLP is a computational neural network with self-feedback and cross-talk (both delayed by one time step) among neurons in hidden layers]. Like other neural-network-training algorithms, this algorithm adjusts network biases and synaptic-connection weights according to a gradient-descent rule. The distinguishing feature of this algorithm is a combination of global feedback (the use of predictions as well as the current output value in computing the gradient at each time step) and recursiveness. The recursive aspect of the algorithm lies in the inclusion of the gradient of predictions at each time step with respect to the predictions at the preceding time step; this recursion enables the RMLP to learn the dynamics. It has been conjectured that carrying the recursion to even earlier time steps would enable the RMLP to represent a noisier, more complex system.

Parlos, Alexander G.; Rais, Omar T.; Menon, Sunil K.; Atiya, Amir F.

2004-01-01

2

Modular, Multilayer Perceptron  

Science.gov (United States)

Combination of proposed modular, multilayer perceptron and algorithm for its operation recognizes new objects after relatively brief retraining sessions. (Perceptron is multilayer, feedforward artificial neural network fully connected and trained via back-propagation learning algorithm.) Knowledge pertaining to each object to be recognized resides in subnetwork of full network, therefore not necessary to retrain full network to recognize each new object.

Cheng, Li-Jen; Liu, Tsuen-Hsi

1991-01-01

3

Multilayer perceptron for nonlinear programming  

International Nuclear Information System (INIS)

A new method for solving nonlinear programming problems within the framework of a multilayer neural network perceptron is proposed. The method employs the Penalty Function method to transform a constrained optimization problem into a sequence of unconstrained optimization problems and then solves the sequence of unconstrained optimizations of the transformed problem by training a series of multilayer perceptrons. The neural network formulation is represented in such a way that the multilayer perceptron prediction error to be minimized mimics the objective function of the unconstrained problem, and therefore, the minimization of the objective function for each unconstrained optimization is attained by training a single perceptron. The multilayer perceptron allows for the transformation of problems with two-sided bounding constraints on the decision variables x, e.g., a?xn?b, into equivalent optimization problems in which these constraints do not explicitly appear. Hence, when these are the only constraints in the problem, the transformed problem is constraint free (i.e., the transformed objective function contains no penalty terms) and is solved by training a multilayer perceptron only once. In addition, we present a new Penalty Function method for solving nonlinear programming problems that is parameter free and guarantees that feasible solutions are obtained when the optimal solution is on the boundary of the feasible region. Simulation results, includble region. Simulation results, including an example from operations research, illustrate the proposed methods.

4

Auto-kernel using multilayer perceptron  

Directory of Open Access Journals (Sweden)

Full Text Available 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

2012-06-01

5

Auto-kernel using multilayer perceptron  

OpenAIRE

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

6

Quaternionic Multilayer Perceptron with Local Analyticity  

Directory of Open Access Journals (Sweden)

Full Text Available 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 the network.

Nobuyuki Matsui

2012-11-01

7

Quaternionic Multilayer Perceptron with Local Analyticity  

OpenAIRE

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...

Nobuyuki Matsui; Haruhiko Nishimura; Teijiro Isokawa

2012-01-01

8

Multilayer perceptron, fuzzy sets, and classification  

Science.gov (United States)

A fuzzy neural network model based on the multilayer perceptron, using the back-propagation algorithm, and capable of fuzzy classification of patterns is described. The input vector consists of membership values to linguistic properties while the output vector is defined in terms of fuzzy class membership values. This allows efficient modeling of fuzzy or uncertain patterns with appropriate weights being assigned to the backpropagated errors depending upon the membership values at the corresponding outputs. During training, the learning rate is gradually decreased in discrete steps until the network converges to a minimum error solution. The effectiveness of the algorithm is demonstrated on a speech recognition problem. The results are compared with those of the conventional MLP, the Bayes classifier, and the other related models.

Pal, Sankar K.; Mitra, Sushmita

1992-01-01

9

Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment  

OpenAIRE

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...

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

2005-01-01

10

Efficient Estimation of Multidimensional Regression Model with Multilayer Perceptron  

OpenAIRE

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

11

Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics  

Directory of Open Access Journals (Sweden)

Full Text Available 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.

N. Pedroni

2008-03-01

12

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

13

Fourier-Lapped Multilayer Perceptron Method for Speech Quality Assessment  

Directory of Open Access Journals (Sweden)

Full Text Available 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 scaled conjugated gradient method. This neural network maps the perceptual parameters into a subjective score. The numerical results show that FLMLP is an effective alternative to previous methods. As a result, it is worth stating that the techniques here described may be potentially useful to other researches facing the same kind of problem.

Ribeiro MoisésVidal

2005-01-01

14

Conventional modeling of the multilayer perceptron using polynomial basis functions  

Science.gov (United States)

A technique for modeling the multilayer perceptron (MLP) neural network, in which input and hidden units are represented by polynomial basis functions (PBFs), is presented. The MLP output is expressed as a linear combination of the PBFs and can therefore be expressed as a polynomial function of its inputs. Thus, the MLP is isomorphic to conventional polynomial discriminant classifiers or Volterra filters. The modeling technique was successfully applied to several trained MLP networks.

Chen, Mu-Song; Manry, Michael T.

1993-01-01

15

Asymptotic law of likelihood ratio for multilayer perceptron models  

OpenAIRE

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

16

A Parallel Framework for Multilayer Perceptron for Human Face Recognition  

OpenAIRE

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...

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

2010-01-01

17

Newton's Method Backpropagation for Complex-Valued Holomorphic Multilayer Perceptrons  

OpenAIRE

The study of Newton's method in complex-valued neural networks faces many difficulties. In this paper, we derive Newton's method backpropagation algorithms for complex-valued holomorphic multilayer perceptrons, and investigate the convergence of the one-step Newton steplength algorithm for the minimization of real-valued complex functions via Newton's method. To provide experimental support for the use of holomorphic activation functions, we perform a comparison of using sig...

La Corte, Diana Thomson; Zou, Yi Ming

2014-01-01

18

A Parallel Framework for Multilayer Perceptron for Human Face Recognition  

CERN Document Server

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 Perceptron (MLP) have been demonstrated. The first architecture is All-Class-in-One-Network (ACON) where all the classes are placed in a single network and the second one is One-Class-in-One-Network (OCON) where an individual single network is responsible for each and every class. Capabilities of these two architectures were compared and verified in solving human face recognition, which is a complex pattern recognition task where several factors affect the recognition performance like pose variations, facial expression changes, occlusions, and ...

Bhowmik, M K; Nasipuri, M; Basu, D K; Kundu, M

2010-01-01

19

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

OpenAIRE

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

20

Error correcting code using tree-like multilayer perceptron  

OpenAIRE

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 Parallel Framework for Multilayer Perceptron for Human Face Recognition  

Directory of Open Access Journals (Sweden)

Full Text Available 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 Perceptron (MLP have been demonstrated. The first architecture is All-Class-in-One-Network (ACON where all the classes are placed in a single network and the second one is One-Class-in-One-Network (OCON where an individual single network is responsible for each and every class. Capabilities of these two architectures were compared and verified in solving human face recognition, which is a complex pattern recognition task where several factors affect the recognition performance like pose variations, facial expression changes, occlusions, and most importantly illumination changes. Experimental results show that the proposed OCON structure performs better than the conventional ACON in terms of network training convergence speed and which can be easily exercised in a parallel environment.

Mita Nasipuri

2010-01-01

22

Optical proximity correction using a multilayer perceptron neural network  

International Nuclear Information System (INIS)

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. (paper)

23

Inversion of Self Potential Anomalies with Multilayer Perceptron Neural Networks  

Science.gov (United States)

This study investigates the inverse solution on a buried and polarized sphere-shaped body using the self-potential method via multilayer perceptron neural networks (MLPNN). The polarization angle ( ?), depth to the centre of sphere ( h), electrical dipole moment ( K) and the zero distance from the origin ( x 0) were estimated. For testing the success of the MLPNN for sphere model, parameters were also estimated by the traditional Damped Least Squares (Levenberg-Marquardt) inversion technique (DLS). The MLPNN was first tested on a synthetic example. The performance of method was also tested for two S/N ratios (5 % and 10 %) by adding noise to the same synthetic data, the estimated model parameters with MLPNN and DLS method are satisfactory. The MLPNN also applied for the field data example in ?zmir, Urla district, Turkey, with two cross-section data evaluated by MLPNN and DLS, and the two methods showed good agreement.

Kaftan, Ilknur; S?nd?rg?, Petek; Akdemir, Özer

2014-08-01

24

Classification of fused face images using multilayer perceptron neural network  

CERN Document Server

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. Fused 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 and visual face images. Experimental results show that the proposed approach significantly improves the verification and identification performance and the success rate is 95.07%. The main objective of employing fusion is to produce a fused image that provides the most detailed and reliable information. Fusion of multip...

Bhattacharjee, Debotosh; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

2010-01-01

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

Prediction of Parametric Roll Resonance by Multilayer Perceptron Neural Network  

DEFF Research Database (Denmark)

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 by feeding it with simulated data of a three degrees-of-freedom nonlinear model of a fishing vessel. The neural network is shown to be capable of forecasting the ship’s roll motion in realistic scenarios.

Míguez González, M; López Peña, F.

2011-01-01

27

Dynamics of a multi-layered perceptron model : a rigorous result  

OpenAIRE

We derive exactly and rigorously the system of dynamical equations for a multi-layered perceptron proposed by Domany, Meir and Kinzel (DMK-model). They describes both the main and the residual overlaps evolution.

Patrick, A. E.; Zagrebnov, V. A.

1990-01-01

28

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

OpenAIRE

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

29

Group Session Key Exchange Multilayer Perceptron Based Simulated Annealing Guided Automata and Comparison Based Metamorphosed Encryption in Wireless Communication (GSMLPSA)  

OpenAIRE

In this paper, a group session Key Exchange multilayer Perceptron based Simulated Annealing guidedAutomata and Comparison based Metamorphosed encryption technique (GSMLPSA) has been proposed inwireless communication of data/information. Both sender and receiver uses identical multilayer perceptronand depending on the final output of the both side multilayer perceptron, weights vector of hidden layer gettuned in both ends. As a results both perceptrons generates identical weight vectors which ...

Arindam Sarkar; Mandal, J. K.

2013-01-01

30

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

31

Classification of Log-Polar-Visual Eigenfaces using Multilayer Perceptron  

CERN Document Server

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

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 exercisemodels. Caution, however, must be exercised because extensive on-line validation of these models is still warranted

33

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

34

Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking  

DEFF Research Database (Denmark)

A multilayer perceptron neural network cloud mask for Meteosat Second Generation SEVIRI (Spinning Enhanced Visible and Infrared Imager) images is introduced and evaluated. The model is trained for cloud detection on MSG SEVIRI daytime data. It consists of a multi-layer perceptron with one hidden sigmoid layer, trained with the error back-propagation algorithm. The model is fed by six bands of MSG data (0.6, 0.8, 1.6, 3.9, 6.2 and 10.8 ?m) with 10 hidden nodes. The multiple-layer perceptrons lead to a cloud detection accuracy of 88.96%, when trained to map two predefined values that classify cloud and clear sky. The network was further evaluated using sixty MSG images taken at different dates. The network detected not only bright thick clouds but also thin or less bright clouds. The analysis demonstrated the feasibility of using machine learning models of cloud detection in MSG SEVIRI imagery.

Proud, Simon Richard

2015-01-01

35

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

36

Application of multilayer perceptron for prediction of radionuclide migration from catchment area to watercourse  

International Nuclear Information System (INIS)

In the thesis the results of verification of multilayer perceptron (MLP) {20–41–1} application with sigmoid activation function for prediction of lateral radionuclide migration are presented. The calculated values of Cs 137 and Sr 90 volumetric activity are close to experimental measurement limits, indicating the possibility of MLP application for the solving problem. (authors)

37

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

OpenAIRE

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.

Charniya, Nadir N.

2013-01-01

38

Classification of non-performing loans portfolio using Multilayer Perceptron artificial neural networks  

Directory of Open Access Journals (Sweden)

Full Text Available The purpose of the present research is to apply a Multilayer Perceptron (MLP neural network technique to create classification models from a portfolio of Non-Performing Loans (NPLs to classify this type of credit derivative. These credit derivatives are characterized as the amount of loans that were not paid and are already overdue more than 90 days. Since these titles are, because of legislative motives, moved by losses, Credit Rights Investment Funds (FDIC performs the purchase of these debts and the recovery of the credits. Using the Multilayer Perceptron (MLP architecture of Artificial Neural Network (ANN, classification models regarding the posterior recovery of these debts were created. To evaluate the performance of the models, evaluation metrics of classification relating to the neural networks with different architectures were presented. The results of the classifications were satisfactory, given the classification models were successful in the presented economics costs structure.

Flávio Clésio Silva de Souza

2014-06-01

39

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

40

Characterisation of tequila according to their major volatile composition using multilayer perceptron neural networks.  

Science.gov (United States)

Differentiation of silver, gold, aged and extra-aged tequila using 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol and furan derivatives like 5-(hydroxymethyl)-2-furaldehyde and 2-furaldehyde has been carried out. The content of 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol was determined by means of head space solid phase microextraction gas chromatography mass-spectrometry. 5-(Hydroxymethyl)-2-furaldehyde and 2-furaldehyde were determined by high performance liquid chromatography with diode array detection. Kruskal-Wallis test was used to highlight significant differences between types of tequila. Principal component analysis was applied as visualisation technique. Linear discriminant analysis and multilayer perceptron artificial neural networks were used to construct classification models. The best classification performance was obtained when multilayer perceptron model was applied. PMID:23194528

Ceballos-Magaña, Silvia G; de Pablos, Fernando; Jurado, José Marcos; Martín, María Jesús; Alcázar, Ángela; Muñiz-Valencia, Roberto; Gonzalo-Lumbreras, Raquel; Izquierdo-Hornillos, Roberto

2013-02-15

41

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

OpenAIRE

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

42

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

OpenAIRE

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

2007-01-01

43

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

OpenAIRE

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

44

Optimal Parameter for the Training of Multilayer Perceptron Neural Networks by Using Hierarchical Genetic Algorithm  

International Nuclear Information System (INIS)

This paper deals with the controversial topic of the selection of the parameters of a genetic algorithm, in this case hierarchical, used for training of multilayer perceptron neural networks for the binary classification. The parameters to select are the crossover and mutation probabilities of the control and parametric genes and the permanency percent. The results can be considered as a guide for using this kind of algorithm.

45

Models to predict cardiovascular risk: comparison of CART, multilayer perceptron and logistic regression.  

OpenAIRE

The estimate of a multivariate risk is now required in guidelines for cardiovascular prevention. Limitations of existing statistical risk models lead to explore machine-learning methods. This study evaluates the implementation and performance of a decision tree (CART) and a multilayer perceptron (MLP) to predict cardiovascular risk from real data. The study population was randomly splitted in a learning set (n = 10,296) and a test set (n = 5,148). CART and the MLP were implemented at their be...

Colombet, I.; Ruelland, A.; Chatellier, G.; Gueyffier, F.; Degoulet, P.; Jaulent, M. C.

2000-01-01

46

A conjugate gradients/trust regions algorithms for training multilayer perceptrons for nonlinear mapping  

Science.gov (United States)

This paper addresses the issue of applying a globally convergent optimization algorithm to the training of multilayer perceptrons, a class of Artificial Neural Networks. The multilayer perceptrons are trained towards the solution of two highly nonlinear problems: (1) signal detection in a multi-user communication network, and (2) solving the inverse kinematics for a robotic manipulator. The research is motivated by the fact that a multilayer perceptron is theoretically capable of approximating any nonlinear function to within a specified accuracy. The algorithm that has been employed in this study combines the merits of two well known optimization algorithms, the Conjugate Gradients and the Trust Regions Algorithms. The performance is compared to a widely used algorithm, the Backpropagation Algorithm, that is basically a gradient-based algorithm, and hence, slow in converging. The performances of the two algorithms are compared with the convergence rate. Furthermore, in the case of the signal detection problem, performances are also benchmarked by the decision boundaries drawn as well as the probability of error obtained in either case.

Madyastha, Raghavendra K.; Aazhang, Behnaam; Henson, Troy F.; Huxhold, Wendy L.

1992-01-01

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

49

Local minima and plateaus in hierarchical structures of multilayer perceptrons.  

Science.gov (United States)

Local minima and plateaus pose a serious problem in learning of neural networks. We investigate the hierarchical geometric structure of the parameter space of three-layer perceptrons in order to show the existence of local minima and plateaus. It is proved that a critical point of the model with H - 1 hidden units always gives many critical points of the model with H hidden units. These critical points consist of many lines in the parameter space, which can cause plateaus in learning of neural networks. Based on this result, we prove that a point in the critical lines corresponding to the global minimum of the smaller model can be a local minimum or a saddle point of the larger model. We give a necessary and sufficient condition for this, and show that this kind of local minima exist as a line segment if any. The results are universal in the sense that they do not require special properties of the target, loss functions and activation functions, but only use the hierarchical structure of the model. PMID:10937965

Fukumizu, K; Amari, S

2000-04-01

50

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

CERN Document Server

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

51

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

OpenAIRE

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 ac...

Mohammad Fathian,; Kia, Arash N.

2012-01-01

52

An Analog Multilayer Perceptron Neural Network for a Portable Electronic Nose  

OpenAIRE

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 powe...

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

2012-01-01

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

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

55

Belief Propagation for Error Correcting Codes and Lossy Compression Using Multilayer Perceptrons  

CERN Document Server

The belief propagation (BP) based algorithm is investigated as a potential decoder for both of error correcting codes and lossy compression, which are based on non-monotonic tree-like multilayer perceptron encoders. We discuss that whether the BP can give practical algorithms or not in these schemes. The BP implementations in those kind of fully connected networks unfortunately shows strong limitation, while the theoretical results seems a bit promising. Instead, it reveals it might have a rich and complex structure of the solution space via the BP-based algorithms.

Mimura, Kazushi; Okada, Masato

2011-01-01

56

Estimation of Neutronic Performance of a High Power Density Hybrid Reactor by Multilayer Perceptron Neural Networks  

Science.gov (United States)

Artificial neural networks (ANNs) have recently been utilized in the nuclear technology applications since they are fast, precise and flexible vehicles to modeling, simulation and optimization. This paper presents a new approach based on multilayer perceptron neural networks (MLPNNs) for the estimation of some important neutronic parameters (net 239Pu production, tritium breeding ratio, cumulative fissile fuel enrichment, and fission rate) of a high power density fusion-fission (hybrid) reactor using light water reactor (LWR) spent fuel. A comparison of the results obtained by the MLPNNs and those found by using the code (Scale 4.3) was carried out. The results pointed out that the MLPNNs trained with least mean squares (LMS) algorithm could provide an accurate computation of the main neutronic parameters for the high power density reactor.

Übeyli, Mustafa; Übeyli, Elif Derya

2008-12-01

57

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.Defence Science Journal, 2009, 59(6, pp.670-674, DOI:http://dx.doi.org/10.14429/dsj.59.1574

H. S. Krishna

2009-11-01

58

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

CERN Document Server

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

59

Static Digits Recognition Using Rotational Signatures and Hu Moments with a Multilayer Perceptron  

Directory of Open Access Journals (Sweden)

Full Text Available This paper presents two systems for recognizing static signs (digits from American Sign Language (ASL. These systems avoid the use color marks, or gloves, using instead, low-pass and high-pass filters in space and frequency domains, and color space transformations. First system used rotational signatures based on a correlation operator; minimum distance was used for the classification task. Second system computed the seven Hu invariants from binary images; these descriptors fed to a Multi-Layer Perceptron (MLP in order to recognize the 9 different classes. First system achieves 100% of recognition rate with leaving-one-out validation and second experiment performs 96.7% of recognition rate with Hu moments and 100% using 36 normalized moments and k-fold cross validation.

Francisco Solís

2014-10-01

60

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

61

Analysis of (7)Be behaviour in the air by using a multilayer perceptron neural network.  

Science.gov (United States)

A multilayer perceptron artificial neural network (ANN) model for the prediction of the (7)Be behaviour in the air as the function of meteorological parameters was developed. The model was optimized and tested using (7)Be activity concentrations obtained by standard gamma-ray spectrometric analysis of air samples collected in Belgrade (Serbia) during 2009-2011 and meteorological data for the same period. Good correlation (r = 0.91) between experimental values of (7)Be activity concentrations and those predicted by ANN was obtained. The good performance of the model in prediction of (7)Be activity concentrations could provide basis for construction of models which would forecast behaviour of other airborne radionuclides. PMID:25106024

Samolov, A; Dragovi?, S; Dakovi?, M; Ba?i?, G

2014-11-01

62

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

63

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

64

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

65

Meteorological time series forecasting with pruned multi-layer perceptron and 2-stage Levenberg-Marquardt method  

OpenAIRE

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; Nivet, Marie Laure; Notton, Gilles; Paoli, Christophe; Balu, Aure?lia; Muselli, Marc

2014-01-01

66

The application of optimal weights initialization algorithm based on K-L transform in multi-layer perceptron networks  

Science.gov (United States)

The paper presents a novel method of initial weights optimization method in Multi-Layer Perceptron Network(MLPN). Firstly, the sample sets should be transformed by K-L Transform. Secondly, use K-L Converting Matrix to initialize the weights between input and hidden layer. Thirdly the MLPN is trained by BP algorithm, and the convergence speed of MLPN is improved evidently. The ultimate test shows the new algorithm is suitable for the situation of low-dimensional data.

Xiao, Wei; Pu, Dun; Dong, Zhicheng; Liu, Cungen

2013-07-01

67

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

OpenAIRE

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; Paoli, Christophe; Balu, Aure?lia; Muselli, Marc; Nivet, Marie Laure; Notton, Gilles

2013-01-01

68

The use of a multilayer perceptron for detecting new human settlements from a time series of MODIS images  

OpenAIRE

This paper presents a novel land cover change detection method that employs a sliding window over hyper-temporal multi-spectral images acquired from the 7 bands of the MODerate-resolution Imaging Spectroradiometer (MODIS) land surface reflectance product. The method uses a Feedforward Multilayer Perceptron (MLP) for supervised change detection that operates on multi-spectral time series extracted with a sliding window from the dataset. The method was evaluated on both real and simulated land ...

Salmon, Brian Paxton; Olivier, Jan Corne; Kleynhans, Waldo; Wessels, Konrad J.; Den Bergh, Frans; Steenkamp, Karen C.

2011-01-01

69

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

OpenAIRE

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; MAYA NAYAK; SAREETA MOHANTY

2011-01-01

70

Detection of Pathological and Normal Heartbeat Using Wavelet Packet, Support Vector Machines and Multilayer Perceptron  

Directory of Open Access Journals (Sweden)

Full Text Available 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 non-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 %.

Alejandro J. Orozco-Naranjo

2013-11-01

71

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

72

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

73

Explaining critical clearing time with the rules extracted from a multilayer perceptron artificial neural network  

Energy Technology Data Exchange (ETDEWEB)

In the past two decades, artificial neural networks (ANN) have been applied to quickly compute the critical clearing time (CCT), a frequently quoted measurement for power systems transient stability. This kind of applications mainly concerns the CCT prediction rather than the explanation because ANN was commonly considered as a black box. This paper will challenge this myth. In this paper, we describe the procedures for explaining CCT by means of a multilayer perceptron (MLP) artificial neural network. The explanation is expressed in terms of ''IF antecedent THEN consequent'' rules, where the antecedent indicates the power system operating conditions and the consequent refers to whether the CCT is high or low. We can accordingly explain CCT, and in turn we can observe under what circumstances will cause the power system CCT to be high or low. To justify the proposed method, the CCTs of two contingencies in 39-bus power systems are investigated. The results have demonstrated that the CCT can be explained by MLP very well. (author)

Lin, Yu-Jen [Dept. of Electrical Engineering, I-Shou University, Kaohsiung County (China)

2010-10-15

74

Using multilayer perceptron and a satellite image for the estimation of soil salinity  

International Nuclear Information System (INIS)

Applying the model of the Perceptron multilayer with momentum of an artificial neural network particularly and a multispectral image of high resolution spatial and radiometric, for the first time estimated the salinity of the soil cultivated with sugar cane. The study area is the UBPC 'Lazaro Romero' of the sugar company 'Hector Molina' of the locality San Nicolas de Bari, Havana province, located at 22° 44' North latitude and 81 ° 56' longitude West. The experiments were made in the framework of the El-479 project funded by the Inter universities Council of Flanders, Belgium. 36 samples geo referenced of soils were taken at 3 depths in each of the 4 sugar cane selected blocks, which determined the electrical conductivity of the saturation extract; half of that amount of data was used for the training of the network and the other half for control in a computer program of the artificial neural network created to that effect, together with the reflectance of vegetation indexes for the image, which were maps of electrical conductivity of each block and bands. They were compared with those obtained by simple linear regression between the normalized difference vegetation index and electrical conductivity, Ndv with the approach of the neuronal network, the correlation coefficient was 0.78 to 0.83, while the linear regression was between 0.65 to 0.75

75

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

Directory of Open Access Journals (Sweden)

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

76

Group Session Key Exchange Multilayer Perceptron Based Simulated Annealing Guided Automata and Comparison Based Metamorphosed Encryption in Wireless Communication (GSMLPSA  

Directory of Open Access Journals (Sweden)

Full Text Available In this paper, a group session Key Exchange multilayer Perceptron based Simulated Annealing guidedAutomata and Comparison based Metamorphosed encryption technique (GSMLPSA has been proposed inwireless communication of data/information. Both sender and receiver uses identical multilayer perceptronand depending on the final output of the both side multilayer perceptron, weights vector of hidden layer gettuned in both ends. As a results both perceptrons generates identical weight vectors which is consider as anone time session key. In GSMLPSA technique plain text is encrypted using metamorphosed code table forproducing level 1 encrypted text. Then comparison based technique is used to further encerypt the level 1encrypted text and produce level 2 encrypted text. Simulated Annealing based keystream is xored with theleve2 encrypted text and form a level 3 encrypted text. Finally level 3 encrypted text is xored with the MLPbased session key and get transmitted to the receiver. GSMLPSA technique uses two keys for encryptionpurpose. SA based key get further encrypted using Automata based technique and finally xored with MLPbased session key and transmitted to the receiver. This technique ensures that if intruders intercept the keyof the keystream then also values of the key not be known to the intruders because of the automata basedencoding. Receiver will perform same operation in reverse order to get the plain text back. Two partiescan swap over a common key using synchronization between their own multilayer perceptrons. But theproblem crop up when group of N parties desire to swap over a key. Since in this case each communicatingparty has to synchronize with other for swapping over the key. So, if there are N parties then total numberof synchronizations needed before swapping over the actual key is O(N2. GSMLPSA scheme offers a noveltechnique in which complete binary tree structure is follows for key swapping over. Using proposedalgorithm a set of N parties can be able to share a common key with only O(log2 N synchronization.Parametric tests have been done and results are compared with some existing classical techniques, whichshow comparable results for the proposed technique

Arindam Sarkar

2013-08-01

77

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

78

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

Energy Technology Data Exchange (ETDEWEB)

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)

Jun, Sung Chan [Department of Computer Science, University of New Mexico, Albuquerque, NM (Mexico)]. E-mail: junsc@cs.unm.edu; Pearlmutter, Barak A.; Nolte, Guido [Department of Computer Science, University of New Mexico, Albuquerque, NM (Mexico)

2002-07-21

79

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 fase 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) )

80

An Optical Thresholding Perceptron  

OpenAIRE

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

81

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

82

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

OpenAIRE

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

83

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

84

Adaptive Weibull Multiplicative Model and Multilayer Perceptron Neural Networks for Dark-Spot Detection from SAR Imagery  

Directory of Open Access Journals (Sweden)

Full Text Available Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR, as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM and MultiLayer Perceptron (MLP neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN model generates poor accuracies.

Alireza Taravat

2014-12-01

85

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

86

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

87

Adaptive Weibull Multiplicative Model and Multilayer Perceptron neural networks for dark-spot detection from SAR imagery.  

Science.gov (United States)

Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM) and MultiLayer Perceptron (MLP) neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN) model generates poor accuracies. PMID:25474376

Taravat, Alireza; Oppelt, Natascha

2014-01-01

88

Retrieval of pigment concentrations and size structure of algal populations from their absorption spectra using multilayered perceptrons  

Science.gov (United States)

Spectral absorption coefficients of phytoplankton can now be derived, under some assumptions, from hyperspectral ocean color measurements and thus become accessible from space. In this study, multilayer perceptrons have been developed to retrieve information on the pigment composition and size structure of phytoplankton from these absorption spectra. The retrieved variables are the main pigment groups (chlorophylls a, b, c, and photosynthetic and nonphotosynthetic carotenoids) and the relative contributions of three algal size classes (pico-, nano-, and microphytoplankton) to total chlorophyll a. The networks have been trained, tested, and validated using more than 3700 simultaneous absorption and pigment measurements collected in the world ocean. Among pigment groups, chlorophyll a is the most accurately retrieved (average relative errors of 17% and 16% for the test and validation data subsets, respectively), while the poorest performances are found for chlorophyll b (average relative errors of 51% and 40%). Relative contributions of algal size classes to total chlorophyll a are retrieved with average relative errors of 19% to 33% for the test subset and of 18% to 47% for the validation subset. The performances obtained for the validation data, showing no strong degradation with respect to test data, suggest that these neural networks might be operated with similar performances for a large variety of marine areas.

Bricaud, Annick; Mejia, Carlos; Blondeau-Patissier, David; Claustre, Hervé; Crepon, Michel; Thiria, Sylvie

2007-03-01

89

Multilayer perceptron applied to the estimation of the influence of the solar spectral distribution on thin-film photovoltaic modules  

International Nuclear Information System (INIS)

Highlights: • Multilayer perceptrons are used to simulate the I–V curve of thin-film PV modules. • APE from the spectral irradiance was added as an input variable to the network. • A self-organised map is used to select the curves used for training the network. • Curve error and maximum power error decrease when using this technique. • This method could provide accurate estimation of the output of a PV plant. - Abstract: In this paper, we propose the use of a methodology to characterise the electrical parameters of several thin-film photovoltaic module technologies. This methodology allows us to use not only solar irradiance and module temperature as classical models do, but also spectral distribution of solar radiation. The methodology is based on the use of neural network models. From all measured I–V curves of a module, a previous selection of them has been used in order to train the neural network model. This selection is performed using a Kohonen self-organising map fed with spectral data. This spectral information has been added as an input to the neural network itself. The results show that the incorporation of spectral measurements to simulate thin-film modules improves significantly both the fitting of the predicted I–V curve to the measured one and the peak power point estimation

90

Weekly-discharge estimation for Tang-Karzin’s Station, using multilayer Perceptron (MLP network optimized by Artificial Bee Colony (ABC Algorithm  

Directory of Open Access Journals (Sweden)

Full Text Available In order to perceive of rainfall- runoff process, essential prediction for water surface source management has special importance. Thereby in this paper, Tang-e Karzin hydrometric station which is located in sub-domain of salman-farsi dam had been considered. By utilizing of weekly statistical discharge information related to past 36 years, multilayer perceptron neural network model was used to predict the average weekly discharge of Tang-e Karzin station through the discharge information of its two upside stations. In order to optimize the weights and biases of the MLP network, we tried to use Artificial Bee Colony (ABC algorithm within training phase of the ANN network. The results indicated that by changing of different parameters of hidden layer of perceptron model, ABC can well optimize ANN’s weights and biases. Among five activation function Log-sigmoid was performed better than others with 9 neurons in hidden layer

Saleh Salimi

2013-10-01

91

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

Directory of Open Access Journals (Sweden)

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

92

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

Science.gov (United States)

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.

Piotrowski, A.; Wallis, S. G.; Napiórkowski, J. J.; Rowi?ski, P. M.

2007-12-01

93

Modeling of gamma ray energy-absorption buildup factors for thermoluminescent dosimetric materials using multilayer perceptron neural network : A comparative study  

DEFF Research Database (Denmark)

In this work, multilayered perceptron neural networks (MLPNNs) were presented for the computation of the gamma-ray energy absorption buildup factors (BA) of seven thermoluminescent dosimetric (TLD) materials [LiF, BeO, Na2B4O7, CaSO4, Li2B4O7, KMgF3, Ca3(PO4)2] in the energy region 0.015–15MeV, and for penetration depths up to 10 mfp (mean-free-path). The MLPNNs have been trained by a Levenberg–Marquardt learning algorithm. The developed model is in 99% agreement with the ANSI/ANS-6.4.3 standard data set. Furthermore, the model is fast and does not require tremendous computational efforts. The estimated BA data for TLD materials have been given with penetration depth and incident photon energy as comparative to the results of the interpolation method using the Geometrical Progression (G-P) fitting formula.

Kucuk, Nil; Manohara, S.R.

2013-01-01

94

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

Directory of Open Access Journals (Sweden)

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

95

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.

