WorldWideScience

Sample records for networks radial basis

  1. Learning Methods for Radial Basis Functions Networks

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman; Kudová, Petra

    2005-01-01

    Roč. 21, - (2005), s. 1131-1142 ISSN 0167-739X R&D Projects: GA ČR GP201/03/P163; GA ČR GA201/02/0428 Institutional research plan: CEZ:AV0Z10300504 Keywords : radial basis function networks * hybrid supervised learning * genetic algorithms * benchmarking Subject RIV: BA - General Mathematics Impact factor: 0.555, year: 2005

  2. Application of radial basis neural network for state estimation of ...

    African Journals Online (AJOL)

    An original application of radial basis function (RBF) neural network for power system state estimation is proposed in this paper. The property of massive parallelism of neural networks is employed for this. The application of RBF neural network for state estimation is investigated by testing its applicability on a IEEE 14 bus ...

  3. Radial basis function neural network in fault detection of automotive ...

    African Journals Online (AJOL)

    Radial basis function neural network in fault detection of automotive engines. ... Five faults have been simulated on the MVEM, including three sensor faults, one component fault and one actuator fault. The three sensor faults ... Keywords: Automotive engine, independent RBFNN model, RBF neural network, fault detection

  4. Organisms modeling: The question of radial basis function networks

    Directory of Open Access Journals (Sweden)

    Muzy Alexandre

    2014-01-01

    Full Text Available There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are tempted to build their own systems independently of biological issues. This publication is a first-step re-evalution of an usual machine learning technique (radial basis funtion(RBF networks in the context of systems and biological reactive organisms.

  5. On-line learning in radial basis functions networks

    OpenAIRE

    Freeman, Jason; Saad, David

    1997-01-01

    An analytic investigation of the average case learning and generalization properties of Radial Basis Function Networks (RBFs) is presented, utilising on-line gradient descent as the learning rule. The analytic method employed allows both the calculation of generalization error and the examination of the internal dynamics of the network. The generalization error and internal dynamics are then used to examine the role of the learning rate and the specialization of the hidden units, which gives ...

  6. Modeling Marine Electromagnetic Survey with Radial Basis Function Networks

    Directory of Open Access Journals (Sweden)

    Agus Arif

    2014-11-01

    Full Text Available A marine electromagnetic survey is an engineering endeavour to discover the location and dimension of a hydrocarbon layer under an ocean floor. In this kind of survey, an array of electric and magnetic receivers are located on the sea floor and record the scattered, refracted and reflected electromagnetic wave, which has been transmitted by an electric dipole antenna towed by a vessel. The data recorded in receivers must be processed and further analysed to estimate the hydrocarbon location and dimension. To conduct those analyses successfuly, a radial basis function (RBF network could be employed to become a forward model of the input-output relationship of the data from a marine electromagnetic survey. This type of neural networks is working based on distances between its inputs and predetermined centres of some basis functions. A previous research had been conducted to model the same marine electromagnetic survey using another type of neural networks, which is a multi layer perceptron (MLP network. By comparing their validation and training performances (mean-squared errors and correlation coefficients, it is concluded that, in this case, the MLP network is comparatively better than the RBF network[1].[1] This manuscript is an extended version of our previous paper, entitled Radial Basis Function Networks for Modeling Marine Electromagnetic Survey, which had been presented on 2011 International Conference on Electrical Engineering and Informatics, 17-19 July 2011, Bandung, Indonesia.

  7. Complexity of Gaussian-Radial-Basis Networks Approximating Smooth Functions

    Czech Academy of Sciences Publication Activity Database

    Kainen, P.C.; Kůrková, Věra; Sanguineti, M.

    2009-01-01

    Roč. 25, č. 1 (2009), s. 63-74 ISSN 0885-064X R&D Projects: GA ČR GA201/08/1744 Institutional research plan: CEZ:AV0Z10300504 Keywords : Gaussian-radial-basis-function networks * rates of approximation * model complexity * variation norms * Bessel and Sobolev norms * tractability of approximation Subject RIV: IN - Informatics, Computer Science Impact factor: 1.227, year: 2009

  8. Radial Basis Function Networks for Conversion of Sound Spectra

    Directory of Open Access Journals (Sweden)

    Carlo Drioli

    2001-03-01

    Full Text Available In many advanced signal processing tasks, such as pitch shifting, voice conversion or sound synthesis, accurate spectral processing is required. Here, the use of Radial Basis Function Networks (RBFN is proposed for the modeling of the spectral changes (or conversions related to the control of important sound parameters, such as pitch or intensity. The identification of such conversion functions is based on a procedure which learns the shape of the conversion from few couples of target spectra from a data set. The generalization properties of RBFNs provides for interpolation with respect to the pitch range. In the construction of the training set, mel-cepstral encoding of the spectrum is used to catch the perceptually most relevant spectral changes. Moreover, a singular value decomposition (SVD approach is used to reduce the dimension of conversion functions. The RBFN conversion functions introduced are characterized by a perceptually-based fast training procedure, desirable interpolation properties and computational efficiency.