2006-09-01

96

Modeling of gamma ray energy-absorption buildup factors for thermoluminescent dosimetric materials using multilayer perceptron neural network: A comparative study  

International Nuclear Information System (INIS)

In this work, multilayered perceptron neural networks (MLPNNs) were presented for the computation of the gamma-ray energy absorption buildup factors (BA) of seven thermoluminescent dosimetric (TLD) materials [LiF, BeO, Na2B4O7, CaSO4, Li2B4O7, KMgF3, Ca3(PO4)2] in the energy region 0.015–15 MeV, and for penetration depths up to 10 mfp (mean-free-path). The MLPNNs have been trained by a Levenberg–Marquardt learning algorithm. The developed model is in 99% agreement with the ANSI/ANS-6.4.3 standard data set. Furthermore, the model is fast and does not require tremendous computational efforts. The estimated BA data for TLD materials have been given with penetration depth and incident photon energy as comparative to the results of the interpolation method using the Geometrical Progression (G-P) fitting formula. - Highlights: ? Gamma-ray energy absorption buildup factors estimation in TLD materials. ? The ANN approach can be alternative to G-P fitting method for BA calculations. ? The applied model is not time-consuming and easily predicted

97

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

2014-12-01

98

Using multilayer perceptron computation to discover ideal insect olfactory receptor combinations in the mosquito and fruit fly for an efficient electronic nose.  

Science.gov (United States)

The model organism, Drosophila melanogaster, and the mosquito Anopheles gambiae use 60 and 79 odorant receptors, respectively, to sense their olfactory world. However, a commercial "electronic nose" in the form of an insect olfactory biosensor demands very low numbers of receptors at its front end of detection due to the difficulties of receptor/sensor integration and functionalization. In this letter, we demonstrate how computation via artificial neural networks (ANNs), in the form of multilayer perceptrons (MLPs), can be successfully incorporated as the signal processing back end of the biosensor to drastically reduce the number of receptors to three while still retaining 100% performance of odorant detection to that of a full complement of receptors. In addition, we provide a detailed performance comparison between D. melanogaster and A. gambiae odorant receptors and demonstrate that A. gambiae receptors provide superior olfaction detection performance over D. melanogaster for very low receptor numbers. The results from this study present the possibility of using the computation of MLPs to discover ideal biological olfactory receptors for an olfactory biosensor device to provide maximum classification performance of unknown odorants. PMID:25380337

Bachtiar, Luqman R; Unsworth, Charles P; Newcomb, Richard D

2015-01-01

99

Temperature profile retrieval in axisymmetric combustion plumes using multilayer perceptron modeling and spectral feature selection in the infrared CO2 emission band.  

Science.gov (United States)

In this work, a methodology based on the combined use of a multilayer perceptron model fed using selected spectral information is presented to invert the radiative transfer equation (RTE) and to recover the spatial temperature profile inside an axisymmetric flame. The spectral information is provided by the measurement of the infrared CO2 emission band in the 3-5 ?m spectral region. A guided spectral feature selection was carried out using a joint criterion of principal component analysis and a priori physical knowledge of the radiative problem. After applying this guided feature selection, a subset of 17 wavenumbers was selected. The proposed methodology was applied over synthetic scenarios. Also, an experimental validation was carried out by measuring the spectral emission of the exhaust hot gas plume in a microjet engine with a Fourier transform-based spectroradiometer. Temperatures retrieved using the proposed methodology were compared with classical thermocouple measurements, showing a good agreement between them. Results obtained using the proposed methodology are very promising and can encourage the use of sensor systems based on the spectral measurement of the CO2 emission band in the 3-5 ?m spectral window to monitor combustion processes in a nonintrusive way. PMID:25061791

García-Cuesta, Esteban; de Castro, Antonio J; Galván, Inés M; López, Fernando

2014-01-01

100

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

Directory of Open Access Journals (Sweden)

Full Text Available 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.

Mokhtar Attari

2013-03-01

101

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

102

Evaluation of an integrated modelling system containing a multi-layer perceptron model and the numerical weather prediction model HIRLAM for the forecasting of urban airborne pollutant concentrations  

Science.gov (United States)

In this paper, a multi-layer perceptron (MLP) model and the Finnish variant of the numerical weather prediction model HIRLAM (High Resolution Limited Area Model) were integrated and evaluated for the forecasting in time of urban pollutant concentrations. The forecasts of the combination of the MLP and HIRLAM models are compared with the corresponding forecasts of the MLP models that utilise meteorologically pre-processed input data. A novel input selection method based on the use of a multi-objective genetic algorithm (MOGA) is applied in conjunction with the sensitivity analysis to reduce the excessively large number of potential meteorological input variables; its use improves the performance of the MLP model. The computed air quality forecasts contain the sequential hourly time series of the concentrations of nitrogen dioxide (NO 2) and fine particulate matter (PM 2.5) from May 2000 to April 2003; the corresponding concentrations have also been measured at two urban air quality stations in Helsinki. The results obtained with the MLP models that use HIRLAM forecasts show fairly good overall agreement for both pollutants. The model performance is substantially better, when the HIRLAM forecasts are used, compared with those obtained both using either HIRLAM analysis data or meteorological pre-processor, for both pollutants. The performance of the currently widely used statistical forecasting methods (such as those based on neural networks) could therefore be significantly improved by using the forecasts of NWP models, instead of the conventionally utilised directly measured or meteorological pre-processed input data. However, the performance of all operational models considered is relatively worse in the course of air pollution episodes.

Niska, Harri; Rantamäki, Minna; Hiltunen, Teri; Karppinen, Ari; Kukkonen, Jaakko; Ruuskanen, Juhani; Kolehmainen, Mikko

103

Optimization of metformin HCl 500 mg sustained release matrix tablets using Artificial Neural Network (ANN) based on Multilayer Perceptrons (MLP) model.  

Science.gov (United States)

The aim of the present study was to apply the simultaneous optimization method incorporating Artificial Neural Network (ANN) using Multi-layer Perceptron (MLP) model to the development of a metformin HCl 500 mg sustained release matrix tablets with an optimized in vitro release profile. The amounts of HPMC K15M and PVP K30 at three levels (-1, 0, +1) for each were selected as casual factors. In vitro dissolution time profiles at four different sampling times (1 h, 2 h, 4 h and 8 h) were chosen as output variables. 13 kinds of metformin matrix tablets were prepared according to a 2(3) factorial design (central composite) with five extra center points, and their dissolution tests were performed. Commercially available STATISTICA Neural Network software (Stat Soft, Inc., Tulsa, OK, U.S.A.) was used throughout the study. The training process of MLP was completed until a satisfactory value of root square mean (RSM) for the test data was obtained using feed forward back propagation method. The root mean square value for the trained network was 0.000097, which indicated that the optimal MLP model was reached. The optimal tablet formulation based on some predetermined release criteria predicted by MLP was 336 mg of HPMC K15M and 130 mg of PVP K30. Calculated difference (f(1) 2.19) and similarity (f(2) 89.79) factors indicated that there was no difference between predicted and experimentally observed drug release profiles for the optimal formulation. This work illustrates the potential for an artificial neural network with MLP, to assist in development of sustained release dosage forms. PMID:18239298

Mandal, Uttam; Gowda, Veeran; Ghosh, Animesh; Bose, Anirbandeep; Bhaumik, Uttam; Chatterjee, Bappaditya; Pal, Tapan Kumar

2008-02-01

104

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

Scientific Electronic Library Online (English)

Full Text Available SciELO Brazil | Language: English Abstract in portuguese 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. Abstract in english 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 parall [...] elism 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.

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

2011-12-01

105

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

106

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  

Scientific Electronic Library Online (English)

Full Text Available SciELO Costa Rica | Language: Spanish Abstract in spanish 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 p [...] resentaban 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. Abstract in english 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 behavi [...] our, 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; Orlando José, Ávila Blas.

2013-01-01

107

Analysis of Multi layer Perceptron Network  

OpenAIRE

In this paper, we introduce the multilayer Perceptron (feedforward) neural network (MLPs) and used it for a function approximation. For the training of MLP, we have used back propagation algorithm principle. The main purpose of this paper lies in changing the number of hidden layers of MLP for achieving minimum value of mean square error.

Jatinder Kaur; Dr. Mandeep Singh; Pardeep Singh Bains; Gagandeep Singh

2013-01-01

108

Analysis of Multi layer Perceptron Network  

Directory of Open Access Journals (Sweden)

Full Text Available In this paper, we introduce the multilayer Perceptron (feedforward neural network (MLPs and used it for a function approximation. For the training of MLP, we have used back propagation algorithm principle. The main purpose of this paper lies in changing the number of hidden layers of MLP for achieving minimum value of mean square error.

Jatinder Kaur

2013-06-01

109

The Attentive Perceptron  

OpenAIRE

We propose a focus of attention mechanism to speed up the Perceptron algorithm. Focus of attention speeds up the Perceptron algorithm by lowering the number of features evaluated throughout training and prediction. Whereas the traditional Perceptron evaluates all the features of each example, the Attentive Perceptron evaluates less features for easy to classify examples, thereby achieving significant speedups and small losses in prediction accuracy. Focus of attention allows...

Pelossof, Raphael; Ying, Zhiliang

2010-01-01

110

The Attentive Perceptron  

CERN Document Server

We propose a focus of attention mechanism to speed up the Perceptron algorithm. Focus of attention speeds up the Perceptron algorithm by lowering the number of features evaluated throughout training and prediction. Whereas the traditional Perceptron evaluates all the features of each example, the Attentive Perceptron evaluates less features for easy to classify examples, thereby achieving significant speedups and small losses in prediction accuracy. Focus of attention allows the Attentive Perceptron to stop the evaluation of features at any interim point and filter the example. This creates an attentive filter which concentrates computation at examples that are hard to classify, and quickly filters examples that are easy to classify.

Pelossof, Raphael

2010-01-01

111

Introduction to Perceptron Networks  

DEFF Research Database (Denmark)

When it is time-consuming or expensive to model a plant using the basic laws of physics, a neural network approach can be an alternative. From a control engineer's viewpoint a two-layer perceptron network is sufficient. It is indicated how to model a dynamic plant using a perceptron network.

Jantzen, Jan

1998-01-01

112

Perceptron Mistake Bounds  

OpenAIRE

We present a brief survey of existing mistake bounds and introduce novel bounds for the Perceptron or the kernel Perceptron algorithm. Our novel bounds generalize beyond standard margin-loss type bounds, allow for any convex and Lipschitz loss function, and admit a very simple proof.

Mohri, Mehryar; Rostamizadeh, Afshin

2013-01-01

113

Generalization ability of a perceptron with non-monotonic transfer function  

OpenAIRE

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...

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

1997-01-01

114

Optimal coloured perceptrons  

OpenAIRE

Ashkin-Teller type perceptron models are introduced. Their maximal capacity per number of couplings is calculated within a first-step replica-symmetry-breaking Gardner approach. The results are compared with extensive numerical simulations using several algorithms.

Bolle, D.; Kozlowski, P.

2000-01-01

115

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 %.

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

2013-12-30

116

Negative spherical perceptron  

OpenAIRE

In this paper we consider the classical spherical perceptron problem. This problem and its variants have been studied in a great detail in a broad literature ranging from statistical physics and neural networks to computer science and pure geometry. Among the most well known results are those created using the machinery of statistical physics in \\cite{Gar88}. They typically relate to various features ranging from the storage capacity to typical overlap of the optimal configu...

Stojnic, Mihailo

2013-01-01

117

The Perceptron with Dynamic Margin  

OpenAIRE

The classical perceptron rule provides a varying upper bound on the maximum margin, namely the length of the current weight vector divided by the total number of updates up to that time. Requiring that the perceptron updates its internal state whenever the normalized margin of a pattern is found not to exceed a certain fraction of this dynamic upper bound we construct a new approximate maximum margin classifier called the perceptron with dynamic margin (PDM). We demonstrate ...

Panagiotakopoulos, Constantinos; Tsampouka, Petroula

2011-01-01

118

Fault characterization of a multilayered perceptron network  

Science.gov (United States)

The results of a set of simulation experiments conducted to quantify the effects of faults in a classification network implemented as a three-layered perception model are reported. The percentage of vectors misclassified by the classification network, the time taken for the network to stabilize, and the output values are measured. The results show that both transient and permanent faults have a significant impact on the performance of the network. Transient faults are also found to cause the network to be increasingly unstable as the duration of a transient is increased. The average percentage of the vectors misclassified is about 25 percent; after relearning, this is reduced to 10 percent. The impact of link faults is relatively insignificant in comparison with node faults (1 percent versus 19 percent misclassified after relearning). A study of the impact of hardware redundancy shows a linear increase in misclassifications with increasing hardware size.

Tan, Chang H.; Iyer, Ravishankar K.

1990-01-01

119

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

120

The Perceptron with Dynamic Margin  

CERN Document Server

The classical perceptron rule provides a varying upper bound on the maximum margin, namely the length of the current weight vector divided by the total number of updates up to that time. Requiring that the perceptron updates its internal state whenever the normalized margin of a pattern is found not to exceed a certain fraction of this dynamic upper bound we construct a new approximate maximum margin classifier called the perceptron with dynamic margin (PDM). We demonstrate that PDM converges in a finite number of steps and derive an upper bound on them. We also compare experimentally PDM with other perceptron-like algorithms and support vector machines on hard margin tasks involving linear kernels which are equivalent to 2-norm soft margin.

Panagiotakopoulos, Constantinos

2011-01-01

121

Finite Size Scaling of Perceptron  

OpenAIRE

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, Elka; Tonchev, N.

2000-01-01

122

Limit cycles of a perceptron  

OpenAIRE

An artificial neural network can be used to generate a series of numbers. A boolean perceptron generates bit sequences with a periodic structure. The corresponding spectrum of cycle lengths is investigated analytically and numerically; it has similarities with properties of rational numbers.

Schroeder, M.; Kinzel, W.

1997-01-01

123

Polyhedrons and Perceptrons Are Functionally Equivalent  

OpenAIRE

Mathematical definitions of polyhedrons and perceptron networks are discussed. The formalization of polyhedrons is done in a rather traditional way. For networks, previously proposed systems are developed. Perceptron networks in disjunctive normal form (DNF) and conjunctive normal forms (CNF) are introduced. The main theme is that single output perceptron neural networks and characteristic functions of polyhedrons are one and the same class of functions. A rigorous formulati...

Crespin, Daniel

2013-01-01

124

The Margitron: A Generalised Perceptron with Margin  

OpenAIRE

We identify the classical Perceptron algorithm with margin as a member of a broader family of large margin classifiers which we collectively call the Margitron. The Margitron, (despite its) sharing the same update rule with the Perceptron, is shown in an incremental setting to converge in a finite number of updates to solutions possessing any desirable fraction of the maximum margin. Experiments comparing the Margitron with decomposition SVMs on tasks involving linear kernel...

Panagiotakopoulos, Constantinos; Tsampouka, Petroula

2008-01-01

125

Robust chaos generation by a perceptron  

OpenAIRE

The properties of time series generated by a perceptron with monotonic and non-monotonic transfer function, where the next input vector is determined from past output values, are examined. Analysis of the parameter space reveals the following main finding: a perceptron with a monotonic function can produce fragile chaos only whereas a non-monotonic function can generate robust chaos as well. For non-monotonic functions, the dimension of the attractor can be controlled monoto...

Priel, A.; Kanter, I.

2000-01-01

126

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

127

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

128

Classification of Parking Spots Using Multilayer Perceptron Networks  

Directory of Open Access Journals (Sweden)

Full Text Available This project intends to develop a prototype for the identification of free spots in open air parking area where there is a good aerial view without obstacles, allowing for the identification of occupied and free spots. We used image processing techniques and pattern recognition using Artificial Neural Networks (ANN. In order to help implement the prototype, we used Matlab. In order to simulate the parking area, we created a model so that we could acquire the images using a webcam, process them, train the neural network, classify the spots and finally, show the results. The results show that it is viable to apply pattern recognition through image capture to classify parking spots

FALCAO, H. S.

2013-12-01

129

Classification of fuels using multilayer perceptron neural networks  

International Nuclear Information System (INIS)

Electrical impedance data obtained with an array of conducting polymer chemical sensors was used by a neural network (ANN) to classify fuel adulteration. Real samples were classified with accuracy greater than 90% in two groups: approved and adulterated.

130

Multilayer Perceptron with Functional Inputs: an Inverse Regression Approach  

OpenAIRE

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

131

FPGA Implementation of Multilayer Perceptron for Modeling of Photovoltaic panel  

International Nuclear Information System (INIS)

The Number of electronic applications using artificial neural network-based solutions has increased considerably in the last few years. However, their applications in photovoltaic systems are very limited. This paper introduces the preliminary result of the modeling and simulation of photovoltaic panel based on neural network and VHDL-language. In fact, an experimental database of meteorological data (irradiation, temperature) and output electrical generation signals of the PV-panel (current and voltage) has been used in this study. The inputs of the ANN-PV-panel are the daily total irradiation and mean average temperature while the outputs are the current and voltage generated from the panel. Firstly, a dataset of 4x364 have been used for training the network. Subsequently, the neural network (MLP) corresponding to PV-panel is simulated using VHDL language based on the saved weights and bias of the network. Simulation results of the trained MLP-PV panel based on Matlab and VHDL are presented. The proposed PV-panel model based ANN and VHDL permit to evaluate the performance PV-panel using only the environmental factors and involves less computational efforts, and it can be used for predicting the output electrical energy from the PV-panel

132

Perceptron beyond the limit of capacity  

OpenAIRE

An input-output map in which the patterns are divided into classes is considered for the perceptron. The statistical mechanical analysis with a finite number of classes turns out to give the same results as the case of only one class of patterns ; the limit of capacity and the relevant order parameters are calculated in a mean field approach. The analysis is then extended to the Derrida Gardner canonical ensemble in which the perceptron can be studied beyond the limit of capacity. We complete...

Del Giudice, P.; Franz, S.; Virasoro, M. A.

1989-01-01

133

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.

134

Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition.  

Science.gov (United States)

This paper proposes noisy speech recognition using hierarchical singleton-type recurrent neural fuzzy networks (HSRNFNs). The proposed HSRNFN is a hierarchical connection of two singleton-type recurrent neural fuzzy networks (SRNFNs), where one is used for noise filtering and the other for recognition. The SRNFN is constructed by recurrent fuzzy if-then rules with fuzzy singletons in the consequences, and their recurrent properties make them suitable for processing speech patterns with temporal characteristics. In n words recognition, n SRNFNs are created for modeling n words, where each SRNFN receives the current frame feature and predicts the next one of its modeling word. The prediction error of each SRNFN is used as recognition criterion. In filtering, one SRNFN is created, and each SRNFN recognizer is connected to the same SRNFN filter, which filters noisy speech patterns in the feature domain before feeding them to the SRNFN recognizer. Experiments with Mandarin word recognition under different types of noise are performed. Other recognizers, including multilayer perceptron (MLP), time-delay neural networks (TDNNs), and hidden Markov models (HMMs), are also tested and compared. These experiments and comparisons demonstrate good results with HSRNFN for noisy speech recognition tasks. PMID:17526348

Juang, Chia-Feng; Chiou, Chyi-Tian; Lai, Chun-Lung

2007-05-01

135

A diluted version of the perceptron model  

OpenAIRE

This note is concerned with a diluted version of the perceptron model. We establish a replica symmetric formula at high temperature, which is achieved by studying the asymptotic behavior of a given spin magnetization. Our main task will be to identify the order parameter of the system.

Marquez-carreras, David; Rovira, Carles; Tindel, Samy

2006-01-01

136

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)

137

Storage capacity of a Potts-perceptron  

OpenAIRE

We consider the properties of “Potts” neural networks where each neuron can be in Q different states. For a “Potts-perceptron” with N Q-states input neurons and one Q' states output neutron, we compute the maximal storage capacity for unbiased patterns. In the large N limit the maximal number of patterns that can be stored is found to be proportional to N(Q-1)f(Q'), where f(Q') is of order 1.

Nadal, Jean-pierre; Rau, Albrecht

1991-01-01

138

Multifractal analysis of perceptron learning with errors  

OpenAIRE

Random input patterns induce a partition of the coupling space of a perceptron into cells labeled by their output sequences. Learning some data with a maximal error rate leads to clusters of neighboring cells. By analyzing the internal structure of these clusters with the formalism of multifractals, we can handle different storage and generalization tasks for lazy students and absent-minded teachers within one unified approach. The results also allow some conclusions on the ...

Weigt, M.

1997-01-01

139

Storage of correlated patterns in a perceptron  

OpenAIRE

We calculate the storage capacity of a perceptron for correlated gaussian patterns. We find that the storage capacity $\\alpha_c$ can be less than 2 if similar patterns are mapped onto different outputs and vice versa. As long as the patterns are in general position we obtain, in contrast to previous works, that $\\alpha_c \\geq 1$ in agreement with Cover's theorem. Numerical simulations confirm the results.

Lopez, B.; Schroeder, M.; Opper, M.

1995-01-01

140

Landscape statistics of the binary perceptron  

OpenAIRE

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

141

Finite size scaling of the bayesian perceptron  

OpenAIRE

We study numerically the properties of the bayesian perceptron through a gradient descent on the optimal cost function. The theoretical distribution of stabilities is deduced. It predicts that the optimal generalizer lies close to the boundary of the space of (error-free) solutions. The numerical simulations are in good agreement with the theoretical distribution. The extrapolation of the generalization error to infinite input space size agrees with the theoretical results. ...

Buhot, A.; Moreno, J. -m Torres; Gordon, M. B.

1997-01-01

142

On-line learning and generalisation in coupled perceptrons  

OpenAIRE

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 vari...

Bolle, D.; Kozlowski, P.

2001-01-01

143

On-line learning through simple perceptron with a margin  

OpenAIRE

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 compu...

Hara, Kazuyuki; Okada, Masato

2003-01-01

144

Stochastic resonance in an intracellular genetic perceptron.  

Science.gov (United States)

Intracellular genetic networks are more intelligent than was first assumed due to their ability to learn. One of the manifestations of this intelligence is the ability to learn associations of two stimuli within gene-regulating circuitry: Hebbian-type learning within the cellular life. However, gene expression is an intrinsically noisy process; hence, we investigate the effect of intrinsic and extrinsic noise on this kind of intracellular intelligence. We report a stochastic resonance in an intracellular associative genetic perceptron, a noise-induced phenomenon, which manifests itself in noise-induced increase of response in efficiency after the learning event under the conditions of optimal stochasticity. PMID:24730883

Bates, Russell; Blyuss, Oleg; Zaikin, Alexey

2014-03-01

145

Finite size scaling of the Bayesian perceptron  

Science.gov (United States)

We study numerically the properties of the Bayesian perceptron through a gradient descent on the optimal cost function. The theoretical distribution of stabilities is deduced. It predicts that the optimal generalizer lies close to the boundary of the space of (error-free) solutions. The numerical simulations are in good agreement with the theoretical distribution. The extrapolation of the generalization error to infinite input space size agrees with the theoretical results. Finite size corrections are negative and exhibit two different scaling regimes, depending on the training set size. The variance of the generalization error vanishes for N-->? confirming the property of self-averaging.

Buhot, Arnaud; Torres Moreno, Juan-Manuel; Gordon, Mirta B.

1997-06-01

146

Finite size scaling of the bayesian perceptron  

CERN Document Server

We study numerically the properties of the bayesian perceptron through a gradient descent on the optimal cost function. The theoretical distribution of stabilities is deduced. It predicts that the optimal generalizer lies close to the boundary of the space of (error-free) solutions. The numerical simulations are in good agreement with the theoretical distribution. The extrapolation of the generalization error to infinite input space size agrees with the theoretical results. Finite size corrections are negative and exhibit two different scaling regimes, depending on the training set size. The variance of the generalization error vanishes for $N \\rightarrow \\infty$ confirming the property of self-averaging.

Buhot, A; Gordon, M B

1997-01-01

147

Stochastic resonance in an intracellular genetic perceptron  

Science.gov (United States)

Intracellular genetic networks are more intelligent than was first assumed due to their ability to learn. One of the manifestations of this intelligence is the ability to learn associations of two stimuli within gene-regulating circuitry: Hebbian-type learning within the cellular life. However, gene expression is an intrinsically noisy process; hence, we investigate the effect of intrinsic and extrinsic noise on this kind of intracellular intelligence. We report a stochastic resonance in an intracellular associative genetic perceptron, a noise-induced phenomenon, which manifests itself in noise-induced increase of response in efficiency after the learning event under the conditions of optimal stochasticity.

Bates, Russell; Blyuss, Oleg; Zaikin, Alexey

2014-03-01

148

Correlated patterns in non-monotonic graded-response perceptrons  

CERN Document Server

The optimal capacity of graded-response perceptrons storing biased and spatially correlated patterns with non-monotonic input-output relations is studied. It is shown that only the structure of the output patterns is important for the overall performance of the perceptrons.

Bollé, D

1999-01-01

149

Optimal Capacity of the Blume-Emery-Griffiths perceptron  

OpenAIRE

A Blume-Emery-Griffiths perceptron model is introduced and its optimal capacity is calculated within the replica-symmetric Gardner approach, as a function of the pattern activity and the imbedding stability parameter. The stability of the replica-symmetric approximation is studied via the analogue of the Almeida-Thouless line. A comparison is made with other three-state perceptrons.

Bolle, D.; Castillo, I. Perez; Shim, G. M.

2002-01-01

150

Investigation of nonlinear pupil dynamics by recurrence quantification analysis.  

Science.gov (United States)

Pupil is controlled by the autonomous nervous system (ANS). It shows complex movements and changes of size even in conditions of constant stimulation. The possibility of extracting information on ANS by processing data recorded during a short experiment using a low cost system for pupil investigation is studied. Moreover, the significance of nonlinear information contained in the pupillogram is investigated. We examined 13 healthy subjects in different stationary conditions, considering habitual dental occlusion (HDO) as a weak stimulation of the ANS with respect to the maintenance of the rest position (RP) of the jaw. Images of pupil captured by infrared cameras were processed to estimate position and size on each frame. From such time series, we extracted linear indexes (e.g., average size, average displacement, and spectral parameters) and nonlinear information using recurrence quantification analysis (RQA). Data were classified using multilayer perceptrons and support vector machines trained using different sets of input indexes: the best performance in classification was obtained including nonlinear indexes in the input features. These results indicate that RQA nonlinear indexes provide additional information on pupil dynamics with respect to linear descriptors, allowing the discrimination of even a slight stimulation of the ANS. Their use in the investigation of pathology is suggested. PMID:24187665

Mesin, L; Monaco, A; Cattaneo, R

2013-01-01

151

Experimental characterization of the perceptron laser rangefinder  

Science.gov (United States)

In this report, we characterize experimentally a scanning laser rangefinder that employs active sensing to acquire three-dimensional images. We present experimental techniques applicable to a wide variety of laser scanners, and document the results of applying them to a device manufactured by Perceptron. Nominally, the sensor acquires data over a 60 deg x 60 deg field of view in 256 x 256 pixel images at 2 Hz. It digitizes both range and reflectance pixels to 12 bits, providing a maximum range of 40 m and a depth resolution of 1 cm. We present methods and results from experiments to measure geometric parameters including the field of view, angular scanning increments, and minimum sensing distance. We characterize qualitatively problems caused by implementation flaws, including internal reflections and range drift over time, and problems caused by inherent limitations of the rangefinding technology, including sensitivity to ambient light and surface material. We characterize statistically the precision and accuracy of the range measurements. We conclude that the performance of the Perceptron scanner does not compare favorably with the nominal performance, that scanner modifications are required, and that further experimentation must be conducted.

Kweon, I. S.; Hoffman, Regis; Krotkov, Eric

1991-01-01

152

Stability of the replica symmetric solution in diluted perceptron learning  

OpenAIRE

We study the role played by the dilution in the average behavior of a perceptron model with continuous coupling with the replica method. We analyze the stability of the replica symmetric solution as a function of the dilution field for the generalization and memorization problems. Thanks to a Gardner like stability analysis we show that at any fixed ratio $\\alpha$ between the number of patterns M and the dimension N of the perceptron ($\\alpha=M/N$), there exists a critical d...

Lage-castellanos, Alejandro; Pagnani, Andrea; Angulo, Gretel Quintero

2012-01-01

153

The Projectron: a Bounded Kernel-Based Perceptron  

OpenAIRE

We present a discriminative online algorithm with a bounded memory growth, which is based on the kernel-based Perceptron. Generally, the required memory of the kernel-based Perceptron for storing the online hypothesis is not bounded. Previous work has been focused on discarding part of the instances in order to keep the memory bounded. In the proposed algorithm the instances are not discarded, but projected onto the space spanned by the previous online hypothesis. We derive a relative mistake...

Orabona, Francesco; Keshet, Joseph; Caputo, Barbara

2008-01-01

154

Generalization learning in a perceptron with binary synapses  

OpenAIRE

We consider the generalization problem for a perceptron with binary synapses, implementing the Stochastic Belief-Propagation-Inspired (SBPI) learning algorithm which we proposed earlier, and perform a mean-field calculation to obtain a differential equation which describes the behaviour of the device in the limit of a large number of synapses N. We show that the solving time of SBPI is of order N*sqrt(log(N)), while the similar, well-known clipped perceptron (CP) algorithm d...

Baldassi, Carlo

2012-01-01

155

Ensemble learning of linear perceptron; Online learning theory  

OpenAIRE

Within the framework of on-line learning, we study the generalization error of an ensemble learning machine learning from a linear teacher perceptron. The generalization error achieved by an ensemble of linear perceptrons having homogeneous or inhomogeneous initial weight vectors is precisely calculated at the thermodynamic limit of a large number of input elements and shows rich behavior. Our main findings are as follows. For learning with homogeneous initial weight vectors...

Hara, Kazuyuki; Okada, Masato

2004-01-01

156

An Efficient Rescaled Perceptron Algorithm for Conic Systems  

OpenAIRE

The classical perceptron algorithm is an elementary row-action/relaxation algorithm for solving a homogeneous linear inequality system Ax > 0. A natural condition measure associated with this algorithm is the Euclidean width {tau} of the cone of feasible solutions, and the iteration complexity of the perceptron algorithm is bounded by 1/{tau}2 [see Rosenblatt, F. 1962. Principles of Neurodynamics. Spartan Books, Washington, DC]. Dunagan and Vempala [Dunagan, J., S. Vempala. 2007. A simple pol...

Vempala, Santosh; Belloni, Alexandre; Freund, Robert Michael

2009-01-01

157

Training a perceptron in a discrete weight space  

OpenAIRE

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

158

A Simple Perceptron that Learns Non-Monotonic Rules  

OpenAIRE

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 o...

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

1997-01-01

159

A perceptron network theorem prover for the propositional calculus  

OpenAIRE

In this paper a short introduction to neural networks and a design for a perceptron network theorem prover for the propositional calculus are presented. The theorem prover is a representation of a variant of the semantic tableau method, called the parallel tableau method, by a network of perceptrons. The parallel tableau method is designed to enable determination of the counter-examples of a formula (if any) concurrently. It is proven that the parallel method is complete, and t...

Drossaers, M. F. J.

1989-01-01

160

Entropy landscape of solutions in the binary perceptron problem  

OpenAIRE

The statistical picture of the solution space for a binary perceptron is studied. The binary perceptron learns a random classification of input random patterns by a set of binary synaptic weights. The learning of this network is difficult especially when the pattern (constraint) density is close to the capacity, which is supposed to be intimately related to the structure of the solution space. The geometrical organization is elucidated by the entropy landscape from a referen...

Huang, Haiping; Wong, K. Y. Michael; Kabashima, Yoshiyuki

2013-01-01

161

Convergence Analysis of Adaptive Recurrent Neural Network  

Directory of Open Access Journals (Sweden)

Full Text Available This paper presents analysis of a modified Feed Forward Multilayer Perceptron (FMP by inserting an ARMA (Auto Regressive Moving Average model at each neuron (processor node with the Backp ropagation learning algorithm. The stability analysis is presented to establish the convergence theory of the Back propagation algorithm based on the Lyapunov function. Furthermore, the analysis extends the Back propagation learning rule by introducing the adaptive learning factors. A range of possible learning factors is derived from the stability analysis. Performance of such network learning with adaptive learning factors is presented and demonstrates that the adaptive learning factor enhance the performance of training while avoiding oscillation phenomenon.

Hong Li

2014-06-01

162

PENGENALAN CITRA OBJEK SEDERHANA DENGAN JARINGAN SARAF TIRUAN METODE PERCEPTRON  

Directory of Open Access Journals (Sweden)

Full Text Available Konsep bangunan dan benda-benda yang ada di sekeliling didasarkan dan dipengaruhi oleh konsep objek sederhana atau sering disebut geometri ruang tiga dimensi, yaitu memiliki panjang, lebar dan tinggi. Namun, dalam rancangan dan penggambarannya menggunakan gambar berdimensi dua saja. Sehingga pada konsep penggambarannya membutuhkan visualisasi yang lebih detail. Diharapkan jaringan syaraf tiruan metode perceptron dapat mengenali gambar yang sesuai dengan bentuk aslinya. Pada penelitian ini metode jaringan saraf yang digunakan adalah metode perceptron untuk mengenali citra objek sederhana. Objek yang digunakan yaitu bentuk bangun ruang yang terdiri dari kubus, kerucut, tabung, prisma, dan limas dengan berbagai jenisnya. Perangkat lunak yang digunakan pada pembuatan aplikasi ini adalah Borland Delphi 7.0. Dari hasil pelatihan dan pengujian jaringan saraf tiruan perceptron dapat mengenali pola dengan rata-rata 75,25 % dengan prosentase terendah yaitu 50,75 % dan prosentase tertinggi yaitu 92,65 %. Dengan prosentase yang cukup baik tersebut, sistem dapat digunakan untuk mengenali citra objek sederhana.

Ardi Pujiyanta

2012-05-01

163

PENGENALAN CITRA OBJEK SEDERHANA DENGAN JARINGAN SARAF TIRUAN METODE PERCEPTRON  

OpenAIRE

Konsep bangunan dan benda-benda yang ada di sekeliling didasarkan dan dipengaruhi oleh konsep objek sederhana atau sering disebut geometri ruang tiga dimensi, yaitu memiliki panjang, lebar dan tinggi. Namun, dalam rancangan dan penggambarannya menggunakan gambar berdimensi dua saja. Sehingga pada konsep penggambarannya membutuhkan visualisasi yang lebih detail. Diharapkan jaringan syaraf tiruan metode perceptron dapat mengenali gambar yang sesuai dengan bentuk aslinya. ...

Ardi Pujiyanta

2012-01-01

164

Training a perceptron by a bit sequence: Storage capacity  

OpenAIRE

A perceptron is trained by a random bit sequence. In comparison to the corresponding classification problem, the storage capacity decreases to alpha_c=1.70\\pm 0.02 due to correlations between input and output bits. The numerical results are supported by a signal to noise analysis of Hebbian weights.

Schroeder, M.; Kinzel, W.; Kanter, I.

1996-01-01

165

Breaking a chaotic image encryption algorithm based on perceptron model  

OpenAIRE

Recently, a chaotic image encryption algorithm based on perceptron model was proposed. The present paper analyzes security of the algorithm and finds that the equivalent secret key can be reconstructed with only one pair of known-plaintext/ciphertext, which is supported by both mathematical proof and experiment results. In addition, some other security defects are also reported.

Zhang, Yu; Li, Chengqing; Li, Qin; Zhang, Dan; Shu, Shi

2011-01-01

166

Multilayer Networks  

CERN Document Server

Most real and engineered systems include multiple subsystems and layers of connectivity, and it is important to take such features into account to try to obtain a complete understanding of these systems. It is thus necessary to generalize "traditional" network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. The origins of such efforts occurred several decades ago, but now the study of multilayer networks has become one of the major directions in network science. In this paper, we discuss the history of multilayer networks (and related concepts) and then review the exploding body of work on such networks. To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other, and provide a thorough discussion that compares, contrasts, and translates between related notions such as multila...

Kivelä, Mikko; Barthelemy, Marc; Gleeson, James P; Moreno, Yamir; Porter, Mason A

2013-01-01

167

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.

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

2012-12-01

168

The Role of Weight Shrinking in Large Margin Perceptron Learning  

CERN Document Server

We introduce into the classical perceptron algorithm with margin a mechanism that shrinks the current weight vector as a first step of the update. If the shrinking factor is constant the resulting algorithm may be regarded as a margin-error-driven version of NORMA with constant learning rate. In this case we show that the allowed strength of shrinking depends on the value of the maximum margin. We also consider variable shrinking factors for which there is no such dependence. In both cases we obtain new generalizations of the perceptron with margin able to provably attain in a finite number of steps any desirable approximation of the maximal margin hyperplane. The new approximate maximum margin classifiers appear experimentally to be very competitive in 2-norm soft margin tasks involving linear kernels.

Panagiotakopoulos, Constantinos

2012-01-01

169

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

170

A polynomial training algorithm for calculating perceptrons of optimal stability  

OpenAIRE

Recomi (REpeated COrrelation Matrix Inversion) is a polynomially fast algorithm for searching optimally stable solutions of the perceptron learning problem. For random unbiased and biased patterns it is shown that the algorithm is able to find optimal solutions, if any exist, in at worst O(N^4) floating point operations. Even beyond the critical storage capacity alpha_c the algorithm is able to find locally stable solutions (with negative stability) at the same speed. There ...

Imhoff, Jorg

1994-01-01

171

The Role of Weight Shrinking in Large Margin Perceptron Learning  

OpenAIRE

We introduce into the classical perceptron algorithm with margin a mechanism that shrinks the current weight vector as a first step of the update. If the shrinking factor is constant the resulting algorithm may be regarded as a margin-error-driven version of NORMA with constant learning rate. In this case we show that the allowed strength of shrinking depends on the value of the maximum margin. We also consider variable shrinking factors for which there is no such dependence...

Panagiotakopoulos, Constantinos; Tsampouka, Petroula

2012-01-01

172

A Coherent Perceptron for All-Optical Learning  

CERN Document Server

We present nonlinear photonic circuit models for constructing programmable linear transformations and use these to realize a coherent Perceptron, i.e., an all-optical linear classifier capable of learning the classification boundary iteratively from training data through a coherent feedback rule. Through extensive semi-classical stochastic simulations we demonstrate that the device nearly attains the theoretical error bound for a model classification problem.

Tezak, Nikolas

2015-01-01

173

Perceptron capacity revisited: classification ability for correlated patterns  

OpenAIRE

In this paper, we address the problem of how many randomly labeled patterns can be correctly classified by a single-layer perceptron when the patterns are correlated with each other. In order to solve this problem, two analytical schemes are developed based on the replica method and Thouless-Anderson-Palmer (TAP) approach by utilizing an integral formula concerning random rectangular matrices. The validity and relevance of the developed methodologies are shown for one known ...

Shinzato, Takashi; Kabashima, Yoshiyuki

2007-01-01

174

Asymptotic behavior of the magnetization for the perceptron model  

OpenAIRE

In this paper, we show that, in case of a perceptron model for which the number of outputs is a small proportion of the size of the system, the limiting behavior of the magnetization of a given spin, namely the random variable $\\langle\\si_k\\rangle$, can be identified. In fact, we prove a $L^2$ convergence for a collection of those random variables.

Marquez-carreras, David; Rovira, Carles; Tindel, Samy

2005-01-01

175

Use of the 'Perceptron' algorithm to distinguish translational initiation sites in E. coli.  

OpenAIRE

We have used a "Perceptron" algorithm to find a weighting function which distinguishes E. coli translational initiation sites from all other sites in a library of over 78,000 nucleotides of mRNA sequence. The "Perceptron" examined sequences as linear representations. The "Perceptron" is more successful at finding gene beginnings than our previous searches using "rules" (see previous paper). We note that the weighting function can find translational initiation sites within sequences that were ...

Stormo, G. D.; Schneider, T. D.; Gold, L.; Ehrenfeucht, A.

1982-01-01

176

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

177

An Automated MR Image Segmentation System Using Multi-layer Perceptron Neural Network  

OpenAIRE

Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image artifacts such as noise, low contrast and intensity non-uniformity, there are some classification errors...

Amiri, S.; Movahedi, M. M.; Kazemi, K.; Parsaei, H.

2013-01-01

178

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

OpenAIRE

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

179

Application of artificial neural networks (multilayer perceptron) in reactor safety research  

International Nuclear Information System (INIS)

One of the key areas of reactor safety research are studies of reliable and safe heat removal from the reactor core and the containment, respectively, of light water reactors. Leakage accidents could carry insulating material into the containment or the building sump of the containment and the associated post-decay heat removal systems. This could obstruct systems functions. In the study titled ''Knowledge-based Modeling of Transport Processes in BWR Coolant Flows Carrying Particle Loads after Loss-of-Coolant Accidents,'' a tool is being created for engineering application which allows the deposition and retention of insulating material in the sump of the reactor containment to be estimated. Potential plant conditions in accidents can be assessed in this way. The study serves the purpose of modeling by means of data-based and knowledge-based methods. In this way, the results of experimental investigations (such as differential pressure tests of retention systems) can be used for modeling purposes. (orig.)

180

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

OpenAIRE

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

181

Multilayer Perceptron for Robust Nonlinear Interval Regression Analysis Using Genetic Algorithms  

OpenAIRE

On the basis of fuzzy regression, computational models in intelligence such as neural networks have the capability to be applied to nonlinear interval regression analysis for dealing with uncertain and imprecise data. When training data are not contaminated by outliers, computational models perform well by including almost all given training data in the data interval. Nevertheless, since training data are often corrupted by outliers, robust learning algorithms employed to resist outliers for ...

Yi-Chung Hu

2014-01-01

182

Perceptron capacity revisited: classification ability for correlated patterns  

International Nuclear Information System (INIS)

In this paper, we address the problem of how many randomly labeled patterns can be correctly classified by a single-layer perceptron when the patterns are correlated with each other. In order to solve this problem, two analytical schemes are developed based on the replica method and the Thouless-Anderson-Palmer (TAP) approach by utilizing an integral formula concerning random rectangular matrices. The validity and relevance of the developed methodologies are shown for one known result and two example problems. A message-passing algorithm to perform the TAP scheme is also presented

183

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

184

Recurrent metatarsalgia.  

Science.gov (United States)

Recurrent metatarsalgia has a multifactorial etiology. The analysis of the cause is critical in planning appropriate treatment. Understanding etiology helps understand the mechanism of prevention, which is the best treatment. Recurrent metatarsalgia is often due to poor technique or poor understanding of the underlying problem. In hallux valgus surgery, recurrent metatarsalgia can be a problem of position of the first metatarsal after an inappropriate or poorly done first metatarsal osteotomy or a problem of gastrocnemius tightness not previously recognized. The best treatment is to restore the normal anatomy but that is not always possible, and surgery on affected rays could be the solution. PMID:25129352

Barouk, Pierre

2014-09-01

185

Maximum Daily Discharge Prediction using Multi Layer Perceptron Network  

Science.gov (United States)

Prediction of maximum daily flow is essential for planning of water resources systems. This study presents the use of an Artificial Neural Network (ANN) to maximum daily flow prediction in the Khosrow Shirin watershed, in north-west Fars province in Iran. Precipitation from four meteorological stations was used to develop a Multi Layer Perceptron (MLP) optimized with the Levenberg-Marquardt (MLP_LM) training algorithm and using a tangent sigmoid activation function. Different methods to construct the input vectors were considered during models development. In the first method the precipitation signal is imported separately as input vectors for training. In the second method area-weighted precipitation and related Hydrographs were used in MLP development. In addition to precipitation, in the last model three inputs were used that were base on antecedent flows with one and two days time lag. The performance of each of these models was investigated with the root mean square errors (RMSE) and correlation coefficient (R2). The results show that the second method with weighted precipitation has higher prediction efficiency. R2 and RMSE of training and validation phase for third the model with weighted precipitation were 0.98 and 0.96, respectively Addition of antecedent flow as input vector and use of weighted precipitation provide better results in maximum daily flow prediction. Keywords: Multi Layer Perceptron, Maximum Daily Flow Prediction, Weighted Precipitation, Antecedent flow, Levenberg-Marquardt Algorithm.

Rezaeian Zadeh, M.; Abghari, H.; van de Giesen, N.; Nikian, A.; Niknia, N.

2009-04-01

186

Entropy landscape of solutions in the binary perceptron problem  

Science.gov (United States)

The statistical picture of the solution space for a binary perceptron is studied. The binary perceptron learns a random classification of input random patterns by a set of binary synaptic weights. The learning of this network is difficult especially when the pattern (constraint) density is close to the capacity, which is supposed to be intimately related to the structure of the solution space. The geometrical organization is elucidated by the entropy landscape from a reference configuration and of solution-pairs separated by a given Hamming distance in the solution space. We evaluate the entropy at the annealed level as well as replica symmetric level and the mean field result is confirmed by the numerical simulations on single instances using the proposed message passing algorithms. From the first landscape (a random configuration as a reference), we see clearly how the solution space shrinks as more constraints are added. From the second landscape of solution-pairs, we deduce the coexistence of clustering and freezing in the solution space.

Huang, Haiping; Wong, K. Y. Michael; Kabashima, Yoshiyuki

2013-09-01

187

Entropy landscape of solutions in the binary perceptron problem  

International Nuclear Information System (INIS)

The statistical picture of the solution space for a binary perceptron is studied. The binary perceptron learns a random classification of input random patterns by a set of binary synaptic weights. The learning of this network is difficult especially when the pattern (constraint) density is close to the capacity, which is supposed to be intimately related to the structure of the solution space. The geometrical organization is elucidated by the entropy landscape from a reference configuration and of solution-pairs separated by a given Hamming distance in the solution space. We evaluate the entropy at the annealed level as well as replica symmetric level and the mean field result is confirmed by the numerical simulations on single instances using the proposed message passing algorithms. From the first landscape (a random configuration as a reference), we see clearly how the solution space shrinks as more constraints are added. From the second landscape of solution-pairs, we deduce the coexistence of clustering and freezing in the solution space. (paper)

188

Generalization and capacity of extensively large two-layered perceptrons  

International Nuclear Information System (INIS)

The generalization ability and storage capacity of a treelike two-layered neural network with a number of hidden units scaling as the input dimension is examined. The mapping from the input to the hidden layer is via Boolean functions; the mapping from the hidden layer to the output is done by a perceptron. The analysis is within the replica framework where an order parameter characterizing the overlap between two networks in the combined space of Boolean functions and hidden-to-output couplings is introduced. The maximal capacity of such networks is found to scale linearly with the logarithm of the number of Boolean functions per hidden unit. The generalization process exhibits a first-order phase transition from poor to perfect learning for the case of discrete hidden-to-output couplings. The critical number of examples per input dimension, ?c, at which the transition occurs, again scales linearly with the logarithm of the number of Boolean functions. In the case of continuous hidden-to-output couplings, the generalization error decreases according to the same power law as for the perceptron, with the prefactor being different

189

Handwritten Arabic Numeral Recognition using a Multi Layer Perceptron  

CERN Document Server

Handwritten numeral recognition is in general a benchmark problem of Pattern Recognition and Artificial Intelligence. Compared to the problem of printed numeral recognition, the problem of handwritten numeral recognition is compounded due to variations in shapes and sizes of handwritten characters. Considering all these, the problem of handwritten numeral recognition is addressed under the present work in respect to handwritten Arabic numerals. Arabic is spoken throughout the Arab World and the fifth most popular language in the world slightly before Portuguese and Bengali. For the present work, we have developed a feature set of 88 features is designed to represent samples of handwritten Arabic numerals for this work. It includes 72 shadow and 16 octant features. A Multi Layer Perceptron (MLP) based classifier is used here for recognition handwritten Arabic digits represented with the said feature set. On experimentation with a database of 3000 samples, the technique yields an average recognition rate of 94....

Das, Nibaran; Saha, Sudip; Haque, Syed Sahidul

2010-01-01

190

A Novel Channel Equalizer Using Large Margin Algebraic Perceptron Network  

Directory of Open Access Journals (Sweden)

Full Text Available This paper proposes a novel control scheme for channel equalization for wireless communication system. The proposed scheme considers channel equalization as a classification problem. For efficient solution of the problem, this paper makes use of a neural network working on Algebraic Perceptron (AP algorithm as a classifier. Also, this paper introduces a method of performance improvement by increasing margin of AP equalizers. Novelty of the proposed scheme is evidenced by its simulation results.

Siba P. Panigrahi

2010-08-01

191

Perfect transmission and highly asymmetric light localization in photonic multilayers  

OpenAIRE

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

192

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

193

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. PMID:15903520

Monterola, Christopher; Zapotocky, Martin

2005-03-01

194

Direct Kernel Perceptron (DKP): ultra-fast kernel ELM-based classification with non-iterative closed-form weight calculation.  

Science.gov (United States)

The Direct Kernel Perceptron (DKP) (Fernández-Delgado et al., 2010) is a very simple and fast kernel-based classifier, related to the Support Vector Machine (SVM) and to the Extreme Learning Machine (ELM) (Huang, Wang, & Lan, 2011), whose ?-coefficients are calculated directly, without any iterative training, using an analytical closed-form expression which involves only the training patterns. The DKP, which is inspired by the Direct Parallel Perceptron, (Auer et al., 2008), uses a Gaussian kernel and a linear classifier (perceptron). The weight vector of this classifier in the feature space minimizes an error measure which combines the training error and the hyperplane margin, without any tunable regularization parameter. This weight vector can be translated, using a variable change, to the ?-coefficients, and both are determined without iterative calculations. We calculate solutions using several error functions, achieving the best trade-off between accuracy and efficiency with the linear function. These solutions for the ? coefficients can be considered alternatives to the ELM with a new physical meaning in terms of error and margin: in fact, the linear and quadratic DKP are special cases of the two-class ELM when the regularization parameter C takes the values C=0 and C=?. The linear DKP is extremely efficient and much faster (over a vast collection of 42 benchmark and real-life data sets) than 12 very popular and accurate classifiers including SVM, Multi-Layer Perceptron, Adaboost, Random Forest and Bagging of RPART decision trees, Linear Discriminant Analysis, K-Nearest Neighbors, ELM, Probabilistic Neural Networks, Radial Basis Function neural networks and Generalized ART. Besides, despite its simplicity and extreme efficiency, DKP achieves higher accuracies than 7 out of 12 classifiers, exhibiting small differences with respect to the best ones (SVM, ELM, Adaboost and Random Forest), which are much slower. Thus, the DKP provides an easy and fast way to achieve classification accuracies which are not too far from the best one for a given problem. The C and Matlab code of DKP are freely available. PMID:24287336

Fernández-Delgado, Manuel; Cernadas, Eva; Barro, Senén; Ribeiro, Jorge; Neves, José

2014-02-01

195

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

OpenAIRE

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

1997-01-01

196

Learning by random walks in the weight space of the Ising perceptron  

OpenAIRE

Several variants of a stochastic local search process for constructing the synaptic weights of an Ising perceptron are studied. In this process, binary patterns are sequentially presented to the Ising perceptron and are then learned as the synaptic weight configuration is modified through a chain of single- or double-weight flips within the compatible weight configuration space of the earlier learned patterns. This process is able to reach a storage capacity of $\\alpha \\appr...

Huang, Haiping; Zhou, Haijun

2010-01-01

197

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

198

30 years of adaptive neural networks - Perceptron, Madaline, and backpropagation  

Science.gov (United States)

Fundamental developments in feedforward artificial neural networks from the past thirty years are reviewed. The history, origination, operating characteristics, and basic theory of several supervised neural-network training algorithms (including the perceptron rule, the least-mean-square algorithm, three Madaline rules, and the backpropagation technique) are described. The concept underlying these iterative adaptation algorithms is the minimal disturbance principle, which suggests that during training it is advisable to inject new information into a network in a manner that disturbs stored information to the smallest extent possible. The two principal kinds of online rules that have developed for altering the weights of a network are examined for both single-threshold elements and multielement networks. They are error-correction rules, which alter the weights of a network to correct error in the output response to the present input pattern, and gradient rules, which alter the weights of a network during each pattern presentation by gradient descent with the objective of reducing mean-square error (averaged over all training patterns).

Widrow, Bernard; Lehr, Michael A.

1990-01-01

199

Intelligent control of HVAC systems. Part II: perceptron performance analysis  

Directory of Open Access Journals (Sweden)

Full Text Available This is the second part of a paper on intelligent type control of Heating, Ventilating, and Air-Conditioning (HVAC systems. The whole study proposes a unified approach in the design of intelligent control for such systems, to ensure high energy efficiency and air quality improving. In the first part of the study it is considered as benchmark system a single thermal space HVAC system, for which it is assigned a mathematical model of the controlled system and a mathematical model(algorithm of intelligent control synthesis. The conception of the intelligent control is of switching type, between a simple neural network, a perceptron, which aims to decrease (optimize a cost index,and a fuzzy logic component, having supervisory antisaturating role for neuro-control. Based on numerical simulations, this Part II focuses on the analysis of system operation in the presence only ofthe neural control component. Working of the entire neuro-fuzzy system will be reported in a third part of the study.

Ioan URSU

2013-09-01

200

Perceptron-like computation based on biologically-inspired neurons with heterosynaptic mechanisms  

Science.gov (United States)

Perceptrons are one of the fundamental paradigms in artificial neural networks and a key processing scheme in supervised classification tasks. However, the algorithm they provide is given in terms of unrealistically simple processing units and connections and therefore, its implementation in real neural networks is hard to be fulfilled. In this work, we present a neural circuit able to perform perceptron's computation based on realistic models of neurons and synapses. The model uses Wang-Buzsáki neurons with coupling provided by axodendritic and axoaxonic synapses (heterosynapsis). The main characteristics of the feedforward perceptron operation are conserved, which allows to combine both approaches: whereas the classical artificial system can be used to learn a particular problem, its solution can be directly implemented in this neural circuit. As a result, we propose a biologically-inspired system able to work appropriately in a wide range of frequencies and system parameters, while keeping robust to noise and error.

Kaluza, Pablo; Urdapilleta, Eugenio

2014-10-01

201

Perancangan Pengenal QR (Quick Response) Code Dengan Jaringan Syaraf Tiruan Metode Perceptron  

OpenAIRE

Quick Response (QR) Code is used to store important information of an item or product. QR Code has a very random pattern and can not be distinguished. QR Code can also be dirty and damaged. Research conducted on the pattern of QR Code in order to find out the information stored in the QR Code. The method used to identify patterns of QR Code is to use Artificial Neural Networks Perceptron method. Perceptron is a neural network method is often used for pattern recognition. The input to the syst...

Novalia

2013-01-01

202

Dealing with Recurrence  

Medline Plus

Full Text Available Resources Brochures & Videos Resource Links Books & Periodicals Cancer Centers print email Resources » Brochures & Videos Dealing with Recurrence We know that the topic of recurrence ...

203

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

204

A quenched large deviation principle and a Parisi formula for a Perceptron version of the GREM  

CERN Document Server

We introduce a perceptron version of the Generalized Random Energy Model, and prove a quenched Sanov type large deviation principle for the empirical distribution of the random energies. The dual of the rate function has a representation through a variational formula which is closely related to the Parisi variational formula for the SK-model.

Bolthausen, E

2010-01-01

205

On the Vapnik-Chervonenkis dimension of the Ising-perceptron  

OpenAIRE

The VC dimension of the Ising perceptron with binary patterns is calculated by numerical enumerations for system sizes N <= 31. It is significantly larger than N/2. The data suggest that there is probably no well defined asymptotic behaviour for N to infinity.

Mertens, S.

1996-01-01

206

Perfect transmission and highly asymmetric light localization in photonic multilayers  

International Nuclear Information System (INIS)

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 of the type (BA)k(AB)k(AABB)m is proposed, combining perfect transmission and highly asymmetric electric field localization. Strength and asymmetry of localization can be controlled independently to be of use in tailoring nonreciprocal behavior of nonlinear all-optical diodes.

207

Perfect transmission and highly asymmetric light localization in photonic multilayers  

CERN Document Server

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 of the type (BA)^k(AB)^k(AABB)^m is proposed, combining perfect transmission and highly asymmetric electric field localization. Strength and asymmetry of localization can be controlled independently, to be of use in tailoring non-reciprocal behavior of nonlinear all-optical diodes.

Zhukovsky, Sergei V

2009-01-01

208

Interfacial effects in multilayers  

International Nuclear Information System (INIS)

Interfacial structure and the atomic interactions between atoms at interfaces in multilayers or nano-laminates have significant impact on the physical properties of these materials. A technique for the experimental evaluation of interfacial structure and interfacial structure effects is presented and compared to experiment. In this paper the impact of interfacial structure on the performance of x-ray, soft x-ray and extreme ultra-violet multilayer optic structures is emphasized. The paper is concluded with summary of these results and an assessment of their implications relative to multilayer development and the study of buried interfaces in solids in general

209

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

OpenAIRE

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...

Mokhtar Attari; Mounir Bouhedda; Fayçal Benrekia

2013-01-01

210

Self-Organizing Map and Multi-Layer Perceptron Neural Network Based Data Mining To Envisage Agriculture Cultivation  

OpenAIRE

Study on characteristics of soil, to determine the types of crops suitable for cultivation in a particular region can increase the yield to greater extent, which minimizes the expenditures involved in irrigation and application of fertilizers. With the tested techniques available for calibrating the quality of soil and the crops suitable for cultivation in it, it is possible to determine the exact crop, irrigation patterns and even the cycle and quantity of fertilizer application. This paper ...

Venkatesh, E. T.; Thangaraj, Dr P.

2008-01-01

211

Multilayers on flexible mica  

International Nuclear Information System (INIS)

X-Ray optics can be broadly classified as being either reflective or transmissive, with either broad or narrow band pass, configured to be either non-focusing or focusing. Multi-layers which reflect (diffract) soft x-rays with intermediate resolution, which can be elastically bent into either convex, non-focusing or concave, focusing geometries, are of interest in this work. Preparation and characteristics of the multilayers are described with the experimental details of the concave and convex geometries

212

Dealing with Recurrence  

Medline Plus

Full Text Available Resources Brochures & Videos Resource Links Books & Periodicals Cancer Centers print email Resources » Brochures & Videos Dealing with Recurrence We know that the topic of recurrence in cancer patients can be an overwhelming ...

213

Recurrent zosteriform herpes simplex  

OpenAIRE

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; Yatgiri R

1992-01-01

214

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

OpenAIRE

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 different...

Miyoshi, Seiji; Hara, Kazuyuki; Okada, Masato

2004-01-01

215

Efficient Bayesian Inference for Learning in the Ising Linear Perceptron and Signal Detection in CDMA  

OpenAIRE

Efficient new Bayesian inference technique is employed for studying critical properties of the Ising linear perceptron and for signal detection in Code Division Multiple Access (CDMA). The approach is based on a recently introduced message passing technique for densely connected systems. Here we study both critical and non-critical regimes. Results obtained in the non-critical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in ...

Neirotti, Juan P.; Saad, David

2005-01-01

216

Identificación de cláusulas y chunks para el Euskera, usando Filtrado y Ranking con el Perceptron  

OpenAIRE

Este artículo presenta sistemas de identificación de chunks y cláusulas para el euskera, combinando gramáticas basadas en reglas con técnicas de aprendizaje automático. Más concretamente, se utiliza el modelo de Filtrado y Ranking con el Perceptron (Carreras, Màrquez y Castro, 2005): un modelo de aprendizaje que permite identificar estructuras sintácticas parciales en la oración, con resultados óptimos para estas tareas en inglés. Este modelo permite incorporar nuev...

Alegri?a Loinaz, In?aki; Arrieta Cortajarena, Bertol; Carreras Pe?rez, Xavier; Di?az Ilarraza Sa?nchez, Arantza; Uria Garin, Larraitz

2008-01-01

217

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

218

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

219

Advances in Artificial Neural Networks – Methodological Development and Application  

OpenAIRE

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

220

Recurrence Tracking Microscope  

OpenAIRE

In order to probe nanostructures on a surface we present a microscope based on the quantum recurrence phenomena. A cloud of atoms bounces off an atomic mirror connected to a cantilever and exhibits quantum recurrences. The times at which the recurrences occur depend on the initial height of the bouncing atoms above the atomic mirror, and vary following the structures on the surface under investigation. The microscope has inherent advantages over existing techniques of scanni...

Saif, Farhan

2006-01-01

221

Recurrent Preterm Birth  

OpenAIRE

Recurrent preterm birth is frequently defined as two or more deliveries before 37 completed weeks of gestation. The recurrence rate varies as a function of the antecedent for preterm birth: spontaneous versus indicated. Spontaneous preterm birth is the result of either preterm labor with intact membranes or preterm prelabor rupture of the membranes. This article reviews the body of literature describing the risk of recurrence of spontaneous and indicated preterm birth. Also discussed are the ...

Mazaki-tovi, Shali; Romero, Roberto; Kusanovic, Juan Pedro; Erez, Offer; Pineles, Beth L.; Gotsch, Francesca; Mittal, Pooja; Than, Nandor Gabor

2007-01-01

222

Recurrent Pneumonia in Children  

OpenAIRE

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 pneumo...

Solmaz Çelebi; Mustafa Hac?mustafao?lu; Yücehan Albayrak; Nurcan Bulur

2010-01-01

223

Magnetic multilayer interface anisotropy  

Energy Technology Data Exchange (ETDEWEB)

Ni/Mo and Ni/V multilayer magnetic anisotropy has been investigated as a function of Ni layer thickness, frequency and temperature. Variable frequency ferromagnetic resonance (FMR) measurements show, for the first time, significant frequency dependence associated with the multilayer magnetic anisotropy. The thickness dependence allows one to extract the interface contribution from the total anisotropy. Temperature dependent FMR (9 GHz) and room temperature magnetization indicate that strain between Ni and the non-magnetic layers is contributing significantly to the source of the interface anisotropy and the state of the interfacial magnetization. In order to examine the interface properties of other transition metal multilayer systems, investigations on Fe/Cu are underway and CoCr/Ag is being proposed. ESR measurements have been reported on Gd substituted YBaCuO superconductors and a novel quasi-equilibrium method has been developed to determine quickly and precisely the transition temperature. During the next project period the P.I. proposes to (1) extend the variable frequency FMR measurements to low temperature, where extremely large interface anisotropies are known to obtain in Ni/Mo and Ni/V and are proposed to exist in Ni/W; (2) obtain accurate dc anisotropies via a novel, variable temperature torque magnetometer currently under construction; (3) expand upon his initial findings in Fe/Cu multilayer investigations; (4) begin anisotropy investigations on Co/Ag and CoCr/Ag multilayers where the easy magnetization direction depends upon the Cr concentration; (4) make and characterize Bi based superconductors according to resistivity, thermal conductivity and thermoelectric power and construct YBaCuO based superconducting loop-gap'' resonators for use in his magnetic resonance work.

Pechan, M.J.

1990-01-01

224

Magnetic multilayer interface anisotropy  

Energy Technology Data Exchange (ETDEWEB)

Ni/Mo and Ni/V multilayer magnetic anisotropy has been investigated as a function of Ni layer thickness, frequency and temperature. Variable frequency ferromagnetic resonance (FMR) measurements show, for the first time, significant frequency dependence associated with the multilayer magnetic anisotropy. The thickness dependence allows one to extract the interface contribution from the total anisotropy. Temperature dependant FMR (9 GHz) and room temperature magnetization indicate that strain between Ni and the non-magnetic layers if contributing significantly to the source of the interface anisotropy and the state of the interfacial magnetization. In order to examine the interface properties of other transition metal multilayer systems, investigations on Fe/Cu are underway and CoCr/Ag is being proposed. ESR measurements have been reported on Gd substituted YBaCuO superconductors and a novel quasi-equilibrium method has been developed to determine quickly and precisely the transition temperature. During the next project the P.I. proposes to (1) extend the variable frequency FMR measurements to low temperature, where extremely large interface anisotropies are known to obtain in Ni/Mo and Ni/V and are proposed to exist in Ni/W; (2) obtain accurate dc anisotropies via a novel, variable temperature torque magnetometer currently under construction; (3) expand upon his initial findings in Fe/Cu multilayer investigations; (4) begin anisotropy investigations on Co/Ag and CoCr/Ag multilayers where the easy magnetization direction depends upon the Cr concentration; (4) make and characterize Bi based superconductors according to resistivity, thermal conductivity and thermoelectric power and construct YBaCuO based superconducting loop-gap'' resonators for use in his magnetic resonance work. 2 figs.

Pechan, M.J.

1991-01-01

225

Calculation of nonstationary heat conduction in multilayer objects with boundary conditions of the third kind  

Science.gov (United States)

Some aspects of the calculation of nonstationary heat conduction in multilayer objects with boundary conditions of the third kind are considered. The homogeneous problem with inhomogeneous boundary conditions is solved for the one-dimensional case. The proposed solution has an explicit form and may be useful in numerical calculations due to the recurrence representation of the basic relations.

Vendin, S. V.

1993-08-01

226

Universal perceptron and DNA-like learning algorithm for binary neural networks: LSBF and PBF implementations.  

Science.gov (United States)

Universal perceptron (UP), a generalization of Rosenblatt's perceptron, is considered in this paper, which is capable of implementing all Boolean functions (BFs). In the classification of BFs, there are: 1) linearly separable Boolean function (LSBF) class, 2) parity Boolean function (PBF) class, and 3) non-LSBF and non-PBF class. To implement these functions, UP takes different kinds of simple topological structures in which each contains at most one hidden layer along with the smallest possible number of hidden neurons. Inspired by the concept of DNA sequences in biological systems, a novel learning algorithm named DNA-like learning is developed, which is able to quickly train a network with any prescribed BF. The focus is on performing LSBF and PBF by a single-layer perceptron (SLP) with the new algorithm. Two criteria for LSBF and PBF are proposed, respectively, and a new measure for a BF, named nonlinearly separable degree (NLSD), is introduced. In the sense of this measure, the PBF is the most complex one. The new algorithm has many advantages including, in particular, fast running speed, good robustness, and no need of considering the convergence property. For example, the number of iterations and computations in implementing the basic 2-bit logic operations such as AND, OR, and XOR by using the new algorithm is far smaller than the ones needed by using other existing algorithms such as error-correction (EC) and backpropagation (BP) algorithms. Moreover, the synaptic weights and threshold values derived from UP can be directly used in designing of the template of cellular neural networks (CNNs), which has been considered as a new spatial-temporal sensory computing paradigm. PMID:23460987

Chen, Fangyue; Chen, Guanrong Ron; He, Guolong; Xu, Xiubin; He, Qinbin

2009-10-01

227

Weight space structure and analysis using a finite replica number in the Ising perceptron  

OpenAIRE

The weight space of the Ising perceptron in which a set of random patterns is stored is examined using the generating function of the partition function $\\phi(n)=(1/N)\\log [Z^n]$ as the dimension of the weight vector $N$ tends to infinity, where $Z$ is the partition function and $[ ... ]$ represents the configurational average. We utilize $\\phi(n)$ for two purposes, depending on the value of the ratio $\\alpha=M/N$, where $M$ is the number of random patterns. For $\\alpha < \\a...

Obuchi, Tomoyuki; Kabashima, Yoshiyuki

2009-01-01

228

Equine recurrent uveitis: treatment.  

Science.gov (United States)

Equine recurrent uveitis has traditionally been treated with medical management to reduce ocular inflammation and control pain during a single episode. Newer management methods include surgical options such as cyclosporine implantation and vitrectomy. These methods were developed not only to control inflammation but also to eliminate the underlying cause of uveitis in order to prevent recurrence. PMID:21870352

Curling, Amanda

2011-06-01

229

Screening in multilayer graphene  

OpenAIRE

In this article we study the static polarization in ABC-stacked multilayer graphene. Since the density of states diverges for these systems if the number of layers exceeds three, screening effects are expected to be important. In the random phase approximation, screening can be included through the polarization. We derive an analytical integral expression for the polarization in both the full-band model and an effective two-band model. Numerical evaluation of these integrals...

Gelderen, R.; Olsen, R.; Smith, C. Morais

2013-01-01

230

Multilayer graphene waveguides  

OpenAIRE

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 lay...

Smirnova, Daria; Iorsh, Ivan; Shadrivov, Ilya; Kivshar, Yuri

2014-01-01

231

Mobile Multilayer IPsec protocol  

OpenAIRE

A mobile user moves around and switches between wireless cells, subnets and domains, it needs to maintain the session continuity. At the same time security of signaling and transport media should not be compromised. A multi-layer security framework involving user authentication, packet based encryption and access control mechanism can provide the desired level of security to the mobile users. Supporting streaming traffic in a mobile wireless Internet is faced with several challenges due to co...

Gayathri, T.; Venkadajothi, S.; Kalaivani, S.; Divya, C.; Suresh Gnana Dhas, Dr C.

2009-01-01

232

Irreversible Multilayer Adsorption  

OpenAIRE

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. A...

Nielaba, P.; Privman, V.; Wang, J. -s

1993-01-01

233

Recurrence for branching Markov chains  

OpenAIRE

The question of recurrence and transience of branching Markov chains is more subtle than for ordinary Markov chains; they can be classified in transience, weak recurrence, and strong recurrence. We review criteria for transience and weak recurrence and give several new conditions for weak recurrence and strong recurrence. These conditions make a unified treatment of known and new examples possible and provide enough information to distinguish between weak and strong recurren...

Mu?ller, Sebastian

2007-01-01

234

Learning by random walks in the weight space of the Ising perceptron  

International Nuclear Information System (INIS)

Several variants of a stochastic local search process for constructing the synaptic weights of an Ising perceptron are studied. In this process, binary patterns are sequentially presented to the Ising perceptron and are then learned as the synaptic weight configuration is modified through a chain of single- or double-weight flips within the compatible weight configuration space of the earlier learned patterns. This process is able to reach a storage capacity of ??0.63 for pattern length N = 101 and ??0.41 for N = 1001. If in addition a relearning process is exploited, the learning performance is further improved to a storage capacity of ??0.80 for N = 101 and ??0.42 for N = 1001. We found that, for a given learning task, the solutions constructed by the random walk learning process are separated by a typical Hamming distance, which decreases with the constraint density ? of the learning task; at a fixed value of ?, the width of the Hamming distance distribution decreases with N

235

Weight space structure and analysis using a finite replica number in the Ising perceptron  

International Nuclear Information System (INIS)

The weight space of the Ising perceptron, in which a set of random patterns is stored, is examined using the generating function of the partition function ?(n) = (1/N)log[Zn] as the dimension of the weight vector N tends to infinity, where Z is the partition function and [c] represents the configurational average. We utilize ?(n) for two purposes, depending on the value of the ratio ? = M/N, where M is the number of random patterns. For ?s = 0.833..., we employ ?(n), in conjunction with Parisi's one-step replica symmetry breaking scheme in the limit of n?0, to evaluate the complexity that characterizes the number of disjoint clusters of weights that are compatible with a given set of random patterns, which indicates that, in typical cases, the weight space is equally dominated by a single large cluster of exponentially many weights and exponentially many small clusters of a single weight. For ?>?s, on the other hand, ?(n) is used to assess the rate function of a small probability that a given set of random patterns is atypically separable by the Ising perceptrons. We show that the analyticity of the rate function changes at ? = ?GD = 1.245..., which implies that the dominant configuration of the atypically separable patterns exhibits a phase transition at this critical ratio. Extensive numerical experiments are conducted to support the theoretical predictions

236

Weight space structure and analysis using a finite replica number in the Ising perceptron  

Science.gov (United States)

The weight space of the Ising perceptron, in which a set of random patterns is stored, is examined using the generating function of the partition function phi(n) = (1/N)log[Zn] as the dimension of the weight vector N tends to infinity, where Z is the partition function and [\\cdots] represents the configurational average. We utilize phi(n) for two purposes, depending on the value of the ratio ? = M/N, where M is the number of random patterns. For ?number of disjoint clusters of weights that are compatible with a given set of random patterns, which indicates that, in typical cases, the weight space is equally dominated by a single large cluster of exponentially many weights and exponentially many small clusters of a single weight. For ?>?s, on the other hand, phi(n) is used to assess the rate function of a small probability that a given set of random patterns is atypically separable by the Ising perceptrons. We show that the analyticity of the rate function changes at ? = ?GD = 1.245..., which implies that the dominant configuration of the atypically separable patterns exhibits a phase transition at this critical ratio. Extensive numerical experiments are conducted to support the theoretical predictions.

Obuchi, Tomoyuki; Kabashima, Yoshiyuki

2009-12-01

237

Recurrent vaginal candidiasis.  

Science.gov (United States)

Recurrent vaginal candidiasis is one of the most common reasons for patients visiting their primary care doctors. Majority of the cases are caused by Candida albicans. Controlling of risk factors such as diabetes mellitus, used of broad spectrum antibiotics, contraceptive pills and steroid therapy helps in managing recurrent vaginal candidiasis. Initial 14-day course of oral azoles and followed by 6 months maintenance are effective in treating majority of the cases. Failure to treat recurrent vaginal candidiasis can lead to various bio-psycho-social complications. PMID:15190674

Loh, K Y; Sivalingam, N

2003-12-01

238

Recurrent idiopathic lumbosacral plexopathy.  

Science.gov (United States)

Recurrent idiopathic lumbosacral plexopathy has rarely been reported in the literature. The present report describes a 59-year-old man presenting with recurrent episodes of acute leg pain, followed by weakness. After each episode, symptoms progressed for several months before peaking. Thereafter, gradual recovery ensued. Electrodiagnostic studies revealed primarily a patchy pattern of denervation in the distribution of part of the lumbosacral plexus, sparing the paraspinal muscles. Extensive evaluations for an underlying cause were unrevealing. Thus, these episodes are suggestive of recurrent idiopathic lumbosacral plexopathy, and the present case is compared with previous cases reported in the literature. PMID:10951450

Yee, T

2000-09-01

239

Beyond Bragg mirrors: the design of aperiodic omnidirectional multilayer reflectors  

Energy Technology Data Exchange (ETDEWEB)

A new method that enables omnidirectional reflectivity for all polarizations of incident light over a wide selectable range of wavelengths was used to design aperiodic multilayer mirrors. Choosing the materials, and with the desired threshold value of the reflection coefficient also being given, the resulting reflectors work for all polarizations in a predetermined range of incidence angles and wavelengths. They are 1D photonic aperiodic crystals composed of a stack of layers arranged according to a deterministic aperiodic substitutive sequence appropriately determined. In the calculation of the optical multilayer properties with the Rayleigh-Abeles matrices, the use of the computationally efficient building block recurrence or trace-antitrace map techniques avoids numerical instability and strongly reduces computational time. Experimental measurements of a prototype satisfying predetermined requirements fabricated after the sequence generated by {sigma}:(a, b){yields}(bba, bbba) show excellent agreement.

Axel, Francoise [Laboratoire de Physique des Solides, CNRS-UMR8502 and Universite Paris-Sud, Batiment 510, 91405 Orsay Cedex (France); Peyriere, Jacques, E-mail: axel@lps.u-psud.fr, E-mail: Jacques.Peyriere@math.u-psud.fr [Laboratoire de Mathematiques, CNRS-UMR8628 and Universite Paris-Sud, Batiment 425, 91405 Orsay Cedex (France)

2011-01-21

240

Dynamics of cancer recurrence  

OpenAIRE

Mutation-induced drug resistance in cancer often causes the failure of therapies and cancer recurrence, despite an initial tumor reduction. The timing of such cancer recurrence is governed by a balance between several factors such as initial tumor size, mutation rates and growth kinetics of drug-sensitive and resistance cells. To study this phenomenon we characterize the dynamics of escape from extinction of a subcritical branching process, where the establishment of a clone...

Foo, Jasmine; Leder, Kevin

2013-01-01

241

Recurrent Urinary Bladder Paraganglioma  

OpenAIRE

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

242

Recurrent Novae - A Review  

OpenAIRE

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 m...

Mukai, Koji

2014-01-01

243

Multi-layers castings  

OpenAIRE

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...

Szajnar, J.; Wro?bel, P.; Wro?bel, T.

2010-01-01

244

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

245

Magnetic metallic multilayers  

International Nuclear Information System (INIS)

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

246

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

247

Hyperhomocysteinemia in Recurrent Miscarriage  

International Nuclear Information System (INIS)

Objective: An elevated total plasma homocysteine level has been suggested as a possible risk factor in women suffering from recurrent pregnancy loss. The current study was undertaken to assess the association between homocysteine, folate, cobalamin (vitamin B12) and the risk of recurrent pregnancy loss. Design: Case . control study Materials and Methods: The study included 57 non-pregnant Egyptian women. They were classified according to their obstetric history into 2 groups: 32 cases with at least two consecutive miscarriages (Study group), and 25 cases with normal obstetric history (Control group). All cases were tested for plasma total homocysteine, serum folate and cobalamin (vitamin B12). Results: The fasting total homocysteine was significantly higher in the study group as compared to the control group. While the median concentrations for the vitamins studied were significantly lower in women of the study group as compared to the controls. Elevated homocysteine and reduced vitamin B12 can be considered risk factors for recurrent miscarriage with odds ratio (OR) and 95% confidence intervals (95% CI) of 1.839 (1.286, 2.63) and 1.993 (1.346, 2.951) respectively in the group of recurrent miscarriages. The OR (95% CI) in the study population for low serum folate concentrations was 1.23 (0.776, 2.256). Conclusion: Elevated homocysteine and reduced serum vitamin B12 are risk factors for recurrent miscarriage. Low serum folate did not seem a risk factor for recurrent miscarriage. Testing for homocysteine levels in women suffering from unexplained recurrent miscarriage and pre-conceptional supplementation with vitamin B12 might be beneficial to improve pregnancy outcome

248

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

249

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

250

Immunomodulation in recurrent miscarriage.  

Science.gov (United States)

There are many etiological factors responsible for recurrent abortions. However, no explanation can be identified in approximately 40-50 % of women with recurrent miscarriage (RM). Several studies demonstrated that successful pregnancy is dependant on shifting of maternal immune response from (proinflammatory) Th1 toward (anti-inflammatory) Th2 phenotypes. It was suggested that unexplained RM might be due to immunologic factors. Recently, there is improved understanding regarding the role of the different immune cells and proteins that are important at each stage of a normal pregnancy. Various immune-based therapies with variable clinical evidences have been reported in women with RM with variable efficacy. Still there is lack of information about the mode of action and possible adverse effects of the treatment and a reliable marker for patient selection for immunopotentiation. Adequately powered placebo-controlled studies are required to study and treat couples with the so-called idiopathic recurrent miscarriage. PMID:24966498

Kumar, Ashok

2014-06-01

251

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

252

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

253

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

254

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

255

Recurrent acute glomerulonephritis.  

Science.gov (United States)

Biopsy-proven recurrent acute glomerulonephritis (AGN) is extremely rare and is usually seen in children with acute, well-defined streptococcal infections. We present here a patient with recurrent AGN in the absence of chronic bacterial infection. The subject, an 80-year-old man, had eight episodes of acute nephritic syndrome following upper respiratory tract infection. No abnormalities were detected during remissions. Renal biopsies during two of those episodes showed typical postinfectious acute exsudative endocapillary glomerulonephritis, while results of another biopsy performed during remission were normal. PMID:1992666

Glotz, D; Jouvin, M H; Nochy, D; Druet, P; Bariety, J

1991-02-01

256

Recurrent atrial myxoma.  

Science.gov (United States)

We have chosen this case of sporadic atrial myxoma for our presentation because it had a particular evolution, with recurrence at 8 years after surgical excision (echocardiography was performed every year) and a particular diagnostic means - at echocardiographic follow-up, the patient being asymptomatic. This presentation, together with a review of literature included in the article, emphasizes the importance of a careful postoperative follow-up of the patients and the existence of some particular aspects of the evolution and symptomatology of recurrent atrial myxoma. PMID:16366135

Macarie, C; Stoica, E; Chioncel, O; Carp, A; Gherghiceanu, D; Stiru, O; Zarma, L; Herlea, V

2004-01-01

257

Tackling a recurrent pinealoblastoma.  

Science.gov (United States)

Pineoblastomas are rare, malignant, pineal region lesions that account for <0.1% of all intracranial tumors and can metastasize along the neuroaxis. Pineoblastomas are more common in children than in adults and adults account for <10% of patients. The management of pinealoblastoma is multimodality approach, surgery followed with radiation and chemotherapy. In view of aggressive nature few centres use high dose chemotherapy with autologus stem cell transplant in newly diagnosed cases but in recurrent setting the literature is very sparse. The present case represents the management of pinealoblastoma in the recurrent setting with reirradiation and adjuvant carmustine chemotherapy wherein the management guidelines are not definitive. PMID:25210636

Palled, Siddanna; Kalavagunta, Sruthi; Beerappa Gowda, Jaipal; Umesh, Kavita; Aal, Mahalaxmi; Abdul Razack, Tanvir Pasha Chitraduraga; Gowda, Veerabhadre; Viswanath, Lokesh

2014-01-01

258

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

259

Impact properties of multilayered materials  

OpenAIRE

The possibilities of multilayered materials as high impact resistance materials are considered with reference to safety in transportation. The mechanism of fracture of the different layers of the material produces an enhancement of the impact resistance behavior and, as a consequence, a lower quantity of material is needed with the corresponding saving in weight of the transport vehicle. The reinforcing material of this multilayered composite are steel sheets. The sheets, two or more, are dip...

Vazquez Vaamonde, A.

1993-01-01

260

Anomalous Magnetoresistance in Fibonacci Multilayers  

OpenAIRE

The present paper theoretically investigates magnetoresistance curves in quasiperiodic magnetic multilayers for two different growth directions, namely [110] and [100]. We considered identical ferromagnetic layers separated by non-magnetic layers with two different thicknesses chosen based on the Fibonacci sequence. Using parameters for Fe/Cr multilayers, four terms were included in our description of the magnetic energy: Zeeman, cubic anisotropy, bilinear and biquadratic co...

Machado, L. D.; Bezerra, C. G.; Correa, M. A.; Chesman, C.; Pearson, J. E.; Hoffmann, A.

2012-01-01

261

[Equine recurrent uveitis].  

Science.gov (United States)

Equine recurrent uveitis is an important ocular disease and the most common cause for blindness in horses and mules worldwide. The anatomy, physiology, immunology and inflammatory reactions of the uveal tract are discussed. Possible etiologies and the clinical signs are described. A detailed description of possible therapies is given and the prognosis is discussed. PMID:9324749

Spiess, B M

1997-01-01

262

Dealing with Recurrence  

Medline Plus

Full Text Available ... Videos Resource Links Books & Periodicals Cancer Centers print email Resources » Brochures & Videos Dealing with Recurrence We know ... your Knowledge: Ovarian Cancer Quiz Join our mailing list ... var input_id = '#mc_embed_signup'; var f = mce_jQuery(input_id); if (ftypes[index]=='address'){ input_id = '#mce-'+fnames[index]+'-addr1'; f = mce_ ...

263

Recurrent Gallstone Ileus  

Science.gov (United States)

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, and she was diagnosed with recurrent gallstone ileus requiring a repeat operation. While management of gallstone ileus can be achieved through a single-stage operation including enterolithotomy and cholecystectomy with repair of biliary-enteric fistula or by enterolithotomy alone, the literature supports enterolithotomy alone as the treatment of choice for gallstone ileus due to decreased mortality and morbidity. However, the latter approach does not obviate potential recurrence. We present this case of recurrent gallstone ileus to elucidate and review the pathogenesis, presentation, diagnosis, and consensus recommendations regarding management of this disorder. PMID:22723467

Hayes, Nicolas; Saha, Sanjoy

2012-01-01

264

Branched coordination multilayers on gold.  

Science.gov (United States)

A C3-symmetric tridentate hexahydroxamate ligand molecule was specially synthesized and used for coordination self-assembly of branched multilayers on Au surfaces precoated with a self-assembled monolayer (SAM) of ligand anchors. Layer-by-layer (LbL) growth of multilayers via metal-organic coordination using Zr4+ ions proceeds with high regularity, adding one molecular layer in each step, as shown by ellipsometry, wettability, UV-vis spectroscopy, and atomic force microscopy (AFM). The branched multilayer films display improved stiffness, as well as a unique defect self-repair capability, attributed to cross-linking in the layers and lateral expansion over defects during multilayer growth. Transmetalation, i.e., exposure of Zr4+-based assemblies to Hf4+ ions, was used to evaluate the cross-linking. Conductive atomic force microscopy (AFM) was used to probe the electrical properties of the multilayers, revealing excellent dielectric behavior. The special properties of the branched layers were emphasized by comparison with analogous multilayers prepared similarly using linear (tetrahydroxamate) ligand molecules. The process of defect annihilation by bridging over defective areas, attributed to lateral expansion via the excess bishydroxamate groups, was demonstrated by introduction of artificial defects in the anchor monolayer, followed by assembly of two layers of either the linear or the branched molecule. Analysis of selective binding of Au nanoparticles (NPs) to unblocked defects emphasized the superior repair mechanism in the branched layers with respect to the linear ones. PMID:16351119

Wanunu, Meni; Vaskevich, Alexander; Cohen, Sidney R; Cohen, Hagai; Arad-Yellin, Rina; Shanzer, Abraham; Rubinstein, Israel

2005-12-21

265

Neural networks and chaos: construction, evaluation of chaotic networks, and prediction of chaos with multilayer feedforward networks.  

Science.gov (United States)

Many research works deal with chaotic neural networks for various fields of application. Unfortunately, up to now, these networks are usually claimed to be chaotic without any mathematical proof. The purpose of this paper is to establish, based on a rigorous theoretical framework, an equivalence between chaotic iterations according to Devaney and a particular class of neural networks. On the one hand, we show how to build such a network, on the other hand, we provide a method to check if a neural network is a chaotic one. Finally, the ability of classical feedforward multilayer perceptrons to learn sets of data obtained from a dynamical system is regarded. Various boolean functions are iterated on finite states. Iterations of some of them are proven to be chaotic as it is defined by Devaney. In that context, important differences occur in the training process, establishing with various neural networks that chaotic behaviors are far more difficult to learn. PMID:22462998

Bahi, Jacques M; Couchot, Jean-François; Guyeux, Christophe; Salomon, Michel

2012-03-01

266

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)

267

A comparative study of different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron  

OpenAIRE

The work presents a comparative assessment of seven different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron (MLP) based classifier. The seven feature sets employed here consist of shadow features, octant centroids, longest runs, angular distances, effective spans, dynamic centers of gravity, and some of their combinations. On experimentation with a database of 3000 samples, the maximum recognition rate of 95.80% is observed with b...

Das, Nibaran; Mollah, Ayatullah Faruk; Sarkar, Ram; Basu, Subhadip

2010-01-01

268

Debugging of neural network based on 3-layer perceptron by the example of expert system in ophthalmology  

Directory of Open Access Journals (Sweden)

Full Text Available The algorithm of development of full set of tests for debugging of neural network expert systems based on threelayer perceptron is considered. The algo-rithm is based on rules extraction from neural network and using of the method of technical diagnostics PODEM. The use of algorithm for testing of expert sys-tem Glaukoma Complaint for prognosis of compliance of ophthalmologic patients is described.

Kuzmin Alexey Konstantinovich

2011-02-01

269

Sistema de análise de ativos através de redes neurais de múltiplas camadas. Asset analysis system using multilayer neural networks  

Directory of Open Access Journals (Sweden)

Full Text Available When investors decide to “adventure” through stock markets they search for a method to provide safety on making decision. In fact, there is no precise way to know which stocks will became a profitable investiment. Technical analysis is a discipline that support the investors on making decisions. Such a discipline uses a set of tools and statistical methods to forecast the market’s movement. Such a paper presents the develpment of a robotical Trade System, using a heuristic method. The system has a Neural Network multilayer perceptron, trained with an algorithm for back propagation error. Thus, approaching to the technical analysis without emotional aspects, using the Neural Network forecast on supporting the decisions of a investor on stock market. In analyzing the results of the neural network can be seen that the neural network got a result of 42.6% higher than the diagnostic of the technical analysis.Quando investidores decidem se “aventurar” pelo mercado de renda variável, como pelo mercado de ações, buscam um método de ter mais segurança na tomada de decisão. Na prática, não há como saber quais ativos tornar-se-ão um investimento lucrativo. No mercado acionário, a Análise Técnica procura auxiliar o investidor na tomada de decisão. Para isso, utiliza-se de ferramentas e de métodos estatísticos para tentar predizer os movimentos do mercado. Este artigo apresenta o desenvolvimento de um Trade System robótico, utilizando um método heurístico. O sistema conta com uma rede neural multilayer perceptron, treinada com o algoritmo de retro propagação de erro, aproximando-se da análise técnica sem o fator emoção. Ao avaliar os resultados da rede neural, pode ser visto que a mesma obteve um resultado de 42,6% maior do que o diagnóstico da análise técnica.

Vânia Medianeira Flores Costa

2012-04-01

270

Polyelectrolyte Multilayers Fabricated from Antifungal ?-Peptides: Design of Surfaces that Exhibit Antifungal Activity Against Candida albicans  

OpenAIRE

The fungal pathogen Candida albicans can form biofilms on the surfaces of medical devices that are resistant to drug treatment and provide a reservoir for recurrent infections. The use of fungicidal or fungistatic materials to fabricate or coat the surfaces of medical devices has the potential to reduce or eliminate the incidence of biofilm-associated infections. Here, we report on (i) the fabrication of multilayered polyelectrolyte thin films (PEMs) that promote the surface-mediated release ...

Karlsson, Amy J.; Flessner, Ryan M.; Gellman, Samuel H.; Lynn, David M.; Palecek, Sean P.

2010-01-01

271

Integrated segmentation and recognition of connected handwritten characters with recurrent neural network  

Science.gov (United States)

In this paper, we propose an efficient method for integrated segmentation and recognition of connected handwritten characters with recurrent neural network. In the proposed method, a new type of recurrent neural network is developed for training the spatial dependencies in connected handwritten characters. This recurrent neural network differs from Jordan's and Elman's recurrent networks in view of functions and architectures because it was originally extended from the multilayer feedforward neural network for improving the discrimination and generalization power. In order to verify the performance of the proposed method, experiments with the NIST database have been performed and the performance of the proposed method has been compared with those of the previous integrated segmentation and recognition methods. The experimental results reveal that the proposed method is superior to the previous integrated segmentation and recognition methods in view of discrimination and generalization ability.

Lee, Seong-Whan; Lee, Eung-Jae

1996-03-01

272

Chronic recurrent multifocal osteomyelitis  

International Nuclear Information System (INIS)

Chronic recurrent multifocal osteomyelitis was first described in 1972 and to date 33 cases have been reported, all but one from outside the United States. This unusual osteomyelitis is characteristically recurrent and multifocal with a predilection for the metaphyses. Cultures are persistently negative and antibiotics do not appear to affect the course of the disease, which may be as long as 15 years. Females are affected twice as frequently as males and half the cases are less than ten years old. Antistreptolysin 0 titers are elevated in a quarter of the patients, and there may be a history of previous throat infection. There is an association with pustulosis palmoplantaris. We present two additional cases from the United States. (orig.)

273

Poincaré recurrence for observations  

OpenAIRE

A high dimensional dynamical system is often studied by experimentalists through the measurement of a relatively low number of different quantities, called an observation. Following this idea and in the continuity of Boshernitzan's work, for a measure preserving system, we study Poincar\\'e recurrence for the observation. The link between the return time for the observation and the Hausdorff dimension of the image of the invariant measure is considered. We prove that when the...

Rousseau, Jero?me; Saussol, Benoit

2008-01-01

274

Recurrence Relations and Determinants  

OpenAIRE

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 independe...

Janjic, Milan

2011-01-01

275

A morphological perceptron with gradient-based learning for Brazilian stock market forecasting.  

Science.gov (United States)

Several linear and non-linear techniques have been proposed to solve the stock market forecasting problem. However, a limitation arises from all these techniques and is known as the random walk dilemma (RWD). In this scenario, forecasts generated by arbitrary models have a characteristic one step ahead delay with respect to the time series values, so that, there is a time phase distortion in stock market phenomena reconstruction. In this paper, we propose a suitable model inspired by concepts in mathematical morphology (MM) and lattice theory (LT). This model is generically called the increasing morphological perceptron (IMP). Also, we present a gradient steepest descent method to design the proposed IMP based on ideas from the back-propagation (BP) algorithm and using a systematic approach to overcome the problem of non-differentiability of morphological operations. Into the learning process we have included a procedure to overcome the RWD, which is an automatic correction step that is geared toward eliminating time phase distortions that occur in stock market phenomena. Furthermore, an experimental analysis is conducted with the IMP using four complex non-linear problems of time series forecasting from the Brazilian stock market. Additionally, two natural phenomena time series are used to assess forecasting performance of the proposed IMP with other non financial time series. At the end, the obtained results are discussed and compared to results found using models recently proposed in the literature. PMID:22391234

Araújo, Ricardo de A

2012-04-01

276

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

277

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

278

Computing and fabricating multilayer models  

OpenAIRE

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

279

Equine recurrent airway obstruction  

Directory of Open Access Journals (Sweden)

Full Text Available Equine Recurrent Airway Obstruction (RAO, also known as heaves or broken wind, is one of the most common disease in middle-aged horses. Inflammation of the airway is inducted by organic dust exposure. This disease is characterized by neutrophilic inflammation, bronchospasm, excessive mucus production and pathologic changes in the bronchiolar walls. Clinical signs are resolved in 3-4 weeks after environmental changes. Horses suffering from RAO are susceptible to allergens throughout their lives, therefore they should be properly managed. In therapy the most importanthing is to eliminate dustexposure, administration of corticosteroids and use bronchodilators to improve pulmonary function.

Artur Nied?wied?

2014-10-01

280

[Recurrent urinary tract infections].  

Science.gov (United States)

Recurrent urinary tract infections (RUTI) are a frequent clinical problem in sexually active young women, pregnant or postmenopausal women and in patients with underlying urological abnormalities. The present chapter reviews RUTI based on their classification: relapses, which usually occur early (cystitis, continuous antibiotic prophylaxis, postcoital antibiotic prophylaxis, topical vaginal estrogens, Lactobacillus, cranberry juice, intravesical administration of non-virulent E. coli strains and vaccines, among others. Several diagnostic-therapeutic algorithms are included. These algorithms are based on the type of urinary infection (relapse-reinfection), on the type of patient (young, postmenopausal, or pregnant women) and on the number of episodes of RUTI. PMID:16854356

Pigrau-Serrallach, Carlos

2005-12-01

281

Endometriosis mimicking hernia recurrence.  

Science.gov (United States)

Endometriosis is a common gynecologic condition and has been described in several locations, mostly in the pelvis. Extragenital endometriosis may appear as a painful nodule evoking an inguinal hernia. Scar endometriosis after inguinal hernia repair seems to be a rare occurrence. We report an unusual case of a 28-year-old woman who developed a scar endometriosis 2 years after an inguinal hernia repair. This case highlights that the presence of a painless inguinal mass similar to a recurrent hernia, with possible swelling related to the menstrual cycle, may evoke endometriosis, especially after a previous hernia repair and should lead to prompt diagnosis, wide excision, and gynecological advice. PMID:17119856

Ducarme, G; Uzan, M; Poncelet, C

2007-04-01

282

Recurrent cutaneous leishmaniasis.  

Science.gov (United States)

We present a case of an 18-year-old male patient who, after two years of inappropriate treatment for cutaneous leishmaniasis, began to show nodules arising at the edges of the former healing scar. He was immune competent and denied any trauma. The diagnosis of recurrent cutaneous leishmaniasis was made following positive culture of aspirate samples. The patient was treated with N-methylglucamine associated with pentoxifylline for 30 days. Similar cases require special attention mainly because of the challenges imposed by treatment. PMID:23793208

Gomes, Ciro Martins; Damasco, Fabiana dos Santos; Morais, Orlando Oliveira de; Paula, Carmen Déa Ribeiro de; Sampaio, Raimunda Nonata Ribeiro

2013-01-01

283

Recurrent malignant gliomas.  

Science.gov (United States)

In almost all patients, malignant glioma recurs following initial treatment with maximal safe resection, conformal radiotherapy, and temozolomide. This review describes the many options for treatment of recurrent malignant gliomas, including reoperation, alternating electric field therapy, chemotherapy, stereotactic radiotherapy or radiosurgery, or some combination of these modalities, presenting the evidence for each approach. No standard of care has been established, though the antiangiogenic agent, bevacizumab; stereotactic radiotherapy or radiosurgery; and, perhaps, combined treatment with these 2 modalities appear to offer modest benefits over other approaches. Clearly, randomized trials of these options would be advantageous, and novel, more efficacious approaches are urgently needed. PMID:25219814

Kirkpatrick, John P; Sampson, John H

2014-10-01

284

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

285

Recurrent tarsal tunnel syndrome.  

Science.gov (United States)

Recurrence of tarsal tunnel syndrome after surgery may be due to inadequate release, lack of understanding or appreciation of the actual anatomy involved, variations in the anatomy of the nerve(s), failure to execute the release properly, bleeding with subsequent scarring, damage to the nerve and branches, persistent hypersensitivity of the nerves, and preexisting intrinsic damage to the nerve. Approaches include more thorough release, use of barrier materials to decrease adherence of the nerve to surrounding tissues to avoid traction neuritis, excisions of neuromas using conduits, and consideration of nerve stimulators and systemic medications to deal with persistent neural pain. PMID:25129355

Gould, John S

2014-09-01

286

Recurrent Inversion Formulas  

OpenAIRE

Let $F(z)=z-H(z)$ with $o(H(z))\\geq 2$ be a formal map from $\\bC^n$ to $\\bC^n$ and $G(z)$ the formal inverse of $F(z)$. In this paper, we fist study the deformation $F_t(z)=z-tH(z)$ and its formal inverse map $G_t(z)$. We then derive two recurrent formulas for the formal inverse $G(z)$. The first formula in certain situations provides a more efficient method for the calculation of $G(z)$ than other well known inversion formulas. The second one is differential free but only w...

Zhao, Wenhua

2003-01-01

287

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

288

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

289

Line Structures in Recurrence Plots  

OpenAIRE

Recurrence plots exhibit line structures which represent typical behaviour of the investigated system. The local slope of these line structures is connected with a specific transformation of the time scales of different segments of the phase-space trajectory. This provides us a better understanding of the structures occuring in recurrence plots. The relationship between the time-scales and line structures are of practical importance in cross recurrence plots. Using this rela...

Marwan, Norbert; Kurths, Juergen

2004-01-01

290

Local recurrence of laryngeal carcinoma  

OpenAIRE

Stoma recurrence following total laryngectomy is one of the most severe complications with extremely poor prognosis. Objective: The aim of our study is to analyze the risk factors for stoma recurrence development and to highlight the measures for prevention.Materials and methods: We preformed retrospective study on 530 patients who underwent total laryngectomy at Queen Giovanna Hospital end Ministry of Interior Medical Institute, Sofia for a period of 2 years.Results: Stoma recurrence deve...

Skerleva, D.; Stoyanov, S.; Rangachev, J.; Assenova, K.

2011-01-01

291

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

292

MAGNETIC MULTILAYERS : STATICS AND DYNAMICS  

OpenAIRE

In the framework of Ginzburg-Landay theory we calculate static and dynamical properties of ferromagnetic multilayers : Tc, mean magnetization and inelastic neutron scattering cross section. The magnon spectrum has a band structure, but the gaps vanish for certain values of k and ?. The cross section strongly increases at the points where gaps vanish.

Fishman, F.; Schwabl, F.; Schwenk, D.

1988-01-01

293

Asymmetric growth in polyelectrolyte multilayers.  

Science.gov (United States)

Radioactive counterions were used to track the ratio of positive to negative polymer repeat units within a polyelectrolyte multilayer made from poly(diallyldimethylammonium chloride), PDADMAC, and poly(styrene sulfonate), PSS. For this widely employed pair of "linearly" assembled polyelectrolytes it was found that the accepted model of charge overcompensation for each layer is incorrect. In fact, overcompensation at the surface occurs only on the addition of the polycation, whereas PSS merely compensates the PDADMAC. After the assembly of about a dozen layers, excess positive sites begin to accrue in the multilayer. Treating the surface as a reaction-diffusion region for pairing of polymer charges, a model profile was constructed. It is shown that different reaction-diffusion ranges of positive and negative polyelectrolyte charge lead to a blanket of glassy, stoichiometric complex growing on top of a layer of rubbery, PDADMAC-rich complex. Though overcompensation and growth was highly asymmetric with respect to the layer number, entirely conventional "linear" assembly of the multilayer was observed. The impact of asymmetric growth on various properties of multilayers is discussed. PMID:23672490

Ghostine, Ramy A; Markarian, Marie Z; Schlenoff, Joseph B

2013-05-22

294

Multilayer High-Gradient Insulators  

Energy Technology Data Exchange (ETDEWEB)

Multilayer High-Gradient Insulators are vacuum insulating structures composed of thin, alternating layers of dielectric and metal. They are currently being developed for application to high-current accelerators and related pulsed power systems. This paper describes some of the High-Gradient Insulator research currently being conducted at Lawrence Livermore National Laboratory.

Harris, J R

2006-08-16

295

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.

2012-01-01

296

Geospatial scenario based modelling of urban and agricultural intrusions in Ramsar wetland Deepor Beel in Northeast India using a multi-layer perceptron neural network  

Science.gov (United States)

In recent decades, the world has experienced unprecedented urban growth which endangers the green environment in and around urban areas. In this work, an artificial neural network (ANN) based model is developed to predict future impacts of urban and agricultural expansion on the uplands of Deepor Beel, a Ramsar wetland in the city area of Guwahati, Assam, India, by 2025 and 2035 respectively. Simulations were carried out for three different transition rates as determined from the changes during 2001-2011, namely simple extrapolation, Markov Chain (MC), and system dynamic (SD) modelling, using projected population growth, which were further investigated based on three different zoning policies. The first zoning policy employed no restriction while the second conversion restriction zoning policy restricted urban-agricultural expansion in the Guwahati Municipal Development Authority (GMDA) proposed green belt, extending to a third zoning policy providing wetland restoration in the proposed green belt. The prediction maps were found to be greatly influenced by the transition rates and the allowed transitions from one class to another within each sub-model. The model outputs were compared with GMDA land demand as proposed for 2025 whereby the land demand as produced by MC was found to best match the projected demand. Regarding the conservation of Deepor Beel, the Landscape Development Intensity (LDI) Index revealed that wetland restoration zoning policies may reduce the impact of urban growth on a local scale, but none of the zoning policies was found to minimize the impact on a broader base. The results from this study may assist the planning and reviewing of land use allocation within Guwahati city to secure ecological sustainability of the wetlands.

Mozumder, Chitrini; Tripathi, Nitin K.

2014-10-01

297

An Increasing Hybrid Morphological-Linear Perceptron with Evolutionary Learning and Phase Correction for Financial Time Series Forecasting  

Science.gov (United States)

In this paper we present a suitable model to solve the financial time series forecasting problem, called increasing hybrid morphological-linear perceptron (IHMP). An evolutionary training algorithm is presented to design the IHMP (learning process), using a modified genetic algorithm (MGA). The learning process includes an automatic phase correction step that is geared at eliminating the time phase distortions that typically occur in financial time series forecasting. Furthermore, we compare the proposed IHMP with other neural and statistical models using two complex nonlinear problems of financial forecasting.

de A. Araújo, Ricardo; Sussner, Peter

298

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

299

Recurrent respiratory papillomatosis.  

Science.gov (United States)

Recurrent respiratory papillomatosis is an uncommon clinical disorder of the respiratory epithelium caused by HPV. It shares an identical viral etiology with genital condyloma and, in all likelihood, is transmitted at the time of birth (juvenile onset RRP) or through intimate sexual contact (adult onset RRP). Despite the precision of the surgical laser under magnification of the operating microscope, a substantial proportion of patients with RRP, adults as well as pediatric, require repeated operations at frequent intervals because of severe hoarseness and upper airway obstruction. For the management of at least a subset of patients, the efficacy of adjuvant agents (interferon is a leading choice) should be investigated in a multi-institutional clinical trial. For the potential prophylactic benefit, cesarean sections in selected high-risk expectant mothers should be considered. PMID:8869953

Kashima, H K; Mounts, P; Shah, K

1996-09-01

300

A recurrent patent ductus arteriosus.  

Science.gov (United States)

Patent ductus arteriosus (PDA) can occur as part of more congenital cardiac malformations or as an isolate finding. Spontaneous, transcatheter, surgical closure, and pharmacological treatment have been reported. We present a case of recurrent PDA after the initial course of a pharmacological treatment. Also this case focuses on recurrent PDA after the initial course of a pharmacological treatment. PMID:19321210

Tulino, Viviana; Dattilo, Giuseppe; Tulino, Domenico; Marte, Filippo; Patanè, Salvatore

2011-05-01

301

Anomalous magnetoresistance in Fibonacci multilayers  

Science.gov (United States)

We theoretically investigated magnetoresistance curves in quasiperiodic magnetic multilayers for two different growth directions, namely, [110] and [100]. We considered identical ferromagnetic layers separated by nonmagnetic layers with two different thicknesses chosen based on the Fibonacci sequence. Using parameters for Fe/Cr multilayers, four terms were included in our description of the magnetic energy: Zeeman, cubic anisotropy, bilinear coupling, and biquadratic coupling. The minimum energy was determined by the gradient method and the equilibrium magnetization directions found were used to calculate magnetoresistance curves. By choosing spacers with a thickness such that biquadratic coupling is stronger than bilinear coupling, unusual behaviors for the magnetoresistance were observed: (i) for the [110] case, there is a different behavior for structures based on even and odd Fibonacci generations, and, more interesting, (ii) for the [100] case, we found magnetic field ranges for which the magnetoresistance increases with magnetic field.

Machado, L. D.; Bezerra, C. G.; Correa, M. A.; Chesman, C.; Pearson, J. E.; Hoffmann, A.

2012-06-01

302

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

303

Anomalous magnetoresistance in Fibonacci multilayers.  

Energy Technology Data Exchange (ETDEWEB)

We theoretically investigated magnetoresistance curves in quasiperiodic magnetic multilayers for two different growth directions, namely, [110] and [100]. We considered identical ferromagnetic layers separated by nonmagnetic layers with two different thicknesses chosen based on the Fibonacci sequence. Using parameters for Fe/Cr multilayers, four terms were included in our description of the magnetic energy: Zeeman, cubic anisotropy, bilinear coupling, and biquadratic coupling. The minimum energy was determined by the gradient method and the equilibrium magnetization directions found were used to calculate magnetoresistance curves. By choosing spacers with a thickness such that biquadratic coupling is stronger than bilinear coupling, unusual behaviors for the magnetoresistance were observed: (i) for the [110] case, there is a different behavior for structures based on even and odd Fibonacci generations, and, more interesting, (ii) for the [100] case, we found magnetic field ranges for which the magnetoresistance increases with magnetic field.

Machado, L. D.; Bezerra, C. G.; Correa, M. A.; Chesman, C.; Pearson, J. E.; Hoffmann, A. (Materials Science Division); (Universidade Federal do Rio Grande do Norte)

2012-01-01

304

Multilayer weighted social network model  

Science.gov (United States)

Recent empirical studies using large-scale data sets have validated the Granovetter hypothesis on the structure of the society in that there are strongly wired communities connected by weak ties. However, as interaction between individuals takes place in diverse contexts, these communities turn out to be overlapping. This implies that the society has a multilayered structure, where the layers represent the different contexts. To model this structure we begin with a single-layer weighted social network (WSN) model showing the Granovetterian structure. We find that when merging such WSN models, a sufficient amount of interlayer correlation is needed to maintain the relationship between topology and link weights, while these correlations destroy the enhancement in the community overlap due to multiple layers. To resolve this, we devise a geographic multilayer WSN model, where the indirect interlayer correlations due to the geographic constraints of individuals enhance the overlaps between the communities and, at the same time, the Granovetterian structure is preserved.

Murase, Yohsuke; Török, János; Jo, Hang-Hyun; Kaski, Kimmo; Kertész, János

2014-11-01

305

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

306

Tests Of Flexible Multilayer Insulations  

Science.gov (United States)

Composite blankets containing reflective layers compared with fibrous silica insulation. Report describes experimental and theoretical study of 11 flexible insulating blankets ranging in thickness from 1.0 to 2.5 in. Multilayer insulations intended for use in partial vacuums of outer planetary atmospheres, where mean free paths of gas molecules much less than characteristic lengths of cells in insulation and consequently conductive and convective effects of gas minimal.

Kourtides, D. A.; Pitts, W. C.

1991-01-01

307

Magnetoelastic interactions in multilayer microwires  

Energy Technology Data Exchange (ETDEWEB)

Amorphous magnetic microwires exhibit outstanding magnetic characteristics as giant Barkhausen jump or nearly non-hysteretic behaviour that make them very suitable as sensing elements in various devices. In this article, we overview the different families of microwires and summarise most relevant results in connection with the magnetoelastic interlayer interactions in multilayer microwires. Improved magnetic behaviour can be observed in bi-layer microwires consisting of a magnetic nucleus coated by insulating cover. By employing combined sputtering and electroplating techniques, a novel series of multilayered magnetic microwires have been recently introduced. They consist typically of a magnetic nucleus and several shells having insulating and/or metallic nature, the latter magnetic or not. The magnetic character of the multilayer microwire will then depend on the magnetoelastic coupling between layers. External layers induce compressive stresses on the soft amorphous nucleus resulting in induced axial or circular anisotropies depending on magnetostriction sign. In a similar way, reduction of measuring temperature results in tensile stress as a consequence of different thermal expansion coefficients of various layers.

Vazquez, M. [Instituto de Ciencia de Materiales, CSIC. 28049 Madrid (Spain)]. E-mail: mvazquez@icmm.csic.es; Pirota, K. [Instituto de Ciencia de Materiales, CSIC. 28049 Madrid (Spain); Torrejon, J. [Instituto de Ciencia de Materiales, CSIC. 28049 Madrid (Spain); Badini, G. [Instituto de Ciencia de Materiales, CSIC. 28049 Madrid (Spain); Torcunov, A. [Instituto de Ciencia de Materiales, CSIC. 28049 Madrid (Spain)

2006-09-15

308

Ultra-thin multilayer capacitors.  

Energy Technology Data Exchange (ETDEWEB)

The fabrication of ultra-thin lanthanum-doped lead zirconium titanate (PLZT) multilayer ceramic capacitors (MLCCs) using a high-power pulsed ion beam was studied. The deposition experiments were conducted on the RHEPP-1 facility at Sandia National Laboratories. The goal of this work was to increase the energy density of ceramic capacitors through the formation of a multilayer device with excellent materials properties, dielectric constant, and standoff voltage. For successful device construction, there are a number of challenging requirements including achieving correct stoichiometric and crystallographic composition of the deposited PLZT, as well as the creation of a defect free homogenous film. This report details some success in satisfying these requirements, although 900 C temperatures were necessary for PLZT perovskite phase formation. These temperatures were applied to a previously deposited multi-layer film which was then post-annealed to this temperature. The film exhibited mechanical distress attributable to differences in the coefficient of thermal expansion (CTE) of the various layers. This caused significant defects in the deposited films that led to shorts across devices. A follow-on single layer deposition without post-anneal produced smooth layers with good interface behavior, but without the perovskite phase formation. These issues will need to be addressed in order for ion beam deposited MLCCs to become a viable technology. It is possible that future in-situ heating during deposition may address both the CTE issue, and result in lowered processing temperatures, which in turn could raise the probability of successful MLCC formation.

Renk, Timothy Jerome; Monson, Todd C.

2009-06-01

309

Parallel Processing of a Multilayer Routing Package  

OpenAIRE

With the increasing density of components on Printed Circuit Boards (PCBs) and the advancement of fabrication technologies for multiplayer PCBs, improvement of speed and techniques for the Computer Aided Design of multilayer PCBs has become a major area of research. The paper discusses the parallel processing of layering and routing algorithms for design of multilayer PCBs on a network of small computers with a moderately high speed communication medium. Multilayer PCB design consists in part...

Srinivas, Mk; Radhakrishnan, T.

1991-01-01

310

Multilayer Analysis and Visualization of Networks  

CERN Document Server

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

311

Electrical Conductivity of Collapsed Multilayer Graphene Tubes  

Directory of Open Access Journals (Sweden)

Full Text Available Synthesis of multilayer graphene on copper wires by a chemical vapor deposition method is reported. After copper etching, the multilayer tube collapses forming stripes of graphitic films, their electrical conductance as a function of temperature indicate a semiconductor-like behavior. Using the multilayer graphene stripes, a cross junction is built and owing to its electrical behavior we propose that a tunneling process exists in the device.

D. Mendoza

2012-06-01

312

Recurrent Novae in M31  

CERN Document Server

The reported positions of 964 suspected nova eruptions in M31 recorded through the end of calendar year 2013 have been compared in order to identify recurrent nova candidates. To pass the initial screen and qualify as a recurrent nova candidate two or more eruptions were required to be coincident within 0.1', although this criterion was relaxed to 0.15' for novae discovered on early photographic patrols. A total of 118 eruptions from 51 potential recurrent nova systems satisfied the screening criterion. To determine what fraction of these novae are indeed recurrent the original plates and published images of the relevant eruptions have been carefully compared. This procedure has resulted in the elimination of 27 of the 51 progenitor candidates (61 eruptions) from further consideration as recurrent novae, with another 8 systems (17 eruptions) deemed unlikely to be recurrent. Of the remaining 16 systems, 12 candidates (32 eruptions) were judged to be recurrent novae, with an additional 4 systems (8 eruptions) b...

Shafter, A W; Rector, T A; Schweizer, F; Hornoch, K; Orio, M; Pietsch, W; Darnley, M J; Williams, S C; Bode, M F; Bryan, J

2014-01-01

313

Magnetoresistive multilayers deposited on the AAO membranes  

Energy Technology Data Exchange (ETDEWEB)

Silicon and GaAs wafers are the most commonly used substrates for deposition of giant magnetoresistive (GMR) multilayers. We explored a new type of a substrate, prepared electrochemically by anodization of aluminum sheets, for deposition of GMR multilayers. The surface of this AAO substrate consists of nanosized hemispheres organized in a regular hexagonal array. The current applied along the substrate surface intersects many magnetic layers in the multilayered structure, which results in enhancement of giant magnetoresistance effect. The GMR effect in uncoupled Co/Cu multilayers was significantly larger than the magnetoresistance of similar structures deposited on Si.

Malkinski, Leszek M. [Advanced Materials Research Institute, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA 70148 (United States)]. E-mail: lmalkins@uno.edu; Chalastaras, Athanasios [Advanced Materials Research Institute, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA 70148 (United States); Vovk, Andriy [Advanced Materials Research Institute, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA 70148 (United States); Jung, Jin-Seung [Department of Chemistry, Kangnung National University, Kangnung 210702 (Korea, Republic of) ; Kim, Eun-Mee [Department of Chemistry, Kangnung National University, Kangnung 210702 (Korea, Republic of) ; Jun, Jong-Ho [Department of Applied Chemistry, Kunkuk University, Chungju 151747 (Korea, Republic of) ; Ventrice, Carl A. [Advanced Materials Research Institute, University of New Orleans, 2000 Lakeshore Drive, New Orleans, LA 70148 (United States)

2005-02-01

314

Magnetoresistive multilayers deposited on the AAO membranes  

International Nuclear Information System (INIS)

Silicon and GaAs wafers are the most commonly used substrates for deposition of giant magnetoresistive (GMR) multilayers. We explored a new type of a substrate, prepared electrochemically by anodization of aluminum sheets, for deposition of GMR multilayers. The surface of this AAO substrate consists of nanosized hemispheres organized in a regular hexagonal array. The current applied along the substrate surface intersects many magnetic layers in the multilayered structure, which results in enhancement of giant magnetoresistance effect. The GMR effect in uncoupled Co/Cu multilayers was significantly larger than the magnetoresistance of similar structures deposited on Si

315

Chronic recurrent multifocal osteomyelitis.  

Science.gov (United States)

Chronic recurrent multifocal osteomyelitis (CRMO) is an autoinflammatory bone disease occurring primarily in children and adolescents. Episodes of systemic inflammation occur due to immune dysregulation without autoantibodies, pathogens or antigen-specific T cells. CRMO is characterised by the insidious onset of pain with swelling and tenderness over the affected bones. Clavicular involvement was the classical description; however, the metaphyses and epiphyses of long bones are frequently affected. Lesions may occur in any bone, including vertebrae. Characteristic imaging includes bone oedema, lytic areas, periosteal reaction and soft tissue reaction. Biopsies from affected areas display polymorphonuclear leucocytes with osteoclasts and necrosis in the early stages. Subsequently, lymphocytes and plasma cells predominate followed by fibrosis and signs of reactive new bone forming around the inflammation. Diagnosis is facilitated by the use of STIR MRI scanning, potentially obviating the need for biopsy and unnecessary long-term antibiotics due to incorrect diagnosis. Treatment options include non-steroidal anti-inflammatory drugs and bisphosphonates. Biologics have been tried in resistant cases with promising initial results. Gene identification has not proved easy although research in this area continues. Early descriptions of the disease suggested a benign course; however, longer-term follow up shows that it can cause significant morbidity and longer-term disability. Although it has always been thought of as very rare, the prevalence is likely to be vastly underestimated due to poor recognition of the disease. PMID:23654059

Roderick, Marion R; Ramanan, Athimalaipet V

2013-01-01

316

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

317

Giant recurrent retroperitoneal liposarcoma presenting as a recurrent inguinal hernia  

OpenAIRE

Retroperitoneal liposarcoma presenting as an inguinal hernia is a rare entity. We present the first case of Giant recurrent liposarcoma presenting as a recurrent inguinal hernia in a 40-year-old male. Physical examination showed an irreducible lump in the right inguinal region and a scar in the right lumbar and right inguinal region. Computed tomography (CT) scan of abdomen revealed it to be a retro peritoneal mass extending into the right inguinal region along and involving the cord...

Sameer Vora; Kori, Channabasappa G.; Shenoy, Sachin S.; Borisa, Ashok D.; Bakhshi, Girish D.; Bhandarwar, Ajay H.

2011-01-01

318

Primary breast lymphoma; disease recurrence  

Directory of Open Access Journals (Sweden)

Full Text Available Primary breast lymphoma (PBL accounts 0.4-0.5% of all breast cancers. The aim is to present the patient diagnosed with recurrency of primary breast lymphoma treated six year ago without radiotherapy. A 63-years-old woman patient admitted to our hospital with a palpabl mass in her left breast. Six years ago she was treated with chemoterapy after local excision for primary left breast lymphoma. Imaging modalities showed multiple lesion in breast and confirmed with biopsy. Pathologic results were similar with first one and the case was accepted as PBL recurrence. Multipl metastases has been determined with staging modalities. Patient started to chemotherapy treatment. PBL is a rare cancer of breast and there is no consensus at the treatment of disease. In the literature addition of radiotherapy to the treatment prevents local recurrence. There were occured recurrence without radiotherapy, mimicked that radiotherapy is an essential modality in PBL treatment.

Hüseyin KADIO?LU

2012-01-01

319

Generalised scheme for optimal learning in recurrent neural networks  

OpenAIRE

A new learning scheme is proposed for neural network architectures like the Hopfield network and bidirectional associative memory. This scheme, which replaces the commonly used learning rules, follows from the proof of the result that learning in these connectivity architectures is equivalent to learning in the 2-state perceptron. Consequently, optimal learning algorithms for the perceptron can be directly applied to learning in these connectivity architectures. Similar results are establishe...

Shanmukh, K.; Venkatesh, Yv

1995-01-01

320

Recurrence for random dynamical systems  

OpenAIRE

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; Rousseau, Jerome

2009-01-01

321

STDP in recurrent neuronal networks  

OpenAIRE

Recent results about spike-timing-dependent plasticity (STDP) in recurrently connected neurons are reviewed, with a focus on the relationship between the weight dynamics and the emergence of network structure. In particular, the evolution of synaptic weights in the two cases of incoming connections for a single neuron and recurrent connections are compared and contrasted. A theoretical framework is used that is based upon Poisson neurons with a temporally inhomogeneous firing rate and the asy...

MatthieuGilson; AnthonyBurkitt; LeoJVan Hemmen

2010-01-01

322

Management of Recurrent Cervical Cancer.  

Directory of Open Access Journals (Sweden)

Full Text Available Approximately 30% of cervical cancer patients will ultimately fail after definitive treatment.The reported 5-year survival rates of patients with treatment failure are between 3.2%and 13%. Management of recurrences depends on the extent of disease, primary treatment,and performance status/comorbidity. Primary treatment, relapse pattern, and characteristicsat presentation are determinants for prognosis after recurrence. Concurrent chemoradiationachieves significantly better outcome than radiation alone in patients with recurrences afterprimary radical hysterectomy. Isolated paraaortic lymph node metastasis and local recurrenceconfined to cervix were associated with better outcome in failure after definitive radiotherapy.When definitive radiotherapy or surgery plus adjuvant radiotherapy has failed,pelvic exenteration is usually necessary for those had central relapse with clear pelvic sidewalland free of distant metastasis. Radical hysterectomy with or without pelvic node dissectionis considered feasible for small uterine and/or vaginal recurrences with high operativemorbidity. For patients who have recurrences involving the irradiated pelvic wall, pelvicexenteration is usually not an option for curative intent. Intraoperative radiotherapy, combinedoperative radiotherapeutic treatment, and laterally extended endopelvic resection havebeen used in such situations with some success. Chemotherapy alone is basically palliative.Generally, combination chemotherapy could attain higher response rates with no significantimprovement in overall survival than cisplatin alone. Recent investigations indicated benefitsof positron emission tomography in more accurate restaging of recurrent disease. Theimpact of various post-treatment surveillance strategies to early detect treatment failureremains to be evaluated.

Chyong-Huey Lai

2004-10-01

323

Preparation of metallic multilayers by electrocrystallization  

Science.gov (United States)

Reflection electron microscopy (REM) studies of Co electrocrystallization on Pt(111) surfaces under potential control have revealed a simultaneous multinuclear multilayer growth up to the coverage of some 10 monolayers. The feasibility of electrocrystallization to produce Co/Pt multilayers with comparable structures and magnetic properties to those by vapor-phase deposition is discussed.

Jyoko, Y.; Kashiwabara, S.; Hayashi, Y.

1993-09-01

324

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.

Khromova, I.; Andryieuski, Andrei

2014-01-01

325

Plasmon bands in multilayer graphene  

Science.gov (United States)

High-energy collective electronic excitations (plasmons) in freestanding multilayer graphene are studied by momentum-resolved electron energy-loss spectroscopy (EELS). For normal incidence, only the high-energy plasmon band is excited and we measure a blueshift of the ? -plasmon dispersion with increasing thickness. The observed transition between two-dimensional and three-dimensional behavior is explained using a layered-electron-gas (LEG) model. We propose a method to measure all individual plasmon bands by tilting the sample with respect to the electron beam. As a proof of concept, EELS experiments for three-layer graphene are compared with predictions from the LEG model.

Wachsmuth, P.; Hambach, R.; Benner, G.; Kaiser, U.

2014-12-01

326

A comparative study of different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron  

CERN Document Server

The work presents a comparative assessment of seven different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron (MLP) based classifier. The seven feature sets employed here consist of shadow features, octant centroids, longest runs, angular distances, effective spans, dynamic centers of gravity, and some of their combinations. On experimentation with a database of 3000 samples, the maximum recognition rate of 95.80% is observed with both of two separate combinations of features. One of these combinations consists of shadow and centriod features, i. e. 88 features in all, and the other shadow, centroid and longest run features, i. e. 124 features in all. Out of these two, the former combination having a smaller number of features is finally considered effective for applications related to Optical Character Recognition (OCR) of handwritten Arabic numerals. The work can also be extended to include OCR of handwritten characters of Arabic alphabet.

Das, Nibaran; Sarkar, Ram; Basu, Subhadip

2010-01-01

327

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

328

Understanding multilayers from a geometrical viewpoint.  

Science.gov (United States)

We reelaborate on the basic properties of lossless multilayers. We show that the transfer matrices for these multilayers have essentially the same algebraic properties as the Lorentz group SO(2, 1) in a (2 + 1)-dimensional space-time as well as the group SL(2, R) underlying the structure of the ABCD law in geometrical optics. By resorting to the Iwasawa decomposition, we represent the action of any multilayer as the product of three matrices of simple interpretation. This group-theoretical structure allows us to introduce bilinear transformations in the complex plane. The concept of multilayer transfer function naturally emerges, and its corresponding properties in the unit disk are studied. We show that the Iwasawa decomposition is reflected at this geometrical level in three simple actions that can be considered the basic pieces for a deeper understanding of the multilayer behavior. We use the method to analyze in detail a simple practical example. PMID:11876327

Yonte, Teresa; Monzón, Juan J; Sánchez-Soto, Luis L; Cariñena, José F; López-Lacasta, Carlos

2002-03-01

329

High-dimensional conformally recurrent manifolds  

OpenAIRE

Conformally recurrent pseudo-Riemannian manifolds of dimension n>4 are investigated. The Weyl tensor may be represented as a Koulkarni-Nomizu product involving a symmetric tensor and the recurrence vector. If the recurrence vector is a closed form, the Ricci and two other tensors are Weyl compatible. If the recurrence vector is non-null, a covariantly constant symmetric tensor exists, with geometric implications. If the metric is Lorentzian, a null recurrence vector makes th...

Mantica, Carlo A.; Molinari, Luca G.

2014-01-01

330

Dynamical diffraction in periodic multilayers  

CERN Document Server

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

331

Recurrent Novae in M31  

Science.gov (United States)

The reported positions of 964 suspected nova eruptions in M31 recorded through the end of calendar year 2013 have been compared in order to identify recurrent nova (RN) candidates. To pass the initial screen and qualify as a RN candidate, two or more eruptions were required to be coincident within 0.?1, although this criterion was relaxed to 0.?15 for novae discovered on early photographic patrols. A total of 118 eruptions from 51 potential RN systems satisfied the screening criterion. To determine what fraction of these novae are indeed recurrent, the original plates and published images of the relevant eruptions have been carefully compared. This procedure has resulted in the elimination of 27 of the 51 progenitor candidates (61 eruptions) from further consideration as RNe, with another 8 systems (17 eruptions) deemed unlikely to be recurrent. Of the remaining 16 systems, 12 candidates (32 eruptions) were judged to be RNe, with an additional 4 systems (8 eruptions) being possibly recurrent. It is estimated that ?4% of the nova eruptions seen in M31 over the past century are associated with RNe. A Monte Carlo analysis shows that the discovery efficiency for RNe may be as low as 10% that for novae in general, suggesting that as many as one in three nova eruptions observed in M31 arise from progenitor systems having recurrence times ? 100 yr. For plausible system parameters, it appears unlikely that RNe can provide a significant channel for the production of Type Ia supernovae.

Shafter, A. W.; Henze, M.; Rector, T. A.; Schweizer, F.; Hornoch, K.; Orio, M.; Pietsch, W.; Darnley, M. J.; Williams, S. C.; Bode, M. F.; Bryan, J.

2015-02-01

332

Recent advances in etched multilayer X-ray optics  

OpenAIRE

We present the recent advances achieved in the Laboratoire de Chimie Physique of Université Paris 6, in the field of the soft X-ray etched multilayer optics. Modellings and characterizations are given for the laminar multilayer amplitude gratings, the highly resolutive X-ray multilayer monochromators, the X-ray polychromators and the Bragg-Fresnel multilayer linear lenses.?

Andre?, J.; Sammar, A.; Bac, S.; Ouahabi, M.; Idir, M.; Soullie?, G.; Barchewitz, R.

1994-01-01

333

Recurrences for elliptic hypergeometric integrals  

CERN Document Server

In recent work (math.QA/0309252) on multivariate hypergeometric integrals, the author generalized a conjectural integral formula of van Diejen and Spiridonov to a ten parameter integral provably invariant under an action of the Weyl group E_7. In the present note, we consider the action of the affine Weyl group, or more precisely, the recurrences satisfied by special cases of the integral. These are of two flavors: linear recurrences that hold only up to dimension 6, and three families of bilinear recurrences that hold in arbitrary dimension, subject to a condition on the parameters. As a corollary, we find that a codimension one special case of the integral is a tau function for the elliptic Painlev\\'e equation.

Rains, E M

2005-01-01

334

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

335

Recurrent Kikuchi-Fujimoto disease  

OpenAIRE

We report the case of a 27-year-old, UK-born, Asian woman who suffered a rare recurrence of Kikuchi-Fujimoto disease. She presented with tender lymphadenopathy of the neck, fever and a prodrome of flu-like symptoms. She had a past medical history of biopsy-proven Kikuchi-Fujimoto disease of her right axilla 2 years earlier, which required no treatment. Following her repeat admission, a cervical lymph node biopsy confirmed a diagnosis of recurrent Kikuchi-Fujimoto disease. She did not improve ...

Spooner, Brendan Boyd; Rahman, Imdadur; Langford, Nigel; Ferner, Robin E.

2010-01-01

336

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

337

Magnetic properties of Ni/Pt multilayers  

International Nuclear Information System (INIS)

We have grown Ni/Pt multilayers with Pt buffer layer, by evaporation under UHV conditions on glass substrates maintained at 300 K. The magnetic properties of Ni/Pt multilayers are examined as a function of Ni layer thickness t Ni. The temperature dependence of the spontaneous magnetization M(T) is well described by a T 3/2 law in all multilayers. A spin-wave theory 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 coupling strength J I for various Ni layer thicknesses have been obtained

338

Near field imaging from multilayer lens.  

Science.gov (United States)

Multilayer superlens has been reported that it had advantages over the single metal layer superlens. In this work, single silver layer and Ag-SiO2 multilayer superlens devices working at wavelength of 365 nm were fabricated using standard photolithography method. Grating objects with line/space (190 nm/190 nm) resolution could be resolved through both kinds of lens structures with working distance up to 128 nm. However, Ag-SiO2 multilayer lens shows higher transmittance and image contrast than the single silver layer device, the experimental result proves the theoretical calculation. PMID:22408982

Li, Guixin; Li, Jensen; Tam, H L; Chan, C T; Cheah, K W

2011-12-01

339

Centrality in Interconnected Multilayer Networks  

CERN Document Server

Real-world complex systems exhibit multiple levels of relationships. In many cases, they require to be modeled by interconnected multilayer networks, characterizing interactions on several levels simultaneously. It is of crucial importance in many fields, from economics to biology, from urban planning to social sciences, to identify the most (or the less) influent nodes in a network. However, defining the centrality of actors in an interconnected structure is not trivial. In this paper, we capitalize on the tensorial formalism, recently proposed to characterize and investigate this kind of complex topologies, to show how several centrality measures -- well-known in the case of standard ("monoplex") networks -- can be extended naturally to the realm of interconnected multiplexes. We consider diagnostics widely used in different fields, e.g., computer science, biology, communication and social sciences, to cite only some of them. We show, both theoretically and numerically, that using the weighted monoplex obta...

De Domenico, Manlio; Omodei, Elisa; Gómez, Sergio; Arenas, Alex

2013-01-01

340

Multilayer sulfonated polyaromatic PEMFC membranes  

Energy Technology Data Exchange (ETDEWEB)

Sulfonated polyetheretherketone (sPEEK) membranes have been developed in which a hierarchical organisation into multilayers has been favoured during preparation using solvent casting. Bilayer membranes comprising sPEEK of different degrees of sulfonation (having ion exchange capacities between 1.1 and 1.6 meq g{sup -1}) have been characterised for their water uptake properties and proton conductivity. The composite membranes show no tendency to delaminate, even under prolonged operation in a hydrogen - oxygen fuel cell. By associating sPEEK of different water uptake characteristics, water back diffusion in an operating fuel cell is favoured, leading to a degree of control over the direction of water production at the anode or the cathode. Such a bilayer membrane has been operated at 110 C without reactant gas hydration for over 900 h. (Abstract Copyright [2005], Wiley Periodicals, Inc.)

Marrony, M.; Roziere, J.; Jones, D.J.; Lindheimer, A. [Laboratoire des Agregats Moleculaires et Materiaux Inorganiques, UMR CNRS 5072, Universite Montpellier II, Place Eugene Bataillon, 34095 Montpellier cedex 5 (France)

2005-08-01

341

Phase stability in metallic multilayers  

Science.gov (United States)

As the thin film materials used in electronic and optical applications continue to decrease in thickness to the nano-scales, marked changes in functional properties are expected to occur due to changes in crystal structure of these materials. Therefore, such multilayer systems have been of considerable interest due to the ability to control properties by engineering the structure of materials at these scales. The new characterization tools allow direct imaging and analysis of such materials in order to link the performance variations with the crystal structure variations. Transmission Electron Microscopy (TEM) has been often the technique of choice in characterization of nanomaterials enabling not only imaging the structure of the material but also chemically probing of the composition changes at a high spatial resolution. The ultimate resolution achievable in the electron microscope is a product of both microscope and the specimen and the simultaneous effect of each defines the quality and quantity of the information transferred through the microscope. In this sense, the common ion-beam assisted TEM sample preparation techniques have been deeply recognized as being surface damaging at high ion milling energies (>5kV) thus limiting the information transfer in the microscope. For the first time, a low energy (focused Ar ion beam milling system has been applied to remove the surface artifacts created by the high energy conventional broad Ar or focused Ga beam milling techniques. The overall quality of the samples drastically improved after the application of the low energy milling practices and the outcome results directly enhanced the clarity of the information gathered at the atomic and nanoscale by the electron microscope. Besides the specimen the resolution achievable in the electron microscope is strongly limited by the imperfections in the electron optics of the microscope column such as the spherical aberration of the electromagnetic lenses. Recently this problem has been solved by the correction of the spherical aberration of the microscope using a set of non-round lenses and consequently the information limit in an aberration corrected microscope (lens of a Scanning TEM microscope was successfully installed at The Ohio State University. The preliminary results from this microscope were presented in the content of this work where we have studied the microscope and performed first hand experiments. Finally we have addressed the phase stability in Cu/Nb and Ti/Nb nanoscale metallic multilayers by extensive use of these advance characterization techniques and tools. At reduced layer thickness (variables. We have investigated both the structural and chemical changes in the Cu/Nb and Ti/Nb nanoscale metallic mutilayers as a function of length scale in order to understand and predict the phase stability. The important constituents: volumetric free energy and interfacial energy changes were experimentally derived considering the chemistry and structure of the multilayers and competition between these thermodynamic terms well explains the observed structural changes in nanoscale metallic multilayers.

Genc, Arda

342

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

343

Recurrence Formulas for Fibonacci Sums  

OpenAIRE

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.; Martins, Joao L.

2008-01-01

344

Relativistic phase space dimensional recurrences  

CERN Document Server

We derive recurrence relations between phase space expressions in different dimensions by confining some of the coordinates to tori or spheres of radius $R$ and taking the limit as $R \\to \\infty$. These relations take the form of mass integrals, associated with extraneous momenta (relative to the lower dimension), and produce the result in the higher dimension.

Delbourgo, Robert

2003-01-01

345

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)

346

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

347

Integrated and Load Responsive Multilayer Insulation  

Science.gov (United States)

Multilayer insulation (MLI) is used to reduce heat leak into cryogenic systems such as tanks, dewars and instruments, and used to control spacecraft heat leak. MLI is typically used in a high vacuum (SOFI).

Dye, S.; Kopelove, A.; Mills, G. L.

2010-04-01

348

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

349

Resonant Diffusive Radiation in Random Multilayered Systems  

OpenAIRE

We have theoretically shown that the yield of diffuse radiation generated by relativistic electrons passing random multilayered systems can be increased when a resonant condition is met. Resonant condition can be satisfied for the wavelength region representing visible light as well as soft X-rays. The intensity of diffusive soft X-rays for specific multilayered systems consisting of two components is compared with the intensity of Cherenkov radiation. For radiation at photo...

Gevorkian, Zh S.; Verhoeven, J.

2005-01-01

350

Ordered organic-organic multilayer growth  

Energy Technology Data Exchange (ETDEWEB)

An ordered multilayer crystalline organic thin film structure is formed by depositing at least two layers of thin film crystalline organic materials successively wherein the at least two thin film layers are selected to have their surface energies within .+-.50% of each other, and preferably within .+-.15% of each other, whereby every thin film layer within the multilayer crystalline organic thin film structure exhibit a quasi-epitaxial relationship with the adjacent crystalline organic thin film.

Forrest, Stephen R; Lunt, Richard R

2015-01-13

351

Planar multilayer assemblies containing block copolymer aggregates.  

Science.gov (United States)

The design, preparation, and properties of planar multilayer structures composed of various combinations of sequentially deposited polyelectrolyte (PE) chains and self-assembled layers of individual block copolymer aggregates (vesicles, micelles, or large compound micelles (LCMs)) are described. The aggregates contain negatively or positively charged corona chains while the PE multilayers contain alternating polyanionic or polycationic chains deposited on silicon wafers. The final structures consist of combinations of layers of various charged species: multilayers of alternating PEs of poly(allyl hydrochloride) (PAH) and poly(acrylic acid) (PAA) as well as vesicles, micelles, or large compound micelles of ionized poly(styrene)-b-poly(4-vinylpyridine) (PS-b-P4VP) or of poly(styrene)-b-poly(acrylic acid) (PS-b-PAA). Two types of layer-by-layer (LbL) multilayer structures were studied: individual aggregate layers sandwiched between PE multilayers and layers of individual aggregates of various morphologies and of different corona chain charges, deposited on top of each other without intermediate multilayers or individual layers of PEs. The strong interactions between the successive layers are achieved mainly by electrostatic attraction between the oppositely charged layers. The planar LbL multilayers containing block copolymer aggregates could, potentially, be used as carriers for multiple functional components; each aggregate layer could be loaded with hydrophobic (in the core of the micelles, LCMs, or vesicle walls) or hydrophilic functional molecules (in the vesicular cavities). The overall thickness of such planar LbL multilayers can be controlled precisely and can vary from tens of nanometers to several micrometers depending on the number of layers, the sizes of the aggregates, and the complexity of the structure. PMID:24417699

Xiao, Lin; Vyhnalkova, Renata; Sailer, Miloslav; Yang, Guang; Barrett, Christopher J; Eisenberg, Adi

2014-01-28

352

Transmission Electron Microscopy of Metallic Multilayers  

OpenAIRE

We give an overview of use of the transmission electron microscope (TEM) in the characterisation of metallic multilayers. The different types of structural information available from phase and diffraction contrast imaging, as well as the various diffraction modes, are described. The particular usefulness of techniques such as the Fresnel fringe method for multilayer interface characterisation is emphasised. The use of analytical TEM and scanning TEM (STEM) for chemical characterisation is als...

Walls, M.; Chevalier, J. -p; Hy?tch, M.

1996-01-01

353

Fretting wear of metallic multilayer films  

International Nuclear Information System (INIS)

Fretting wear behaviour of electrodeposited Cu/Ni multilayer films with 10 and 5 nm thick sublayers has been investigated against a hardened steel ball as the counter body and compared with that of the constituents, Cu and Ni. The wear tests were carried out by using a ball-on-flat geometry at a translation frequency of 8 Hz and slip amplitude of 100 ?m. Friction force was recorded on line during the tests. At the end of the tests, the wear scars were examined by laser surface profilometry, scanning electron microscopy and energy dispersive X-ray microanalysis. It has been observed that the frictional and wear mechanisms are very different for copper, nickel and Cu/Ni multilayers. Fretting of copper creates a relatively smooth wear scar mainly by mechanical ploughing of the asperities on steel counterbody (abrasive wear) and shows a very little third body interaction. Fretting of nickel involves adhesive wear resulting in a large transfer of steel to nickel, which is attributed to the strong chemical interaction between nickel and the steel counterbody. Fretting on multilayers involves a strong third body interaction resulting in ploughing mainly by debris (abrasive wear). The coefficient of friction is approximately 0.45 for copper, and approximately 0.8 for nickel as well as for multilayers. The values of the coefficient of friction for nickel and Cu/Ni multilayers found under the present fretting conditions are approximately double the corresponding values reportey double the corresponding values reported earlier for sliding wear conditions. It has been found that Cu/Ni multilayer is more resistance to fretting wear than the constituents, copper and nickel. Furthermore, the fretting wear resistance of Cu/Ni multilayers with 5 nm thick sublayer is better than that of the multilayers with 10 nm thick sublayers

354

Lipid layers on polyelectrolyte multilayer supports  

OpenAIRE

The mechanism of formation of supported lipid layers from phosphatidylcholine and phosphatidylserine vesicles in solution on polyelectrolyte multilayers was studied by a variety of experimental techniques. The interaction of zwitterionic and acidic lipid vesicles, as well as their mixtures, with polyelectrolyte supports was followed in real time by micro-gravimetry. The fabricated lipid-polyelectrolyte composite structures on top of multilayer coated colloidal particles were characterized by ...

Fischlechner, Martin; Zaulig, Markus; Meyer, Stefan; Estrela-lopis, Irina; Cue?llar, Luis; Irigoyen, Joseba; Pescador, Paula; Brumen, Milan; Messner, Paul; Moya, Sergio; Donath, Edwin

2012-01-01

355

Multi-Layer Microbubbles by Microfluidics  

OpenAIRE

Multi-layer microbubble has great potential in enabling the corporation of medical imaging with tumor therapy such as drug and gene delivery of therapeutics or other functional materials in medical applications. Microfluidic technique has advanced over the last decade and showed great promise in replacing traditional microbubble generating method. In this paper, a multi-layer microbubble structure was produced with the aspect as potentially used for drug loaded micro...

Hongbo Zhang; Haosu Meng; Qian Sun; Jianpu Liu; Zhang, W. J.

2013-01-01

356

Recurrent Facial Urticaria Following Herpes Simplex Labialis  

OpenAIRE

We describe recurrent acute right-sided facial urticaria associated with herpes labialis infection in a middle-aged female patient. Antiviral medications and antihistamines not only successfully cleared the herpes infection and urticaria but also prevented further recurrences.

Zawar, Vijay; Godse, Kiran

2012-01-01

357

Recurrence interval analysis of trading volumes  

OpenAIRE

We study the statistical properties of the recurrence intervals $\\tau$ between successive trading volumes exceeding a certain threshold $q$. The recurrence interval analysis is carried out for the 20 liquid Chinese stocks covering a period from January 2000 to May 2009, and two Chinese indices from January 2003 to April 2009. Similar to the recurrence interval distribution of the price returns, the tail of the recurrence interval distribution of the trading volumes follows a...

Ren, Fei; Zhou, Wei-xing

2010-01-01

358

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

359

Giant recurrent retroperitoneal liposarcoma presenting as a recurrent inguinal hernia  

Directory of Open Access Journals (Sweden)

Full Text Available Retroperitoneal liposarcoma presenting as an inguinal hernia is a rare entity. We present the first case of Giant recurrent liposarcoma presenting as a recurrent inguinal hernia in a 40-year-old male. Physical examination showed an irreducible lump in the right inguinal region and a scar in the right lumbar and right inguinal region. Computed tomography (CT scan of abdomen revealed it to be a retro peritoneal mass extending into the right inguinal region along and involving the cord structures. Wide local excision of the tumour with right orchidectomy and inguinal hernioplasty was performed. Histo-pathology confirmed it to be a liposarcoma. Patient received postoperative radio therapy. Follow up of two years has shown him to be disease free. Retroperitoneal liposarcoma can grow along cord structures into the inguinal canal and mimic an irreducible indirect inguinal hernia.

Sameer Vora

2011-09-01

360

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

361

Recurrent infection in the child.  

Science.gov (United States)

In the child with recurrent infection, early recognition of defects in host defenses is critical for appropriate treatment and for patient survival and well-being. Familiarity on the physician's part with the clinical clues of an anatomic or functional defect can save time, money, and patient discomfort. When no such defect is apparent, the problem may be in the child's immunologic system and more specific testing is necessary to identify whether the defect is in cell-mediated immunity or is in the functioning of the phagocytic, complement, or humoral system. Treatments for these problems are available, but their success depends on early diagnosis before recurrent infection and malnutrition result in irreversible tissue damage. PMID:7054773

Regelmann, W E

1982-01-01

362

Pinealitis accompanying equine recurrent uveitis.  

OpenAIRE

There is no direct verification of pineal gland involvement in human uveitis. Specimens of pineal tissue are not available during active uveitis in human patients. Naturally occurring uveitis in horses gives us an opportunity to examine tissues during active ocular inflammation. We examined the pineal gland of a horse that was killed because it had become blind during an episode of uveitis. The clinical history and histopathology of the eyes were consistent with post-leptospiral equine recurr...

Kalsow, C. M.; Dwyer, A. E.; Smith, A. W.; Nifong, T. P.

1993-01-01

363

Multi-layered Social Networks  

CERN Document Server

It is quite obvious that in the real world, more than one kind of relationship can exist between two actors and that those ties can be so intertwined that it is impossible to analyse them separately [Fienberg 85], [Minor 83], [Szell 10]. Social networks with more than one type of relation are not a completely new concept [Wasserman 94] but they were analysed mainly at the small scale, e.g. in [McPherson 01], [Padgett 93], and [Entwisle 07]. Just like in the case of regular single-layered social network there is no widely accepted definition or even common name. At the beginning such networks have been called multiplex network [Haythornthwaite 99], [Monge 03]. The term is derived from communications theory which defines multiplex as combining multiple signals into one in such way that it is possible to separate them if needed [Hamill 06]. Recently, the area of multi-layered social network has started attracting more and more attention in research conducted within different domains [Kazienko 11a], [Szell 10], [...

Bródka, Piotr

2012-01-01

364

Supplemental multilayer insulation research facility  

International Nuclear Information System (INIS)

The Supplemental Multilayer Insulation Research Facility (SMIRF) provides a small scale test bed for conducting cryogenic experiments in a vacuum environment. The facility vacuum system is capable of simulating a Space Shuttle launch pressure profile as well as providing a steady space vacuum environment of 1.3x10-4 N/m2(1 x 10-6 torr). Warm side boundary temperatures can be maintained constant between 111 K(200 R) and 361 K(650 R) using a temperature controlled shroud. The shroud can also simulate a typical lunar day-night temperature profile. The test hardware consists of a cryogenic calorimeter supported by the lid of the vacuum chamber. A 0.45 m3 (120 gal) vacuum jacketed storage/supply tank is available for conditioning the cryogen prior to use in the calorimeter. The facility was initially designed to evaluate the thermal performance of insulation systems for long-term storage in space. The facility has recently been used to evaluate the performance of various new insulation systems for LH2 and LN2 ground storage dewars

365

Recurrence statistics of great earthquakes  

Science.gov (United States)

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 qualitatively and quantitatively as statistics of extreme values and moment analysis yield remarkably similar results.

Ben-Naim, E.; Daub, E. G.; Johnson, P. A.

2013-06-01

366

MRI in recurrent nasopharyngeal carcinoma  

International Nuclear Information System (INIS)

In this study, we retrospectively reviewed the MRI features of recurrent nasopharyngeal carcinoma (NPC) in 72 patients who underwent MRI before and after gadolinium injection. Recurrent NPC exhibited a high degree of regional spread and a variety of signal intensities and contours. MRI showed a nasopharyngeal mass in 50 patients (69.4 %); other sites of involvement included the parapharyngeal space (44.4 %), nasal cavity (12.5 %), paranasal sinuses (27.8 %), oropharynx (4.2 %), orbit (8.3 %), infratemporal fossa (18.1 %), skull base (59.8 %), intracranial area (51.4 %) and regional lymph nodes (15.3 %). On T2-weighted images, the nasopharyngeal mass gave high signal in 9 of 50 cases (18 %), intermediate in 27 (54 %), mixed in 8 (16 %) and low signal in 6 (12 %). Contrast enhancement was strong in 12 cases (24 %), moderate in 29 (58 %) and heterogeneous in 9 (18 %). The lesion was convex in 31 cases (62 %) and concave or straight in 19 (38 %). Recognition of the distribution and the appearance of recurrent NPC on MRI is essential for timely diagnosis and appropriate treatment. (orig.)

367

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

368

Locoregional recurrence after management of carcinoma breast  

International Nuclear Information System (INIS)

Objective: To determine the rate of locoregional recurrence, disease-free interval, site and pattern of locoregional recurrence and the significance of different factors for predicting locoregional recurrence in patients with stage II and III carcinoma breast. Patients and Methods: Criteria for including patients in this study was female patients with stage II and III carcinoma breast who presented in our unit from 1995-2002 and underwent surgical (modified radical mastectomy, simple mastectomy with axillary sampling) and non-surgical (chemotherapy, radiotherapy, hormonal therapy) treatment of carcinoma breast. Record of 98 patients was evaluated for rate of locoregional recurrence, disease-free interval, site and pattern of locoregional recurrence and different clinical factors like stage of carcinoma, tumour size, lymph node status and histopathology were assessed for association with locoregional recurrence. Results: After a mean follow-up of 3.5 years, 17 patients developed locoregional recurrence. Mean disease free interval in stage II was 30 months and only 9.5 months in stage III. Lymph node positivity was associated with locoregional recurrence (p-value is less than 0.05). Chest wall was commonest site of recurrence (73%). Single spot recurrence was common in stage II whereas multiple spot recurrence and field change was more common in stage III. Addition of radiotherapy to surgery decreased the locoregional recurrence but chemotherapy had no significant effec but chemotherapy had no significant effect on prevention of locoregional recurrence. Conclusion: In this series 17.34 % patients developed locoregional recurrence for mean follow-up duration of 3.5 years. Mean disease-free interval was 20.52 months. Lymph node involvement had significant correlation with LRR. (author)

369

Enhancement of magnetoresistance in manganite multilayers  

CERN Document Server

Magnanite multilayers have been fabricated using La0.67Ca0.33MnO3 as the ferromagnetic layer and Pr0.7Ca0.3MnO3 and Nd0.5Ca0.5MnO3 as the spacer layers. All the multilayers were grown on LaAlO3 (100) by pulse laser deposition. An enhanced magnetoresistnace (defined (RH- R0)/R0) of more than 98% is observed in these multilayers. Also a low field magnetoresistance of 41% at 5000 Oe is observed in these multilayer films. The enhanced MR is attributed to the induced double exchange in the spacer layer, which is giving rise to more number of conducting carriers. This is compared by replacing the spacer layer with LaMnO3 where Mn exists only in 3+ state and no enhancement is observed in the La0.67Ca0.33MnO3 / LaMnO3 multilayers as double exchange mechanism can not be induced by external magnetic fields.

Venimadhav, A; Prasad, V; Subramanian, S V

2000-01-01

370

High-resolution X-ray Multilayers  

International Nuclear Information System (INIS)

Two new approaches are taken in multilayer fabrication to help bridge the gap in bandwidth between traditional multilayers (1 to 2%) and perfect crystals (0.01%). The first approach is based on creating many layers of low-contrast Al2O3/ B4C materials. The second approach is based on using multilayer structures with a small d-spacing using traditional W/B4C and Mo/B4C materials. With 8 keV x-rays on the Chess A2 beamline, we measured a bandwidth of 0.27% with a reflectivity of 40% and a Darwin width of 17 arc seconds from a 26 A d-spacing multilayer with 800 bi-layers of Al2O3/B4C using the low-contrast approach. On the other hand, the short period approach with a W/B4C multilayer and a 14.8 A d-spacing showed a resolution of 0.5 % and a reflectivity of 58.5%. Two more Mo/B4C samples with d-spacings of 15 A and 20 A showed energy resolutions of 0.25% and 0.52% with corresponding reflectivities of 39% and 66%. Thus we observe that both methods can produce useful x-ray optical components

371

CT manifestations of recurrent thyroid carcinoma  

International Nuclear Information System (INIS)

Objective: To study the CT manifestations of recurrent thyroid carcinoma, in order to recognize the characteristics of recurrent thyroid carcinoma. Methods: 42 cases of recurrent thyroid carcinoma proved by surgery and pathology were reviewed, including papillary carcinoma (n = 25), follicular carcinoma (n = 9), medullary carcinoma (n = 6) and clear cell carcinoma (n=2). Results: Local recurrence in thyroid bed was found in 23 cases. Invasion of carotid artery (n = 2), trachea and esophagus (n = 17), larynx and hypopharynx (n = 2) was revealed by CT. In 9 cases of follicular carcinoma 8 had local thyroid bed recurrence. All of the 7 cases with contrast administration had enhancement of tumor mass. Recurrence of contralateral lobe was seen in 12 cases, the pathologic types were the same as the primary carcinoma. Cervical lymph node metastases were proved in 31 cases, being the major manifestation of papillary carcinoma (76%). Mediastinal lymph node metastases were found in 7 cases. 75% of patients had more than one type of recurrences. Conclusion: The majority of recurrent thyroid carcinoma were found in cervical lymph node and thyroid bed. Thyroid bed recurrence was most commonly seen in follicular carcinoma while cervical lymph node metastasis were frequent in papillary carcinoma. The adjacent organs or structures was of ten invaded by local recurrent tumor

372

Magnetic properties of Ni/Pt multilayers  

Energy Technology Data Exchange (ETDEWEB)

We have grown Ni/Pt multilayers with Pt buffer layer, by evaporation under UHV conditions on glass substrates maintained at 300 K. The magnetic properties of Ni/Pt multilayers are examined as a function of Ni layer thickness t {sub Ni}. The temperature dependence of the spontaneous magnetization M(T) is well described by a T {sup 3/2} law in all multilayers. A spin-wave theory has been used to explain the temperature dependence of the magnetization and the approximate values for the bulk exchange interaction J {sub b}, surface exchange interaction J {sub S} and the interlayer coupling strength J {sub I} for various Ni layer thicknesses have been obtained.

Benkirane, K. [Laboratoire de Traitement d' information, Faculte des Sciences Ben' Msik Sidi-Othmane, B.P. 7955, Sidi-Othmane, Casablanca (Morocco)]. E-mail: karbenkirane@yahoo.fr; Elkabil, R. [Laboratoire de Traitement d' information, Faculte des Sciences Ben' Msik Sidi-Othmane, B.P. 7955, Sidi-Othmane, Casablanca (Morocco); Lassri, M. [Laboratoire de Physique des Materiaux et de Micro-electronique, Faculte des Sciences Ain Chock, Universite Hassan II, B.P. 5366 Ma-hat arif, Route d' El Jadida, km-8, Casablanca, Marocco (Morocco); Abid, M. [Laboratoire de Physique des Materiaux et de Micro-electronique, Faculte des Sciences Ain Chock, Universite Hassan II, B.P. 5366 Ma-hat arif, Route d' El Jadida, km-8, Casablanca, Marocco (Morocco); Lassri, H. [Laboratoire de Physique des Materiaux et de Micro-electronique, Faculte des Sciences Ain Chock, Universite Hassan II, B.P. 5366 Ma-hat arif, Route d' El Jadida, km-8, Casablanca, Marocco (Morocco); Berrada, A. [Laboratoire de Physique des Materiaux, Faculte des Sciences, Avenue Ibn Batouta, B.P. 1014, Rabat (Morocco); Hamdoun, A. [Laboratoire de Traitement d' information, Faculte des Sciences Ben' Msik Sidi-Othmane, B.P. 7955, Sidi-Othmane, Casablanca (Morocco); Krishnan, R. [Laboratoire de Magnetisme et d' Optique, URA 1531, 45 Avenue des Etats Unis, 78035 Versailles Cedex (France)

2005-01-15

373

Long Range Surface Plasmons in Multilayer Structures  

CERN Document Server

We present a new strategy, based on a Fresnel coefficient pole analysis, for designing an asymmetric multilayer structure that supports long range surface plasmons (LRSP). We find that the electric field intensity in the metal layer of a multilayer LRSP structure can be even slightly smaller than in the metal layer of the corresponding symmetric LRSP structure, minimizing absorption losses and resulting in LRSP propagation lengths up to 2mm. With a view towards biosensing applications, we also present semi-analytic expressions for a standard surface sensing parameter in arbitrary planar resonant structures, and in particular show that for an asymmetric structure consisting of a gold film deposited on a multilayer of SiO2 and TiO2 a surface sensing parameter G = 1.28(1/nm) can be achieved.

Delfan, Aida

2013-01-01

374

Maximum screening fields of superconducting multilayer structures  

CERN Document Server

It is shown that a multilayer comprised of alternating thin superconducting and insulating layers on a thick substrate can fully screen the applied magnetic field exceeding the superheating fields $H_s$ of both the superconducting layers and the substrate, the maximum Meissner field is achieved at an optimum multilayer thickness. For instance, a dirty layer of thickness $\\sim 0.1\\; \\mu$m at the Nb surface could increase $H_s\\simeq 240$ mT of a clean Nb up to $H_s\\simeq 290$ mT. Optimized multilayers of Nb$_3$Sn, NbN, some of the iron pnictides, or alloyed Nb deposited onto the surface of the Nb resonator cavities could potentially double the rf breakdown field, pushing the peak accelerating electric fields above 100 MV/m while protecting the cavity from dendritic thermomagnetic avalanches caused by local penetration of vortices.

Gurevich, Alex

2015-01-01

375

Maximum screening fields of superconducting multilayer structures  

Science.gov (United States)

It is shown that a multilayer comprised of alternating thin superconducting and insulating layers on a thick substrate can fully screen the applied magnetic field exceeding the superheating fields Hs of both the superconducting layers and the substrate, the maximum Meissner field is achieved at an optimum multilayer thickness. For instance, a dirty layer of thickness ˜0.1 ?m at the Nb surface could increase Hs ? 240 mT of a clean Nb up to Hs ? 290 mT. Optimized multilayers of Nb3Sn, NbN, some of the iron pnictides, or alloyed Nb deposited onto the surface of the Nb resonator cavities could potentially double the rf breakdown field, pushing the peak accelerating electric fields above 100 MV/m while protecting the cavity from dendritic thermomagnetic avalanches caused by local penetration of vortices.

Gurevich, Alex

2015-01-01

376

Mechanical behaviour of hard PVD multilayered coatings  

Energy Technology Data Exchange (ETDEWEB)

The aim of this work was to investigate the cracking behaviour and adhesion of tungsten-carbon-based multilayered coatings deposited on steel substrates by magnetron sputtering. Three-point bending experiments were performed on the coating-on-substrate systems until failure of the film. The systems were also strained uniaxially with a microtensile device adapted to a scanning electron microscope. The mechanical response is analysed from the evolution of the crack density in the coating and the fracture toughness. The results show that the rupture properties of the multilayered coatings are correlated to the film thickness and arrangement of the elementary layers. Scratch experiments on the systems revealed a strong adhesion of the multilayered coatings on steel substrates, and delamination at layer interfaces. Thus, graded coatings appear to be more attractive for mechanical applications. (orig.)

Harry, E. [Lyon-1 Univ., Villeurbanne (France). Lab. des Sciences and Ingenierie des Surfaces; Ignat, M.; Pauleau, Y. [ENSEEG, F-38402, Saint Martin d' Heres (France); Rouzaud, A.; Juliet, P. [CEA, F-38054, Grenoble (France)

2000-03-01

377

Palbociclib Isethionate in Treating Younger Patients With Recurrent, Progressive, or Refractory Central Nervous System Tumors  

Science.gov (United States)

Childhood Choroid Plexus Tumor; Childhood Ependymoblastoma; Childhood Grade III Meningioma; Childhood High-grade Cerebellar Astrocytoma; Childhood High-grade Cerebral Astrocytoma; Childhood Medulloepithelioma; Recurrent Childhood Anaplastic Astrocytoma; Recurrent Childhood Anaplastic Oligoastrocytoma; Recurrent Childhood Anaplastic Oligodendroglioma; Recurrent Childhood Brain Stem Glioma; Recurrent Childhood Cerebellar Astrocytoma; Recurrent Childhood Cerebral Astrocytoma; Recurrent Childhood Giant Cell Glioblastoma; Recurrent Childhood Glioblastoma; Recurrent Childhood Gliomatosis Cerebri; Recurrent Childhood Gliosarcoma; Recurrent Childhood Medulloblastoma; Recurrent Childhood Pineoblastoma; Recurrent Childhood Supratentorial Primitive Neuroectodermal Tumor

2014-12-08

378

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

379

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

380

Multilayer graphene under vertical electric field  

OpenAIRE

We study the effect of vertical electric field (E-field) on the electronic properties of multilayer graphene. We show that the effective mass, electron velocity and density-of-state of a bilayer graphene are modified under the E-field. We also study the transformation of the band structure of multilayer graphenes. E-field induces finite (zero) bandgap in the even (odd)-layer ABA-stacking graphene. On the other hand, finite bandgap is induced in all ABC-stacking graphene. We ...

Kumar, S. Bala; Guo, Jing

2011-01-01

381

Synthesis and electrical conductivity of multilayer silicene  

Science.gov (United States)

The epitaxial growth and the electrical resistance of multilayer silicene on the Ag(111) surface has been investigated. We show that the atomic structure of the first silicene layer differs from the next layers and that the adsorption of Si induces the formation of extended silicene terraces surrounded by step bunching. Thanks to the controlled contact formation between the tips of a multiple probe scanning tunneling microscope and these extended terraces, a low sheet resistance, albeit much higher than the electrical resistance of the underlying silver substrate, has been measured, advocating for the electrical viability of multilayer silicene.

Vogt, P.; Capiod, P.; Berthe, M.; Resta, A.; De Padova, P.; Bruhn, T.; Le Lay, G.; Grandidier, B.

2014-01-01

382

Physical and chemical characterization of multilayered structures  

International Nuclear Information System (INIS)

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

383

Measurement of the perfection of nanoscale multilayers.  

Science.gov (United States)

In modern materials science the characterisation of nanostructures is becoming increasingly important. For measurement of the quality of nanoscale multilayer arrangement with high spatial resolution a method is described that is based on the broadening of the spots in the Fourier transformation of transmission electron microscopic images of multilayer cross-sections. Using this method on Si/Ge superlattices with periodic lengths between 4 and 12 nm it could be quantitatively shown that the layer perfection decreases with increasing periodic length. The transition from elastic to plastic deformation between the Si and Ge layers at larger periodic lengths can be the reason for this behaviour. PMID:12802573

Thomas, J; Schumann, J; Kleint, C

2003-07-01

384

Voltage drop at interfaces in multilayer ferroelectrics  

Science.gov (United States)

Based upon a defined surface barrier in ferroelectric multilayers deposited on (100) p-type silicon, ?Va, which bears a portion of the external electrical voltage, a modified empirical power law I=A(?V)n is established for quantitatively describing detailed I-V dependence in ferroelectric multilayers. The voltage drop at the interface, Vi, which directly affects electrical characteristics of ferroelectric multiplayer system, is studied thoroughly. The voltage drop obtained from the modified empirical power law of the I-V dependence is consistent with that obtained from the C-V dependence model.

Li, Xingjiao; Wang, Ningzhang; Bao, Junbo; Chen, Tao; Xu, Jingping; Feng, Hanhua; Li, Shaoping

2003-03-01

385

Radiation therapy of recurrent nasopharyngeal carcinoma  

International Nuclear Information System (INIS)

Recurrent nasopharyngeal carcinoma (NPC), if left untreated, has a 5-year survival of less than one per cent. In contrast, the overall 5-year survival in a treated series of patients was 18 per cent. Excluding those with distant metastases at the beginning of the retreatment, the 5-year survival was 23 per cent. If the recurrence was limited to the neck, a 5-year survival of 34 per cent was obtained and if it was confined to the nasopharynx the 5-year survival was 25 per cent. High doses (about 60 Gy), using multiple narrow beams, carefully directed, were required. For recurrences in the neck, lymph node dissection supplemented by a lower radiation dose should be considered. Surgery was sometimes the only possible method for cure, when recurrence occurred in the neck nodes. Recurrences in the neck, especially when repeatedly appearing, most often were combined with a local recurrence in the nasopharynx. (Auth.)

386

Equine recurrent uveitis: classification, etiology, and pathogenesis.  

Science.gov (United States)

Equine recurrent uveitis is a cyclical disease that affects the eye and often leads to high management costs and unfavorable results, such as blindness. Research has improved understanding of the roles of various etiologies, especially leptospirosis, in initiating and perpetuating the pathogenesis of equine recurrent uveitis. Research has also led to the discovery that specific breeds and horses with specific coat color patterns may be predisposed to developing recurrent uveitis. PMID:21870351

Curling, Amanda

2011-06-01

387

Surgical management of recurrent thyroid cancer  

OpenAIRE

Recurrent thyroid tumors are much less frequent but more aggressive than primary tumors. The aim is to find out their characteristics, aggressiveness and the possibility of radical surgical excision as well as the frequency of complications. Method and material: retrospective study on 69 patients operated for recurrent thyroid tumors. Results: Recurrent tumors were found in 42 patients with papillary, 11 with follicular (8 with Hurthle), 9 with medullary and 7 with anaplastic thyroid tumors. ...

Boži? Vesna; Havelka Marija J.; Tati? Svetislav B.; Kalezi? Nevena K.; Kaži? Milena; Živi? Rastko; Krgovi? Ksenija Lj.; Paunovi? Ivan R.; Živaljevi? Vladan R.; Dikli? Aleksandar ?.

2003-01-01

388

Treatment of local recurrences of rectal carcinoma  

International Nuclear Information System (INIS)

From 1978-1992, 159 patients were treated for local recurrences of rectal carcinoma. They could be subdivided into three groups according to the type of primary treatment given; 82 patients underwent primary surgery without irradiation, 37 patients had preoperative and 40 patients postoperative radiotherapy. The localizations of the recurrences and the curative and palliative potentials of surgery and radiotherapy in the treatment of local recurrences were studied. There was no difference in the localisation of the recurrences in the three groups. Median time between initial surgery and recurrence was also almost the same in the three groups and 75% of the recurrences appeared within 2 years. Twenty percent of the patients in the primary surgery alone group, compared with 49% and 38% in the preoperative and postoperative irradiation groups, respectively, had distant metastases at the time of the diagnosis of local recurrence. The predominant symptom from the local recurrence was pain and, after treatment of the recurrence, pain relief was registered in 63%. In 66%, 16% and 22%, respectively, of the patients in the three groups, the intention of the treatment was curative, with either radiotherapy alone, radiotherapy combined with surgery or surgery alone. The 5-years-survival after recurrence was 6% in the primary surgery alone group and 0% in the other 2 groups. Of the 69 patients treated with a curative intention, 32% were locally symptom-free at death or the last focally symptom-free at death or the last follow-up. Our conclusion is that a local recurrence must be avoided due to the morbidity associated with local failure and the potentially low likelihood of curative treatment of a local recurrence

389

Recurrent Laryngeal Nerve Injury in Thyroid Surgery  

OpenAIRE

AbstractObjectives: Vocal cord paresis or paralysis due to iatrogenic injury of the recurrent laryngeal nerve (RLNI) is one of the main problems in thyroid surgery. Although many procedures have been introduced to prevent the nerve injury, still the incidence of recurrent laryngeal nerve palsy varies between 1.5-14?20The aim of the present study is to assess the risk factors of recurrent laryngeal nerve injury during thyroid surgery.Methods: Patients who had thyroid surgery between 1990 and...

Zakaria, Hazem M.

2011-01-01

390

Chestwall recurrences of breast cancer  

International Nuclear Information System (INIS)

In 35 patients with chestwall recurrences of breast carcinoma, 45 lesions were treated with combined radiation and hyperthermia. The majority of the lesions received 6 fractions of 4 Gy, twice a week during 3 weeks. Hyperthermia was administered within 30 min after irradiation, aiming a tumor temperature of 430C during one hour. The percentage of complete response (CR) was 57%. In small lesions, the percentage of CR was 80%. The mean duration of the response was 7 months. Response rate increased with increasing temperature. Particularly, mean temperature and isoeffect thermal dose correlated very well with response rate. In nine cases, comparative lesions were treated with either radiation alone or radiation combined with hyperthermia. The response rates were 3/9 and 7/9, respectively. Acute skin reactions were enhanced by the combined treatment. However, late skin reactions were not increased. Although the prognosis of patients with chestwall recurrences is determined by the presence of distant metastases, local control remains an important objective. Combined treatment with radiation and hyperthermia offers the possibility of obtaining a high local control rate particularly in relatively small lesions. 36 refs.; 10 tabs

391

Random Recurrent Neural Networks Dynamics  

CERN Document Server

This paper is a review dealing with the study of large size random recurrent neural networks. The connection weights are selected according to a probability law and it is possible to predict the network dynamics at a macroscopic scale using an averaging principle. After a first introductory section, the section 1 reviews the various models from the points of view of the single neuron dynamics and of the global network dynamics. A summary of notations is presented, which is quite helpful for the sequel. In section 2, mean-field dynamics is developed. The probability distribution characterizing global dynamics is computed. In section 3, some applications of mean-field theory to the prediction of chaotic regime for Analog Formal Random Recurrent Neural Networks (AFRRNN) are displayed. The case of AFRRNN with an homogeneous population of neurons is studied in section 4. Then, a two-population model is studied in section 5. The occurrence of a cyclo-stationary chaos is displayed using the results of \\cite{Dauce01}...

Samuelides, M

2006-01-01

392

Recurrent negative pressure pulmonary edema.  

Science.gov (United States)

An African-American man, aged 34 years, underwent an elective uncomplicated right wrist laceration repair while under general anesthesia. Following extubation, the patient developed hypoxemia, tachypnea, shortness of breath, pulmonary rales, frothy sputum, decreased oxygen saturation, and evidence of upper airway obstruction. Chest radiograph showed pulmonary edema. The patient was diagnosed with post-extubation pulmonary edema (aka. negative pressure pulmonary edema [NPPE]) and was treated with intravenous furosemide and oxygen therapy; he improved remarkably within a few hours. Once stabilized, the patient described a similar episode 10 years earlier following surgery for multiple gunshot wounds. Negative pressure pulmonary edema following tracheal extubation is an uncommon (0.1%) and life-threatening complication of patients undergoing endotracheal intubation and general anesthesia for surgical procedures. The common pattern in these cases is the occurrence of an episode of airway obstruction upon emergence from general anesthesia, usually caused by laryngospasm. Patients who are predisposed to airway obstruction may have an increased risk of airway complications upon extubation after general anesthesia. Prevention and early relief of upper airway obstruction should decrease incidence. Recurrent NPPE has not been previously described in the literature. Herein, we describe the first case of recurrent NPPE in the same patient following extubation. PMID:20852091

Pathak, Vikas; Rendon, Iliana S Hurtado; Ciubotaru, Ronald L

2011-06-01

393

Reliable Communications Using Multi-layer Transmission  

Science.gov (United States)

In this paper, we propose a MIMO approach for packet combining in hybrid automatic repeat request (HARQ) protocols using single-carrier multi-layer transmission over block fading channels. Based on this model, the problem of the optimization of the linear superposition coefficients is briefly addressed.

Assimi, Abdel-Nasser; Poulliat, Charly; Fijalkow, Inbar

394

Josephson plasma resonance in superconducting multilayers  

DEFF Research Database (Denmark)

We derive an analytical solution for the josephson plasma resonance of superconducting multilayers. This analytical solution is derived mainly for low T-c systems with magnetic coupling between the superconducting layers, but many features of our results are more general, and thus an application to the recently derived plasma resonance phenomena for high T-c superconductors of the BSCCO type is discussed.

Pedersen, Niels Falsig

1999-01-01

395

Domain structures in Co/Pd multilayers  

OpenAIRE

Domain observations and measurements of mean domain sizes in Co/Pd multilayers with high perpendicular anisotropy are reported and compared with the predictions of the stacked-stripe model of domain structure. The estimated high wall energies are consistent with measured anisotropy. The properties of the model in the thin-layer limit are discussed

Kambersky, V.; Haan, P.; Lodder, J. C.; Simsova, J.; Gemperle, R.

1993-01-01

396

Transmission fingerprints in quasiperiodic magnonic multilayers  

Energy Technology Data Exchange (ETDEWEB)

In this paper we investigated the influence of mirror symmetry on the transmission spectra of quasiperiodic magnonic multilayers arranged according to Fibonacci, Thue-Morse and double period quasiperiodic sequences. We consider that the multilayers composed of two simple cubic Heisenberg ferromagnets with bulk exchange constants J{sub A} and J{sub B} and spin quantum numbers S{sub A} and S{sub B}, respectively. The multilayer structure is surrounded by two semi-infinite slabs of a third Heisenberg ferromagnetic material with exchange constant J{sub C} and spin quantum number S{sub C}. For simplicity, the lattice constant has the same value a in each material, corresponding to epitaxial growth at the interfaces. The transfer matrix treatment was used for the exchange-dominated regime, taking into account the random phase approximation (RPA). Our numerical results illustrate the effects of mirror symmetry on (i) transmission spectra and (ii) transmission fingerprints. - Highlights: > We model quasiperiodic magnetic multilayers presenting mirror symmetry. > We investigated the allowed and forbidden bands of magnonic transmission. > Transmission return maps show the influence of mirror symmetry. > Mirror symmetry has no effect on the Fibonacci case. > Mirror symmetry does have effect on the Thue-Morse and double period cases.

Coelho, I.P. [Departamento de Ensino Superior, Instituto Federal de Educacao, Ciencia e Tecnologia do Maranhao, Imperatriz-MA 65919-050 (Brazil); Departamento de Fisica, Universidade Federal do Rio Grande do Norte, Natal-RN 59072-970 (Brazil); Vasconcelos, M.S. [Escola de Ciencias e Tecnologia, Universidade Federal do Rio Grande do Norte, Natal-RN 59072-970 (Brazil); Bezerra, C.G., E-mail: cbezerra@dfte.ufrn.br [Departamento de Fisica, Universidade Federal do Rio Grande do Norte, Natal-RN 59072-970 (Brazil)

2011-12-15

397

Multilayered image representation: application to image compression.  

Science.gov (United States)

The main contribution of this work is a new paradigm for image representation and image compression. We describe a new multilayered representation technique for images. An image is parsed into a superposition of coherent layers: piecewise smooth regions layer, textures layer, etc. The multilayered decomposition algorithm consists in a cascade of compressions applied successively to the image itself and to the residuals that resulted from the previous compressions. During each iteration of the algorithm, we code the residual part in a lossy way: we only retain the most significant structures of the residual part, which results in a sparse representation. Each layer is encoded independently with a different transform, or basis, at a different bitrate, and the combination of the compressed layers can always be reconstructed in a meaningful way. The strength of the multilayer approach comes from the fact that different sets of basis functions complement each others: some of the basis functions will give reasonable account of the large trend of the data, while others will catch the local transients, or the oscillatory patterns. This multilayered representation has a lot of beautiful applications in image understanding, and image and video coding. We have implemented the algorithm and we have studied its capabilities. PMID:18249728

Meyer, François G; Averbuch, Amir Z; Coifman, Ronald R

2002-01-01

398

Multilayer radio absorbing nanocomposite materials and coatings  

International Nuclear Information System (INIS)

Basic principles for design of multilayer film materials on the base of nanocomposite and chiral layers (NbC, Y2Fe5O12) have been developed. By changing of the structure, number, and order of alternation of the layers, absorption spectra of produced composite materials can be varied in the range of electromagnetic radiation 0.8-14.0 cm

399

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 ncreases 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)

400

Current management options for recurrent adrenocortical carcinoma  

Directory of Open Access Journals (Sweden)

Full Text Available Anthony R Glover,1 Julian C Y Ip,1 Jing Ting Zhao,1 Patsy S H Soon,1,4 Bruce G Robinson,1,3 Stan B Sidhu1,2 1Kolling Institute of Medical Research, Cancer Genetics Laboratory, 2Endocrine Surgical Unit, 3Department of Endocrinology, Royal North Shore Hospital and University of Sydney, St Leonards, 4Department of Surgery, Bankstown Hospital and University of New South Wales, Bankstown, NSW, Australia Abstract: Adrenal cortical carcinoma (ACC is a rare cancer that poses a number of management challenges due to the limited number of effective systemic treatments. Complete surgical resection offers the best chance of long-term survival. However, despite complete resection, ACC is associated with high recurrence rates. This review will discuss the management of recurrent ACC in adults following complete surgical resection. Management should take place in a specialist center and treatment decisions must consider the individual tumor biology of each case of recurrence. Given the fact that ACC commonly recurs, management to prevent recurrence should be considered from initial diagnosis with the use of adjuvant mitotane. Close follow up with clinical examination and imaging is important for early detection of recurrent disease. Locoregional recurrence may be isolated, and repeat surgical resection should be considered along with mitotane. The use of radiotherapy in ACC remains controversial. Systemic recurrence most often involves liver, pulmonary, and bone metastasis and is usually managed with mitotane, with or without combination chemotherapy. There is a limited role for surgical resection in systemic recurrence in selected patients. In all patients with recurrent disease, control of excessive hormone production is an important part of management. Despite intensive management of recurrent ACC, treatment failure is common and the use of clinical trials and novel treatment is an important part of management. Keywords: recurrence, surgery, chemotherapy, mitotane, treatment

Glover AR

2013-06-01

401

Pinealitis accompanying equine recurrent uveitis.  

Science.gov (United States)

There is no direct verification of pineal gland involvement in human uveitis. Specimens of pineal tissue are not available during active uveitis in human patients. Naturally occurring uveitis in horses gives us an opportunity to examine tissues during active ocular inflammation. We examined the pineal gland of a horse that was killed because it had become blind during an episode of uveitis. The clinical history and histopathology of the eyes were consistent with post-leptospiral equine recurrent uveitis. The pineal gland of this horse had significant inflammatory infiltration consisting mainly of lymphocytes with some eosinophils. This observation of pinealitis accompanying equine uveitis supports the animal models of experimental autoimmune uveoretinitis with associated pinealitis and suggests that the pineal gland may be involved in some human uveitides. PMID:8435400

Kalsow, C M; Dwyer, A E; Smith, A W; Nifong, T P

1993-01-01

402

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)

403

[Recurrent obstructive bronchitis in infants].  

Science.gov (United States)

The study comprised 458 infants complaining of recurrent obstructive bronchitis from the clinical, chest X-rays and gastroesophageal reflux investigation view points. Spontaneous radiological reflux was found in 49.1% of the patients, although a history of vomiting was present only in 26.6%. In infants with positive radiological reflux, manometrics showed a shorter gastroesophageal sphincter and with lesser pressures than a group of normal infants. With medical treatment of the reflux, remission of the respiratory symptoms was seen in 63.5% of the patients. In a group of infants treated, control X-rays, and manometrics were practiced at the end of the medical treatment showing significant improvement of pressure and length of the gastroesophageal sphincter. The long-term follow-up in infants showing failure of the medical treatment, bronchial asthma appeared in 56.6%. PMID:572685

Casar, C; Díaz, A; Ceruti, E; Danus, O; Vildosola, C

1979-01-01

404

Local Recurrence After Uveal Melanoma Proton Beam Therapy: Recurrence Types and Prognostic Consequences  

Energy Technology Data Exchange (ETDEWEB)

Purpose: To study the prognosis of the different types of uveal melanoma recurrences treated by proton beam therapy (PBT). Methods and Materials: This retrospective study analyzed 61 cases of uveal melanoma local recurrences on a total of 1102 patients treated by PBT between June 1991 and December 2010. Survival rates have been determined by using Kaplan-Meier curves. Prognostic factors have been evaluated by using log-rank test or Cox model. Results: Our local recurrence rate was 6.1% at 5 years. These recurrences were divided into 25 patients with marginal recurrences, 18 global recurrences, 12 distant recurrences, and 6 extrascleral extensions. Five factors have been identified as statistically significant risk factors of local recurrence in the univariate analysis: large tumoral diameter, small tumoral volume, low ratio of tumoral volume over eyeball volume, iris root involvement, and safety margin inferior to 1 mm. In the local recurrence-free population, the overall survival rate was 68.7% at 10 years and the specific survival rate was 83.6% at 10 years. In the local recurrence population, the overall survival rate was 43.1% at 10 years and the specific survival rate was 55% at 10 years. The multivariate analysis of death risk factors has shown a better prognosis for marginal recurrences. Conclusion: Survival rate of marginal recurrences is superior to that of the other recurrences. The type of recurrence is a clinical prognostic value to take into account. The influence of local recurrence retreatment by proton beam therapy should be evaluated by novel studies.

Caujolle, Jean-Pierre, E-mail: ncaujolle@aol.com [Department of Ophthalmology, Saint Roch Hospital, Nice Teaching Hospital, Nice (France); Paoli, Vincent [Department of Ophthalmology, Saint Roch Hospital, Nice Teaching Hospital, Nice (France); Chamorey, Emmanuel [Department of Radiation Oncology, Protontherapy Center, Centre Antoine Lacassagne, Nice (France); Department of Biostatistics and Epidemiology, Centre Antoine Lacassagne, Nice (France); Maschi, Celia; Baillif, Stéphanie [Department of Ophthalmology, Saint Roch Hospital, Nice Teaching Hospital, Nice (France); Herault, Joël [Department of Radiation Oncology, Protontherapy Center, Centre Antoine Lacassagne, Nice (France); Gastaud, Pierre [Department of Ophthalmology, Saint Roch Hospital, Nice Teaching Hospital, Nice (France); Hannoun-Levi, Jean Michel [Department of Radiation Oncology, Protontherapy Center, Centre Antoine Lacassagne, Nice (France)

2013-04-01

405

Recurrent respiratory papillomatosis: a review.  

Science.gov (United States)

Recurrent respiratory papillomatosis (RRP), which is caused by human papillomavirus types 6 and 11, is the most common benign neoplasm of the larynx among children and the second most frequent cause of childhood hoarseness. After changes in voice, stridor is the second most common symptom, first inspiratory and then biphasic. Less common presenting symptoms include chronic cough, recurrent pneumonia, failure to thrive, dyspnea, dysphagia, or acute respiratory distress, especially in infants with an upper respiratory tract infection. Differential diagnoses include asthma, croup, allergies, vocal nodules, or bronchitis. Reports estimate the incidence of RRP in the United States at 4.3 per 100,000 children and 1.8 per 100,000 adults. Infection in children has been associated with vertical transmission during vaginal delivery from an infected mother. Younger age at diagnosis is associated with more aggressive disease and the need for more frequent surgical procedures to decrease the airway burden. When surgical therapy is needed more frequently than four times in 12 months or there is evidence of RRP outside the larynx, adjuvant medical therapy should be considered. Adjuvant therapies that have been investigated include dietary supplements, control of extra-esophageal reflux disease, potent antiviral and chemotherapeutic agents, and photodynamic therapies; although several have shown promise, none to date has "cured" RRP, and some may have serious side effects. Because RRP, although histologically benign, is so difficult to control and can cause severe morbidity and death, better therapies are needed. The potential for a quadrivalent human papilloma vaccine is being explored to reduce the incidence of this disease. PMID:18496162

Derkay, Craig S; Wiatrak, Brian

2008-07-01

406

Recurrence of Kikuchi's lymphadenitis after 12 years  

OpenAIRE

A 40 year old woman developed recurrent Kikuchi's disease 12 years after the original episode. The recurrence affected the same site (axilla) and occurred after the longest delay so far recorded in a European resident. Care must be taken to avoid misdiagnosis of Kikuchi's disease as lymphoma.

Blewitt, R.; Kumar, S.; Abraham, J.

2000-01-01

407

Recurrent Salmonella enteritidis sepsis and hepatic tuberculosis.  

OpenAIRE

A 33 year old woman with recurrent Salmonella enteritidis sepsis is described. Penicillins, ceftriaxone, ciprofloxacin, and chloramphenicol could not eradicate the salmonellas but a combination of high dose ciprofloxacin and ceftriaxone for the eighth episode successfully cured the infection. The combination of ciprofloxacin and ceftriaxone may be a valuable therapeutic regimen in patients with recurrent salmonella sepsis. Prolonged intrahepatic cholestasis resulting from granulomatous hepati...

Trauner, M.; Grasmug, E.; Stauber, R. E.; Hammer, H. F.; Hoefler, G.; Reisinger, E. C.

1995-01-01

408

Androgen deprivation therapy prevents bladder cancer recurrence.  

Science.gov (United States)

Although accumulating preclinical evidence indicates the involvement of androgen receptor signals in bladder cancer (BC) development, its clinical relevance remains unclear. We aimed to evaluate the predictive role of androgen deprivation therapy (ADT) in BC recurrence in prostate cancer (PC) patients. We retrospectively reviewed 20,328 patients with PC diagnosed during 1991-2013 and identified 239 (1.2%) men having primary BC. After excluding ineligible patients, 162 patients made up a final cohort. With a median follow-up of 62 months, 38 (50%) of 76 control patients without ADT experienced BC recurrence, while 19 (22%) of 86 did in ADT group. Thus, patients having received ADT for their PC showed a significantly lower risk of BC recurrence (5-year actuarial recurrence-free survival: 76% v 40%; P < 0.001) and also had a significantly smaller number of recurrence episodes (5-year cumulative recurrence: 0.44 v 1.54; P < 0.001), compared to the control patients. A multivariable analysis revealed ADT as an independent prognosticator (hazard ratio, 0.29; 95% confidence interval, 0.17-0.49) for BC recurrence. This is the first clinical study showing that ADT significantly reduces the risk of BC recurrence. PMID:25557268

Izumi, Koji; Taguri, Masataka; Miyamoto, Hiroshi; Hara, Yoshinori; Kishida, Takeshi; Chiba, Kimio; Murai, Tetsuo; Hirai, Kotaro; Suzuki, Kotaro; Fujinami, Kiyoshi; Ueki, Teiichiro; Udagawa, Koichi; Kitami, Kazuo; Moriyama, Masatoshi; Miyoshi, Yasuhide; Tsuchiya, Futoshi; Ikeda, Ichiro; Kobayashi, Kazuki; Sato, Maho; Morita, Satoshi; Noguchi, Kazumi; Uemura, Hiroji

2014-12-30

409

Endoscopic Therapy for Chronic Recurrent Pancreatitis  

OpenAIRE

Chronic recurrent pancreatitis develops as a result of pancreaticoutflow disturbance associated with pancreatic duct stenosis orpancreatic stones in most cases. Therefore it is rational to reduceintrapancreatic ductal pressure by removing pancreatic outflowdisturbance for treatment of chronic recurrent pancreatitis. Surgicalprocedures and endoscopic pancreatic stenting are available fordecompression of the pancreatic duct. As endoscopic pancreaticstenting is less invasive, safe and effective ...

Yoshiaki Kawaguchi; Tetsuya Mine

2012-01-01

410

Alternative therapy for recurrent Hodgkin's disease  

International Nuclear Information System (INIS)

Eleven patients with recurrent Hodgkin's disease have returned to apparent normality after simple treatment regimes with radiotherapy and hyperthermia from 434 MHz electromagnetic radiation. None have experienced any complication or sequelae from this treatment. All the patients with recurrent active Hodgkin's disease who attended the author's practice since February 1976 have been treated with this combined treatment and are reported here. (author)

411

MRCP findings in recurrent pyogenic cholangitis  

International Nuclear Information System (INIS)

Objective: In this essay, we present the spectrum of intrahepatic and extrahepatic bile duct abnormalities seen on MRCP in patients with recurrent pyogenic cholangitis. Conclusion: MRCP is a promising, noninvasive alternative to more invasive direct cholangiography for evaluating the intrahepatic and extrahepatic bile ducts in patients with recurrent pyogenic cholangitis

412

MRCP findings in recurrent pyogenic cholangitis  

Energy Technology Data Exchange (ETDEWEB)

Objective: In this essay, we present the spectrum of intrahepatic and extrahepatic bile duct abnormalities seen on MRCP in patients with recurrent pyogenic cholangitis. Conclusion: MRCP is a promising, noninvasive alternative to more invasive direct cholangiography for evaluating the intrahepatic and extrahepatic bile ducts in patients with recurrent pyogenic cholangitis.

Jain, Manoj [Department of Radiology, AMRI Hospitals, Salt Lake, JC-16 and 17 Salt Lake City, Kolkata 700091 (India)], E-mail: jainmanoj70@hotmail.com; Agarwal, Ajay [Department of Radiology, AMRI Hospitals, Salt Lake, JC-16 and 17 Salt Lake City, Kolkata 700091 (India)], E-mail: doctorajay2002@yahoo.co.in

2008-04-15

413

Recurrent Multifocal Primary Amyloidosis of Urinary Bladder  

OpenAIRE

Primary localized amyloidosis of bladder is rare. We report a case of recurrence of multifocal primary amyloidosis of urinary bladder. Cystoscopy revealed a diffuse left lateral wall lesion with normal surrounding mucosa. Histopathological examination of the specimen revealed urinary bladder amyloidosis with negative surgical margins. Recurrent urinary bladder amyloidosis was confirmed 3 months after the first resection. Close follow-up is recommended.

Patel S; Trivedi A; Dholaria P; Dholakia M; Devra A; Gupta B; Shah S

2008-01-01

414

Interline power flow controller (IPFC) based damping recurrent neural network controllers for enhancing stability  

International Nuclear Information System (INIS)

Highlights: ? A method is presented to improve power system stability using IPFC. ? Recurrent neural network controllers damp oscillations in a power system. ? Training is based on back propagation with adaptive training parameters. ? Selection of effectiveness damping control signal carried out using SVD method. -- Abstract: This paper presents a method to improve power system stability using IPFC based damping online learning recurrent neural network controllers for damping oscillations in a power system. Parameters of equipped controllers for enhancing dynamical stability at the IPFC are tuned using mathematical methods. Therefore these control parameters are often fixed and are set for particular system configurations or operating points. Multilayer recurrent neural network, which can be tuned for changing system conditions, is used in this paper for effectively damp the oscillations. Training is based on back propagation with adaptive training parameters. This controller is tested to variations in system loading and fault in the power system and its performance is compared with performance of a controller that the phase compensation method is used to set its parameters. Selection of effectiveness damping control signal for the design of robust IPFC damping controller carried out through singular value decomposition (SVD) method. Simulation studies show the superior robustness and stabilizing effect of the proposed controller in comparison with phase compeler in comparison with phase compensation method.

415

Alisertib in Treating Young Patients With Recurrent or Refractory Solid Tumors or Leukemia  

Science.gov (United States)

Childhood Hepatoblastoma; Previously Treated Childhood Rhabdomyosarcoma; Recurrent Childhood Acute Lymphoblastic Leukemia; Recurrent Childhood Acute Myeloid Leukemia; Recurrent Childhood Malignant Germ Cell Tumor; Recurrent Childhood Rhabdomyosarcoma; Recurrent Childhood Soft Tissue Sarcoma; Recurrent Ewing Sarcoma/Peripheral Primitive Neuroectodermal Tumor; Recurrent Neuroblastoma; Recurrent Osteosarcoma; Recurrent Wilms Tumor and Other Childhood Kidney Tumors

2014-03-17

416

Endoscopic Therapy for Chronic Recurrent Pancreatitis  

Directory of Open Access Journals (Sweden)

Full Text Available Chronic recurrent pancreatitis develops as a result of pancreaticoutflow disturbance associated with pancreatic duct stenosis orpancreatic stones in most cases. Therefore it is rational to reduceintrapancreatic ductal pressure by removing pancreatic outflowdisturbance for treatment of chronic recurrent pancreatitis. Surgicalprocedures and endoscopic pancreatic stenting are available fordecompression of the pancreatic duct. As endoscopic pancreaticstenting is less invasive, safe and effective method, this approachhas spread rapidly. Comorbid pancreatic cancer should never beoverlooked before stenting for chronic recurrent pancreatitis, becausechronic recurrent pancreatitis carries a high risk of progressingto pancreatic cancer. In cases with a stone in the pancreatic duct,extracorporeal shock wave lithotripsy (ESWL should be performedin combination with endoscopic pancreatic stenting. In this reviewwe discuss the current status of endoscopic pancreatic stenting in thetreatment of chronic recurrent pancreatitis.

Yoshiaki Kawaguchi

2012-12-01

417

[Prevention of recurrence after successful gallstone dissolution].  

Science.gov (United States)

Gallstone recurrence is a major problem in the medical treatment of gallstones (treatment with UDCA/CDCA, ESWL, local MTBE lysis). The probability of gallstone recurrence is higher in subjects with multiple stones before dissolution treatment and in older subjects (greater than 50 years). The present knowledge on factors predictive of gallstone recurrence and the results of clinical trials for preventing recurrence are given. The different effects of diet and drugs on cholesterol saturation of bile, on nucleation of bile, on mucus production of gallbladder and on gallbladder contractility are discussed and recommendations for a rational approach for prevention of gallstone recurrence are given. Preventable risk factors for gallstone disease have to be eliminated. In general, continuous post-dissolution treatment seems not justified. Regular follow-up ultrasound examinations should be started to detect renewed of gallstones at an early stage. PMID:1926965

Leiss, O; von Bergmann, K

1991-06-01

418

MR imaging characteristics of recurrent thyroid tumors  

International Nuclear Information System (INIS)

MR imaging was used to evaluate 32 patients after partial or total thyroidectomy. Surgical (n = 25) or clinical (n = 7) follow-up was done. Of 23 patients with primary thyroid carcinomas, MR imaging disclosed recurrence in 15 and no recurrence in eight. There were two false-positive diagnoses and one false-negative diagnosis. Nine patients who had undergone surgery for benign disease were studied to assess the appearance of the thyroid bed after thyroidectomy. Local recurrence of carcinoma was characterized by low to medium signal intensity on T1-weighted images and medium to high signal intensity on T2-weighted images. Scar tissue has low intensity. Coronal and sagittal images provided definition of local and mediastinal extension and metastasis. Thus, MR imaging can be used to evaluate recurrence of thyroid tumors and to differentiate recurrence from postoperative fibrosis

419

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.

420

MDX-010 in Treating Patients With Recurrent or Refractory Lymphoma  

Science.gov (United States)

Adult Grade III Lymphomatoid Granulomatosis; B-cell Chronic Lymphocytic Leukemia; Cutaneous B-cell Non-Hodgkin Lymphoma; Extranodal Marginal Zone B-cell Lymphoma of Mucosa-associated Lymphoid Tissue; Intraocular Lymphoma; Nodal Marginal Zone B-cell Lymphoma; Recurrent Adult Burkitt Lymphoma; Recurrent Adult Diffuse Large Cell Lymphoma; Recurrent Adult Diffuse Mixed Cell Lymphoma; Recurrent Adult Diffuse Small Cleaved Cell Lymphoma; Recurrent Adult Grade III Lymphomatoid Granulomatosis; Recurrent Adult Hodgkin Lymphoma; Recurrent Adult Immunoblastic Large Cell Lymphoma; Recurrent Adult Lymphoblastic Lymphoma; Recurrent Grade 1 Follicular Lymphoma; Recurrent Grade 2 Follicular Lymphoma; Recurrent Mantle Cell Lymphoma; Recurrent Marginal Zone Lymphoma; Refractory Hairy Cell Leukemia; Small Intestine Lymphoma; Splenic Marginal Zone Lymphoma; Testicular Lymphoma; Waldenström Macroglobulinemia

2014-05-22

421

Recurrent solutions of neutral differential-difference systems  

OpenAIRE

Results of Bohr-Neugebauer type are obtained for recurrent functions : If $y$ is a bounded uniformly continuous solution of a linear neutral difference-differential system with recurrent right-hand side, then $y$ is recurrent if $c_0 \

Basit, Bolis; Gu?nzler, Hans

2012-01-01

422

Eigenfunctional representation of dyadic Green's functions in multilayered gyrotropic chiral media  

Energy Technology Data Exchange (ETDEWEB)

Studying electromagnetic waves in complex media has been an important research topic due to its useful applications and scientific significance of its physical performance. Dyadic Green's functions (DGFs), as a mathematical kernel or a dielectric medium response, have long been a valuable tool in solving both source-free and source-incorporated electromagnetic boundary value problems for electromagnetic scattering, radiation and propagation phenomena. A complete eigenfunctional expansion of the dyadic Green's functions for an unbounded and a planar, arbitrary multilayered gyrotropic chiral media is formulated in terms of the vector wavefunctions. After a general representation of Green's dyadics is obtained, the scattering coefficients of Green's dyadics are determined from the boundary conditions at each interface and are expressed in a greatly compact form of recurrence matrices. In the formulation of Green's dyadics and their scattering coefficients, three cases are considered, i.e. the current source is immersed in (1) the first, (2) the intermediate, and (3) the last regions, respectively. Although the dyadic Green's functions for an unbounded gyroelectric medium has been reported in the literature, we here present not only unbounded but also multilayered DGFs for the gyrotropic chiral media. The explicit representation of the DGFs after reduction to the gyroelectric or isotropic case agrees well with those existing corresponding results.

Qiu, C-W [Department of Electrical and Computer Engineering, National University of Singapore, Kent Ridge, Singapore 117576, Singapore (Singapore); Yao, H-Y [Department of Electrical and Computer Engineering, National University of Singapore, Kent Ridge, Singapore 117576, Singapore (Singapore); Li, L-W [Department of Electrical and Computer Engineering, National University of Singapore, Kent Ridge, Singapore 117576, Singapore (Singapore); Zouhdi, Said [Lab de Genie Electrique de Paris, CNRS, Ecole Superieure d' Electricite, Plateau de Moulon 91192, Gif-sur-Yvette Cedex (France); Yeo, T-S [Department of Electrical and Computer Engineering, National University of Singapore, Kent Ridge, Singapore 117576, Singapore (Singapore)

2007-05-25

423

EUV Ellipsometry on Mo/Si Multilayers  

International Nuclear Information System (INIS)

We investigate polarisation properties of a reflective Mo/Si multilayer system in the EUV range using polarized synchrotron radiation at BESSY-II. The characterization involves reflectivity measurements with s- and p-polarized light as a function of the wavelength for three different angles near normal incidence. The phase retardance is determined near normal incidence for one fixed angle of incidence as a function of the wavelength. As an additional spin-off of the polarimetry measurement the Stokes parameters of the beamline could be determined. With the 8-axis UHV-polarimeter we have measured the complex reflection coefficients for the first time and establish this ellipsometry technique as an additional sensitive probe to characterize and model multilayer optical elements.

424

Exchange interactions in Fe/Y multilayers  

Energy Technology Data Exchange (ETDEWEB)

The magnetization of Fe/Y multilayers has been measured as a function of temperature. A bulk-like T {sup 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 {sub 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 {sub b}, surface exchange interaction J {sub s} and the interlayer exchange interaction J {sub I} for various Fe layer thicknesses have been obtained.

Elkabil, R. [Laboratoire de traitement d' information, Faculte des Sciences Ben' Msik Sidi-Othmane, Casablanca (Morocco)]. E-mail: relkabil@yahoo.fr; Elkaidi, I. [Laboratoire de Physique des Materiaux et de Micro-electronique, Faculte des Sciences Ain Chock, Universite Hassan II, B.P. 5366 Ma-hat arif, Route d' El Jadida, Km-8, Casablanca (Morocco): UFR, Automatique et Informatique Industriel, Faculte des Sciences Ain Chock, Universite Hassan II, B.P. 5366 Ma-hat arif, Route d' El Jadida, Km-8, Casablanca (Morocco); Annouar, F. [Laboratoire de Physique des Materiaux et de Micro-electronique, Faculte des Sciences Ain Chock, Universite Hassan II, B.P. 5366 Maarif, Route d' El Jadida, Km-8, Casablanca (Morocco); Lassri, H. [Laboratoire de Physique des Materiaux et de Micro-electronique, Faculte des Sciences Ain Chock, Universite Hassan II, B.P. 5366 Ma-hat arif, Route d' El Jadida, Km-8, Casablanca (Morocco); Hamdoun, A. [Laboratoire de traitement d' information, Faculte des Sciences Ben' Msik Sidi-Othmane, Casablanca (Morocco); Bensassi, B. [UFR, Automatique et Informatique Industriel, Faculte des Sciences Ain Chock, Universite Hassan II, B.P. 5366 Ma-hat arif, Route d' El Jadida, Km-8, Casablanca (Morocco); Berrada, A. [Laboratoire de Physique des Materiaux, Faculte des Sciences Universite Mohammed V, B.P. 1014 Rabat (Morocco); Krishnan, R. [Laboratoire de Magnetisme et d' Optique, URA 1531, 45 Avenue des Etats Unis, 78035 Versailles Cedex (France)

2005-05-17

425

Magnetic studies in Fe/Zn multilayers  

International Nuclear Information System (INIS)

The structural and magnetic properties of Fe/Zn films prepared by thermal evaporation have been studied by means of X-ray diffraction, vibrating-sample magnetometry and ferromagnetic resonance (FMR). For Fe layer thickness smaller than 20 A the saturation magnetization decreases with decreasing Fe thickness, which is an indication of the island growth of Zn and Fe-Zn interdiffusion at the layer interfaces. The effective field magnetization 4?Meff of the Fe/Zn multilayers was determined from the FMR data in a rotating external magnetic field. The interface anisotropy constant of the Fe/Zn multilayers, KS, is found to be 1.0 erg/cm2 at 300 K. This indicates the presence of a large perpendicular interface anisotropy and this may suggest that the largest part of KS originates from lattice misfit strain

426

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

427

Optics in magnetic multilayers and nanostructures  

CERN Document Server

In the continuing push toward optical computing, the focus remains on finding and developing the right materials. Characterizing materials, understanding the behavior of light in these materials, and being able to control the light are key players in the search for suitable optical materials. Optics in Magnetic Multilayers and Nanostructures presents an accessible introduction to optics in anisotropic magnetic media.While most of the literature presents only final results of the complicated formulae for the optics in anisotropic media, this book provides detailed explanations and full step-by-step derivations that offer insight into the procedure and reveal any approximations. Based on more than three decades of experimental research on the subject, the author explains the basic concepts of magnetooptics; nonreciprocal wave propagation; the simultaneous effect of crystalline symmetry and arbitrarily oriented magnetization on the form of permittivity tensors; spectral dependence of permittivity; multilayers at...

Visnovsky, Stefan

2006-01-01

428

Optical model for multilayer glazing systems  

International Nuclear Information System (INIS)

In the design phase of a glazing system, multiple laminated glass configurations may be conceived for various architectural purposes (mainly related to aesthetical issues, energy efficiency, safety and security and/or acoustic insulation). Therefore, the availability of computational simulations of optical and thermal properties of laminated glass as a function of the properties of its constituents (glass panes, polymeric films, selective coatings) may be of great utility. Standardised procedures for this kind of calculations are still being prepared by CEN (European Committee for Standardization). The theoretical study of laminated glass with internal selective coatings is especially relevant due to the introduction of reflectivity within the multilayer optical system. Here, a theoretical model based on transfer matrix method and applied to multilayer glazing with external and internal coatings is presented. Simulation results are compared with UV-VIS-NIR spectrophotometric measurements. (Author)

429

Mo-C Multilayered CVD Coatings  

Directory of Open Access Journals (Sweden)

Full Text Available Production processes of multi-layered Mo-C coatings by the method of chemical vapor deposition (CVD with the use of organometallic compounds were developed. Coatings are applied on technical purpose steel DIN 1.2379 (H12F1 and DIN 1.7709 (25H2MF (ÉI10 heat-treated ball with the high class of surface roughness (> 10. The average deposition rate was 50 ?m / h. The optimal conditions of deposition coatings for different technological schemas were defined. Metallographic investigations of the obtained coatings were carried out. Tribological studies of the friction and wear characteristics of sliding friction in conditions of boundary lubrication of Ï-S multilayered CVD coatings shows, that coatings have low friction coefficients (0075-0095 at loads up to 2.0 kN, showed high resistance to wear and are effective in increasing the stability of the pair for precision friction pairs of hydraulical units.

A. Sagalovych

2013-12-01

430

Solar absorption behaviour of multilayer stacks  

Energy Technology Data Exchange (ETDEWEB)

The absorption spectra of multilayer structures have been obtained and analyzed in the wavelength range 0.5-10 ..mu..m. The multilayer system is an SMS type in which M is a thin metallic layer sandwiched between two semiconducting layers. The systems (i) B.S./Cu/B.S. and (ii) Cu/sub 2/S/Cu/Cu/sub 2/S (where B.S. = black sulphide) are developed by the methods of electrodeposition/chemical dipping, whereas the ZnS/Cu/ZnS system is fabricated in vacuo. The ..cap alpha../epsilon ratios are also calculated using the experimentally observed absorption spectra, and found to be higher in the case of the ZnS/Cu/ZnS system, in comparison to the other two systems. The absorption spectra have also been calculated using our theoretical model of the above-mentioned systems.

Chandra, A.; Mishra, M.

1985-01-01

431

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)

432

Deconvolution of mixed magnetism in multilayer graphene  

Energy Technology Data Exchange (ETDEWEB)

Magnetic properties of graphite modified at the edges by KCl and exfoliated graphite in the form of twisted multilayered graphene (<4 layers) are analyzed to understand the evolution of magnetic behavior in the absence of any magnetic impurities. The mixed magnetism in multilayer graphene is deconvoluted using Low field-high field hysteresis loops at different temperatures. In addition to temperature and the applied magnetic field, the density of edge state spins and the interaction between them decides the nature of the magnetic state. By virtue of magnetometry and electron spin resonance studies, we demonstrate that ferromagnetism is intrinsic and is due to the interactions among various paramagnetic centers. The strength of these magnetic correlations can be controlled by modifying the structure.

Swain, Akshaya Kumar [IITB-Monash Research Academy, Department of Metallurgical Engineering and Materials Science, IIT Bombay, Mumbai 400076 (India); Bahadur, Dhirendra, E-mail: dhirenb@iitb.ac.in [Department of Metallurgical Engineering and Materials Science, IIT Bombay, Mumbai 400076 (India)

2014-06-16

433

Interlayer coupling in rotationally faulted multilayer graphenes  

Science.gov (United States)

This paper reviews progress in the theoretical modelling of the electronic structure of rotationally faulted multilayer graphenes. In these systems the crystallographic axes of neighbouring layers are misaligned so that the layer stacking does not occur in the Bernal structure observed in three-dimensional graphite and frequently found in exfoliated bilayer graphene. Notably, rotationally faulted graphenes are commonly found in other forms of multilayer graphene including epitaxial graphenes thermally grown on SiC (0\\,0\\,0\\,\\bar 1) , graphenes grown by chemical vapour deposition, folded mechanically exfoliated graphenes, and graphene flakes deposited on graphite. Rotational faults are experimentally associated with a strong reduction of the energy scale for coherent single particle interlayer motion. The microscopic basis for this reduction and its consequences have attracted significant theoretical attention from several groups that are highlighted in this review.

Mele, E. J.

2012-04-01

434

Deconvolution of mixed magnetism in multilayer graphene  

International Nuclear Information System (INIS)

Magnetic properties of graphite modified at the edges by KCl and exfoliated graphite in the form of twisted multilayered graphene (<4 layers) are analyzed to understand the evolution of magnetic behavior in the absence of any magnetic impurities. The mixed magnetism in multilayer graphene is deconvoluted using Low field-high field hysteresis loops at different temperatures. In addition to temperature and the applied magnetic field, the density of edge state spins and the interaction between them decides the nature of the magnetic state. By virtue of magnetometry and electron spin resonance studies, we demonstrate that ferromagnetism is intrinsic and is due to the interactions among various paramagnetic centers. The strength of these magnetic correlations can be controlled by modifying the structure.

435

Multilayered (Hg,Cd)Te infrared detector  

Science.gov (United States)

Multilayered mercury-cadmium telluride photoconductive detectors were developed which are capable of providing individual coverage of three separate spectral wavelength bands without the use of beam splitters. The multilayered "three-color" detector on a single dewar takes the place of three separate detector/filter/dewar units and enables simpler and more reliable mechanical and optical designs for multispectral scanners and radiometers. Wavelength channel design goals (in micrometers) were: 10.1 to 11.0, 11.0 to 12.0, and 13.0. Detectivity for all channels was 1 x 10 to the 10th power cm-Hz 1/2/Watt. A problem occurred in finding an epoxy layer which had good infrared transmission properties and which also was chemically and mechanically compatible with HgCdTe processing techniques. Data on 6 candidate bonding materials are surveyed and discussed.

Rae, W. G.

1977-01-01

436

Thermodynamic properties of a multilayer classical ferromagnet  

International Nuclear Information System (INIS)

Full text: The 2-dimensional Heisenberg ferromagnet has no finite-temperature phase transition. However, the 3-dimensional system is believed to have a conventional 2nd order phase transition with power law singularities. The specific heat exponent ? is negative (? ? -0.12), signifying a cusp at the transition temperature rather than a divergence. An interesting question is to study the development of this transition in multilayer system where the number of layers n is varied. This is sure to be pertinent to real multilayer systems produced by MBE growth. We have studied such systems via extensive Monte Carlo simulations. We consider system of classical spins localised on the sites of a simple cubic lattice and coupled by nearest-neighbour ferromagnetic interaction. In particular we measure the position and height of the specific heat peak for various number of layers n. An empirical scaling relation is obtained

437

Multi-layer weighted social network model  

CERN Document Server

Recent empirical studies using large-scale datasets have validated the Granovetter hypothesis on the structure of the society in that there are strongly wired communities connected by weak ties. However, as interaction between individuals takes place in diverse contexts, these communities turn out to be overlapping. This implies that the society has a multi-layered structure, where the layers represent the different contexts. To model this structure we begin with a single-layer weighted social network (WSN) model showing the Granovetterian structure. We find that when merging such WSN models, sufficient amount of inter-layer correlation is needed to maintain the relationship between topology and link weights but these correlations destroy the enhancement in the community overlap due to multiple layers. To resolve this, we devise a geographic multi-layer WSN model, where the indirect inter-layer correlations due to the geographic constraints of individuals enhance the overlaps between the communities and, at t...

Murase, Yohsuke; Jo, Hang-Hyun; Kaski, Kimmo; Kertész, János

2014-01-01

438

The structure and dynamics of multilayer networks  

Science.gov (United States)

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 the network affects processes and dynamics.

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

2014-11-01

439

Partial laryngeal surgery in recurrent carcinoma.  

Science.gov (United States)

Abstract With the growing acceptance of nonsurgical therapies for laryngeal squamous cell carcinomas (LSCCs), it has become important to delineate surgical salvage strategies for disease recurrences. Total laryngectomy is often recommended, but appropriately selected laryngeal recurrences may be treated successfully with partial laryngeal surgery: laryngeal function can be preserved with oncological efficacy. The main available studies dealing with partial laryngeal surgery in recurrent carcinoma were critically reviewed. The most appealing feature of salvage transoral laser surgery (TLS) is the opportunity to make tumor-tailored excisions without any reconstructive limitations and retaining the option to switch to open partial laryngectomy. A recent detailed review of 11 series found a pooled local control rate of 57% after a first TLS procedure. Supracricoid laryngectomy (SCL) seems to achieve good local control rates in selected cases of recurrent supraglottic-glottic carcinoma: one review considering seven series calculated that 85% of the patients treated with salvage SCL after radiotherapy experienced no local recurrence; and total laryngectomy after failure of salvage SCL afforded an overall local control rate of 65%. Neck dissection is mandatory in all cases of local LSCC recurrence with evidence of neck metastases, and routine elective neck dissection is recommended for recurrent supraglottic and transglottic cancers. PMID:25539063

Marioni, Gino; Marchese-Ragona, Rosario; Kleinsasser, Norbert H; Lionello, Marco; Lawson, Georges; Hagen, Rudolf; Staffieri, Alberto

2015-02-01

440

Inguinal hernia recurrence: Classification and approach  

Directory of Open Access Journals (Sweden)

Full Text Available The authors reviewed the records of 2,468 operations of groin hernia in 2,350 patients, including 277 recurrent hernias updated to January 2005. The data obtained - evaluating technique, results and complications - were used to propose a simple anatomo-clinical classification into three types which could be used to plan the surgical strategy:Type R1: first recurrence ?high,? oblique external, reducible hernia with small (< 2 cm defect in non-obese patients, after pure tissue or mesh repairType R2: first recurrence ?low,? direct, reducible hernia with small (< 2 cm defect in non-obese patients, after pure tissue or mesh repairType R3: all the other recurrences - including femoral recurrences; recurrent groin hernia with big defect (inguinal eventration; multirecurrent hernias; nonreducible, linked with a controlateral primitive or recurrent hernia; and situations compromised from aggravating factors (for example obesity or anyway not easily included in R1 or R2, after pure tissue or mesh repair.

Campanelli Giampiero

2006-01-01

441

Perceptron Learning of SAT  

OpenAIRE

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

442

Characterization of novel gold SERS substrates with multilayer enhancements  

Science.gov (United States)

A detailed study of SERS enhancements from novel multilayer gold film over nanoparticle (GFON) substrates is presented. These multilayer GFON substrates were optimized in terms of the number of metal layers, and the amounts of gold and silver oxide deposited. These multilayer GFON substrates were also structurally characterized in terms of surface roughness. No significant changes in the surface roughness of these multilayer GFON substrates, even with different layers of gold, have been observed, suggesting there is no direct correlation between the multilayer SERS enhancements and the surface roughness. UV-Vis reflectance spectra of these substrates were also characterized, indicating that the significant multilayer enhancements require the presence of silver oxide layers separating the continuous gold film layers.

Li, Honggang; Baum, Caitlin E.; Cullum, Brian M.

2006-10-01

443

Supervised Learning in Multilayer Spiking Neural Networks  

OpenAIRE

The current article introduces a supervised learning algorithm for multilayer spiking neural networks. The algorithm presented here overcomes some limitations of existing learning algorithms as it can be applied to neurons firing multiple spikes and it can in principle be applied to any linearisable neuron model. The algorithm is applied successfully to various benchmarks, such as the XOR problem and the Iris data set, as well as complex classifications problems. The simulat...

Sporea, Ioana; Gru?ning, Andre?

2012-01-01

444

Initialization of multilayer forecasting artifical neural networks  

OpenAIRE

In this paper, a new method was developed for initialising artificial neural networks predicting dynamics of time series. Initial weighting coefficients were determined for neurons analogously to the case of a linear prediction filter. Moreover, to improve the accuracy of the initialization method for a multilayer neural network, some variants of decomposition of the transformation matrix corresponding to the linear prediction filter were suggested. The efficiency of the pro...

Bochkarev, Vladimir V.; Maslennikova, Yulia S.

2014-01-01

445

Analysis of multi-layer polymer films  

Directory of Open Access Journals (Sweden)

Full Text Available Polymer multi-layer films are used in a variety of industries. It is important both to the manufacturers of polymer films and to the industries using these films that the quality and composition be strictly controlled. The confocal analysis and high spatial resolution of Raman microscopy make this technique ideal for identifying the source and identity of defects and inclusions in polymer films.

Paulette Guillory

2009-04-01

446

Ultrapure Multilayer Graphene in Bromine Intercalated Graphite  

OpenAIRE

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

447

Toughening mechanisms in bioinspired multilayered materials.  

Science.gov (United States)

Outstanding mechanical properties of biological multilayered materials are strongly influenced by nanoscale features in their structure. In this study, mechanical behaviour and toughening mechanisms of abalone nacre-inspired multilayered materials are explored. In nacre's structure, the organic matrix, pillars and the roughness of the aragonite platelets play important roles in its overall mechanical performance. A micromechanical model for multilayered biological materials is proposed to simulate their mechanical deformation and toughening mechanisms. The fundamental hypothesis of the model is the inclusion of nanoscale pillars with near theoretical strength (?th ~ E/30). It is also assumed that pillars and asperities confine the organic matrix to the proximity of the platelets, and, hence, increase their stiffness, since it has been previously shown that the organic matrix behaves more stiffly in the proximity of mineral platelets. The modelling results are in excellent agreement with the available experimental data for abalone nacre. The results demonstrate that the aragonite platelets, pillars and organic matrix synergistically affect the stiffness of nacre, and the pillars significantly contribute to the mechanical performance of nacre. It is also shown that the roughness induced interactions between the organic matrix and aragonite platelet, represented in the model by asperity elements, play a key role in strength and toughness of abalone nacre. The highly nonlinear behaviour of the proposed multilayered material is the result of distributed deformation in the nacre-like structure due to the existence of nano-asperities and nanopillars with near theoretical strength. Finally, tensile toughness is studied as a function of the components in the microstructure of nacre. PMID:25551150

Askarinejad, Sina; Rahbar, Nima

2015-01-01

448

Domain Structure of Co/Pd multilayers  

OpenAIRE

The observations of submicron domain structure of Co/Pd multilayers at various parts of the M-H loop and after different magnetization cycles designed to approach the global-equilibrium domain width are reported. The wall energy densities were estimated from comparison of the measured equilibrium domain width with the anhysteretic model predictions and also compared with the wall energy densities determined from the slope of major M-H loop

Simsova, Jarmila; Gemperle, Richard; Kambersky, Vladimir; Porthun, Steffen; Haan, Poul; Lodder, Cock

1994-01-01

449

Permeation barrier studies of multilayer films  

OpenAIRE

The gas barrier properties of multilayered films fabricated using a new vacuum web coater at the University of Oxford have been investigated. Oxygen and water vapor transmission rates were measured for a range of coated LLDPE film architectures in order to establish the influence of vacuum deposited acrylate layers on the barrier properties. It was found that the addition of an organic interlayer between two aluminum layers results in three order of magnitude decrease in oxygen transmission r...

Henry, Bm; Topping, J.; Assender, He; Grovenor, Crm; Marras, L.

2005-01-01

450

Multi-layer Boosting for Pattern Recognition  

OpenAIRE

We extend the standard boosting procedure to train a two-layer classifier dedicated to handwritten character recognition. The scheme we propose relies on a hidden layer which extracts feature vectors on a fixed number of points of interest, and an output layer which combines those feature vectors and the point of interest locations into a final classification decision. Our main contribution is to show that the classical AdaBoost procedure can be extended to train such a multi-layered structu...

Fleuret, Francois

2008-01-01

451

A dynamic multilayer shallow water model  

OpenAIRE

We propose a new simple approximation of the viscous primitive equations of the ocean including Coriolis force, by a multilayer shallow water type model. Using a finite volume type discretization in the vertical direction, we show that our system is a consistent approximation of the primitive model. Existence and uniqueness of local in time strong solution is proved for the new model. Finally we design a finite volume numerical scheme, taking advantage of the shallow water type formulation an...

Rambaud, Ame?lie

2012-01-01

452

Stress-induced traps in multilayered structures  

OpenAIRE

The trap parameters of defects in Si/CaF2 multilayered structures were determined from the analysis of optical charging spectroscopy measurements. Two kinds of maxima were observed. Some of them were rather broad, corresponding to "normal" traps, while the others, very sharp, were attributed to stress-induced traps. A procedure of optimal linear smoothing the noisy experimental data has been developed and applied. This procedure is based on finding the minimal value of the r...

Ciurea, Magdalena Lidia; Lazanu, Sorina; Stavarache, Ionel; Lepadatu, Ana-maria; Iancu, Vladimir; Mitroi, Mihai Razvan; Nigmatullin, Raoul Rashid; Baleanu, Cristina Mihaela

2011-01-01

453

Multi-layered liposomes as optical resonators  

Science.gov (United States)

Multi-layered liposomes, comprising a concentric series of lipid bilayers - separated at fixed distances and compartmentalizing aqueous solutions of alternating refractive indices - are proposed as optical Bragg resonators. Seminal work focuses on the feasibility of successive encapsulations coupled with size-control via extrusion. Synthesis criteria for realization of these liposomes were subsequently discussed based on experimental observations. Numerical studies of the proposed structure showed discernible band gaps, qualifying their potential application in biological lasing.

Yong, Derrick; Ng, Wei Long; Lee, Elizabeth; Yu, Xia; Bosman, Michel; Chan, Chi Chiu

454

Recurrent inguinal hernia: preferred operative approach.  

Science.gov (United States)

Inguinal herniorrhaphy remains one of the most common general surgical operations, with approximately 10 to 20 per cent performed for recurrence. Subsequent repairs provide considerable technical challenge, as well as substantially greater risk of developing further recurrence. Mesh repair is advocated by several specialized hernia centers, demonstrating re-recurrence rates less than 2 per cent. Detractors of this repair include cost, technical difficulty, and risk for infection. The purpose of this study was to compare results of mesh and nonmesh repairs for recurrent inguinal hernia, either using an anterior or posterior approach, at a large teaching institution. From January 1, 1985, to December 31, 1994, 146 patients underwent repair for recurrent inguinal hernia at the Veterans Administration Hospital at Memphis, Tennessee. Patients were stratified by type of repair: Lichtenstein (Mesh), open anterior (OA), Bassini, Marcy, McVay, Shouldice, and preperitoneal with or without mesh. Patient ages and weights were similar between groups. Mean operative time for Mesh repair (104 +/- 4 minutes) was longer than that for OA repairs (80 +/- 5 minutes, P repairs (92 +/- 5 minutes, P repairs had the longest operative times (116 +/- 5 minutes). Hospital stay averaged 2.8 +/- 0.3 days, similar among all groups. One wound infection (1.0%) occurred in patients undergoing Mesh repair, which required operative drainage. No patient required removal of mesh. Two patients in the Mesh group (5.9%) developed recurrence compared with four recurrences (18.0%) in patients undergoing OA repairs. Only one patient with a mesh-based posterior repair recurred (1.9%) compared to eight without mesh (21.6%, P Repair of recurrent inguinal hernia using either an anterior or posterior mesh repair technique, performed at a teaching facility, provides superior recurrence rates without increasing risk for infection or length of stay. Preperitoneal mesh based repair is the preferred technique. PMID:9619180

Janu, P G; Sellers, K D; Mangiante, E C

1998-06-01

455

Automation Enhancement of Multilayer Laue Lenses  

Energy Technology Data Exchange (ETDEWEB)

X-ray optics fabrication at Brookhaven National Laboratory has been facilitated by a new, state of the art magnetron sputtering physical deposition system. With its nine magnetron sputtering cathodes and substrate carrier that moves on a linear rail via a UHV brushless linear servo motor, the system is capable of accurately depositing the many thousands of layers necessary for multilayer Laue lenses. I have engineered a versatile and automated control program from scratch for the base system and many subsystems. Its main features include a custom scripting language, a fully customizable graphical user interface, wireless and remote control, and a terminal-based interface. This control system has already been successfully used in the creation of many types of x-ray optics, including several thousand layer multilayer Laue lenses.Before reaching the point at which a deposition can be run, stencil-like masks for the sputtering cathodes must be created to ensure the proper distribution of sputtered atoms. Quality of multilayer Laue lenses can also be difficult to measure, given the size of the thin film layers. I employ my knowledge of software and algorithms to further ease these previously painstaking processes with custom programs. Additionally, I will give an overview of an x-ray optic simulator package I helped develop during the summer of 2010. In the interest of keeping my software free and open, I have worked mostly with the multiplatform Python and the PyQt application framework, utilizing C and C++ where necessary.

Lauer K. R.; Conley R.

2010-12-01

456

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

457

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

458

Multilayer modal actuator-based piezoelectric transformers.  

Science.gov (United States)

An innovative, multilayer piezoelectric transformer equipped with a full modal filtering input electrode is reported herein. This modal-shaped electrode, based on the orthogonal property of structural vibration modes, is characterized by full modal filtering to ensure that only the desired vibration mode is excited during operation. The newly developed piezoelectric transformer is comprised of three layers: a multilayered input layer, an insulation layer, and a single output layer. The electrode shape of the input layer is derived from its structural vibration modal shape, which takes advantage of the orthogonal property of the vibration modes to achieve a full modal filtering effect. The insulation layer possesses two functions: first, to couple the mechanical vibration energy between the input and output, and second, to provide electrical insulation between the two layers. To meet the two functions, a low temperature, co-fired ceramic (LTCC) was used to provide the high mechanical rigidity and high electrical insulation. It can be shown that this newly developed piezoelectric transformer has the advantage of possessing a more efficient energy transfer and a wider optimal working frequency range when compared to traditional piezoelectric transformers. A multilayer piezoelectric, transformer-based inverter applicable for use in LCD monitors or portable displays is presented as well. PMID:17328332

Huang, Yao-Tien; Wu, Wen-Jong; Wang, Yen-Chieh; Lee, Chih-Kung

2007-02-01

459

Treatment of Recurrent Ovarian Cancer.  

Directory of Open Access Journals (Sweden)

Full Text Available Recurrent ovarian cancer is a common clinical problem and the management of eachpatient must be individualized. Diagnosis is usually based on a progressively rising CA-125titre, and a CT scan of the pelvis and abdomen, together with a chest X-ray should be performed.Although there is no study to support immediate treatment in the asymptomaticpatient, our approach is to commence such patients on Tamoxifen. Chemotherapy isreserved for asymptomatic patients or those who progress on Tamoxifen. The longer thetreatment-free interval of 18-24 months. The choice of non-platinum second or subsequentline chemotherapy is based on many factors including likelihood of benefit, potential toxicity,schedule and convenience to the patient, as well as organ function and residual toxicityfrom prior treatment. Aggressive secondary cytoreductive surgery can significantly prolongsurvival in those with a disease-free interval of 24 months or more and in those in whom allmacroscopic disease can be removed. Radiation therapy to the tumour bed following resectionof localized disease may be beneficial in selected patients. Quality of life issues are particularlyimportant for this group of patients and have not been adequately studies.Communication regarding the objectives of therapy is important, and the multidisciplinaryapproach should include palliative care and psycho-social support, in addition to the moretraditional medical options.

Neville F. Hacker

2004-08-01

460

Thromboembolism risk following recurrent miscarriage.  

Science.gov (United States)

Normal pregnancy is associated with extensive changes in hemostasis such that the procoagulant effect becomes dominant. The evolutionary advantage of this hypercoagulability may be to counteract the inherent instability associated with hemochorial placentation, which is unique to human beings. However, overall, there is a four- to 10-fold increased thrombotic risk throughout gestation and the postpartum period. Certain inherited or acquired thrombophilic factors may predispose to arterial and/or venous thrombosis and have a possible association with pregnancy complications, including recurrent miscarriage (RM), which affects up to 5% of couples with childbearing desire. A subgroup of women with RM has been demonstrated to be in a prothombotic state before and after pregnancy. The long-term health implications of this hypercoagulability may imply an increased risk of ischemic heart disease. Moreover, the presence of antiphospholipid antibodies rather than thrombophilic genetic defects (i.e., factor V Leiden or prothrombin G202010A mutation) in patients with RM is a determinant of thrombotic events later in life, especially among those patients having also cardiovascular risk factors. This article highlights the thromboembolic risk in nonpregnant RM patients in different thrombophilic settings and the need for thromboprophylaxis among these patients. PMID:24134441

Martínez-Zamora, Maria Á; Cervera, Ricard; Balasch, Juan

2013-11-01

461

Recurrence of hallux valgus: a review.  

Science.gov (United States)

Recurrence of hallux valgus deformity can be a common complication after corrective surgery. The cause of recurrent hallux valgus is usually multifactorial, and includes patient-related factors such as preoperative anatomic predisposition, medical comorbidities, compliance with postcorrection instructions, and surgical factors such as choice of the appropriate procedure and technical competency. For a successful outcome, this cause must be ascertained preoperatively. Although the algorithm to determine which intervention should be used is not unlike that of primary hallux valgus surgery, operative correction of hallux valgus recurrence can be challenging. This article discusses these challenges, complications, causes, and techniques. PMID:24878414

Raikin, Steven M; Miller, Adam G; Daniel, Joseph

2014-06-01

462

Typicality of recurrence for Lorentz gases  

CERN Document Server

It is a safe conjecture that most (not necessarily periodic) two-dimensional Lorentz gases with finite horizon are recurrent. Here we formalize this conjecture by means of a stochastic ensemble of Lorentz gases, in which i.i.d. random scatterers are placed in each cell of a co-compact lattice in the plane. We prove that the typical Lorentz gas, in the sense of Baire, is recurrent, and give results in the direction of showing that recurrence is an almost sure property (including a zero-one law that holds in every dimension). A few toy models illustrate the extent of these results.

Lenci, M

2004-01-01

463

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. Owho 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

464

Recurrences of transient synovitis of the hip.  

OpenAIRE

Thirty six children with transient synovitis of the hip had a total of 80 recurrences, 69 of them personally observed, and 11 described by the mother. No features distinguished the initial attack of those who had a recurrence from that of the 18 children who have not so far had a recurrence. We analysed the total of 126 episodes. In 72 there was evidence of an associated infection from the history, clinical signs, and a raised antistreptolysin O titre or isolation of a pathogen from a throat ...

Illingworth, C. M.

1983-01-01

465

New Si-based multilayers for solar cell applications  

OpenAIRE

Abstract In this article, we have fabricated and studied a new multilayer structure Si-SiO2/SiN x by reactive magnetron sputtering. The comparison between SiO2 and SiN x host matrices in the optical properties of the multilayers is detailed. Structural analysis was made on the multilayer structures using Fourier transform infrared spectroscopy. The effect of specific annealing treatments on the optical properties is stu...

Nalini Ramesh; Dufour Christian; Cardin Julien; Gourbilleau Fabrice

2011-01-01

466

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

467

Stress in tungsten carbide-diamond like carbon multilayer coatings:  

OpenAIRE

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...

Pujada, B. R.; Tichelaar, F. D.; Janssen, G. C. A. M.

2007-01-01

468

Polymerization of amphiphilic dienes in Langmuir-Blodgett multilayers  

OpenAIRE

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...

Laschewsky, Andre?; Ringsdorf, H.

1988-01-01

469

77 FR 45336 - 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 was published...

2012-07-31

470

76 FR 76693 - Multilayered Wood Flooring From the People's Republic of China: Countervailing Duty Order  

Science.gov (United States)

...Administration [C-570-971] Multilayered Wood Flooring From the People's Republic of...duty (``CVD'') order on multilayered wood flooring from the People's Republic of...producers and exporters of multilayered wood flooring from the PRC. See...

2011-12-08

471

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

472

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

473

Heterogeneous recurrence monitoring and control of nonlinear stochastic processes  

Energy Technology Data Exchange (ETDEWEB)

Recurrence is one of the most common phenomena in natural and engineering systems. Process monitoring of dynamic transitions in nonlinear and nonstationary systems is more concerned with aperiodic recurrences and recurrence variations. However, little has been done to investigate the heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. Notably, nonlinear recurrence methodologies are based on homogeneous recurrences, which treat all recurrence states in the same way as black dots, and non-recurrence is white in recurrence plots. Heterogeneous recurrences are more concerned about the variations of recurrence states in terms of state properties (e.g., values and relative locations) and the evolving dynamics (e.g., sequential state transitions). This paper presents a novel approach of heterogeneous recurrence analysis that utilizes a new fractal representation to delineate heterogeneous recurrence states in multiple scales, including the recurrences of both single states and multi-state sequences. Further, we developed a new set of heterogeneous recurrence quantifiers that are extracted from fractal representation in the transformed space. To that end, we integrated multivariate statistical control charts with heterogeneous recurrence analysis to simultaneously monitor two or more related quantifiers. Experimental results on nonlinear stochastic processes show that the proposed approach not only captures heterogeneous recurrence patterns in the fractal representation but also effectively monitors the changes in the dynamics of a complex system.

Yang, Hui, E-mail: huiyang@usf.edu; Chen, Yun [Complex Systems Monitoring, Modeling and Analysis Laboratory, University of South Florida, Tampa, Florida 33620 (United States)

2014-03-15

474

Heterogeneous recurrence monitoring and control of nonlinear stochastic processes  

International Nuclear Information System (INIS)

Recurrence is one of the most common phenomena in natural and engineering systems. Process monitoring of dynamic transitions in nonlinear and nonstationary systems is more concerned with aperiodic recurrences and recurrence variations. However, little has been done to investigate the heterogeneous recurrence variations and link with the objectives of process monitoring and anomaly detection. Notably, nonlinear recurrence methodologies are based on homogeneous recurrences, which treat all recurrence states in the same way as black dots, and non-recurrence is white in recurrence plots. Heterogeneous recurrences are more concerned about the variations of recurrence states in terms of state properties (e.g., values and relative locations) and the evolving dynamics (e.g., sequential state transitions). This paper presents a novel approach of heterogeneous recurrence analysis that utilizes a new fractal representation to delineate heterogeneous recurrence states in multiple scales, including the recurrences of both single states and multi-state sequences. Further, we developed a new set of heterogeneous recurrence quantifiers that are extracted from fractal representation in the transformed space. To that end, we integrated multivariate statistical control charts with heterogeneous recurrence analysis to simultaneously monitor two or more related quantifiers. Experimental results on nonlinear stochastic processes show that the proposed approach not only captures heterogeneous recurrence patterns in the fractal representation but also effectively monitors the changes in the dynamics of a complex system