  9. Neuronal spike sorting based on radial basis function neural networks

    Directory of Open Access Journals (Sweden)

    Taghavi Kani M

    2011-02-01

    Full Text Available "nBackground: Studying the behavior of a society of neurons, extracting the communication mechanisms of brain with other tissues, finding treatment for some nervous system diseases and designing neuroprosthetic devices, require an algorithm to sort neuralspikes automatically. However, sorting neural spikes is a challenging task because of the low signal to noise ratio (SNR of the spikes. The main purpose of this study was to design an automatic algorithm for classifying neuronal spikes that are emitted from a specific region of the nervous system."n "nMethods: The spike sorting process usually consists of three stages: detection, feature extraction and sorting. We initially used signal statistics to detect neural spikes. Then, we chose a limited number of typical spikes as features and finally used them to train a radial basis function (RBF neural network to sort the spikes. In most spike sorting devices, these signals are not linearly discriminative. In order to solve this problem, the aforesaid RBF neural network was used."n "nResults: After the learning process, our proposed algorithm classified any arbitrary spike. The obtained results showed that even though the proposed Radial Basis Spike Sorter (RBSS reached to the same error as the previous methods, however, the computational costs were much lower compared to other algorithms. Moreover, the competitive points of the proposed algorithm were its good speed and low computational complexity."n "nConclusion: Regarding the results of this study, the proposed algorithm seems to serve the purpose of procedures that require real-time processing and spike sorting.

  10. Satisfiability of logic programming based on radial basis function neural networks

    International Nuclear Information System (INIS)

    Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged; Choon, Ong Hong

    2014-01-01

    In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We applied the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems

  11. Satisfiability of logic programming based on radial basis function neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hamadneh, Nawaf; Sathasivam, Saratha; Tilahun, Surafel Luleseged; Choon, Ong Hong [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia)

    2014-07-10

    In this paper, we propose a new technique to test the Satisfiability of propositional logic programming and quantified Boolean formula problem in radial basis function neural networks. For this purpose, we built radial basis function neural networks to represent the proportional logic which has exactly three variables in each clause. We used the Prey-predator algorithm to calculate the output weights of the neural networks, while the K-means clustering algorithm is used to determine the hidden parameters (the centers and the widths). Mean of the sum squared error function is used to measure the activity of the two algorithms. We applied the developed technique with the recurrent radial basis function neural networks to represent the quantified Boolean formulas. The new technique can be applied to solve many applications such as electronic circuits and NP-complete problems.

  12. A metric for the Radial Basis Function Network - Application on Real Radar Data

    NARCIS (Netherlands)

    Heiden, R. van der; Groen, F.C.A.

    1996-01-01

    A Radial Basis Functions (RBF) network for pattern recognition is considered. Classification with such a network is based on distances between patterns, so a metric is always present. Using real radar data, the Euclidean metric is shown to perform poorly - a metric based on the so called Box-Cox

  13. Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

    Science.gov (United States)

    Burken, John J.

    2005-01-01

    This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

  14. Sea Surface Temperature Modeling using Radial Basis Function Networks With a Dynamically Weighted Particle Filter

    KAUST Repository

    Ryu, Duchwan; Liang, Faming; Mallick, Bani K.

    2013-01-01

    be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle

  15. An enhanced radial basis function network for short-term electricity price forecasting

    International Nuclear Information System (INIS)

    Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang

    2010-01-01

    This paper proposed a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Radial Basis Function Network (RBFN) and Orthogonal Experimental Design (OED), an Enhanced Radial Basis Function Network (ERBFN) has been proposed for the solving process. The Locational Marginal Price (LMP), system load, transmission flow and temperature of the PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday and weekend. With the OED applied to learning rates in the ERBFN, the forecasting error can be reduced during the training process to improve both accuracy and reliability. This would mean that even the ''spikes'' could be tracked closely. The Back-propagation Neural Network (BPN), Probability Neural Network (PNN), other algorithms, and the proposed ERBFN were all developed and compared to check the performance. Simulation results demonstrated the effectiveness of the proposed ERBFN to provide quality information in a price volatile environment. (author)

  16. Machine learning of radial basis function neural network based on Kalman filter: Introduction

    Directory of Open Access Journals (Sweden)

    Vuković Najdan L.

    2014-01-01

    Full Text Available This paper analyzes machine learning of radial basis function neural network based on Kalman filtering. Three algorithms are derived: linearized Kalman filter, linearized information filter and unscented Kalman filter. We emphasize basic properties of these estimation algorithms, demonstrate how their advantages can be used for optimization of network parameters, derive mathematical models and show how they can be applied to model problems in engineering practice.

  17. A prediction method for the wax deposition rate based on a radial basis function neural network

    Directory of Open Access Journals (Sweden)

    Ying Xie

    2017-06-01

    Full Text Available The radial basis function neural network is a popular supervised learning tool based on machinery learning technology. Its high precision having been proven, the radial basis function neural network has been applied in many areas. The accumulation of deposited materials in the pipeline may lead to the need for increased pumping power, a decreased flow rate or even to the total blockage of the line, with losses of production and capital investment, so research on predicting the wax deposition rate is significant for the safe and economical operation of an oil pipeline. This paper adopts the radial basis function neural network to predict the wax deposition rate by considering four main influencing factors, the pipe wall temperature gradient, pipe wall wax crystal solubility coefficient, pipe wall shear stress and crude oil viscosity, by the gray correlational analysis method. MATLAB software is employed to establish the RBF neural network. Compared with the previous literature, favorable consistency exists between the predicted outcomes and the experimental results, with a relative error of 1.5%. It can be concluded that the prediction method of wax deposition rate based on the RBF neural network is feasible.

  18. Radial basis function neural networks with sequential learning MRAN and its applications

    CERN Document Server

    Sundararajan, N; Wei Lu Ying

    1999-01-01

    This book presents in detail the newly developed sequential learning algorithm for radial basis function neural networks, which realizes a minimal network. This algorithm, created by the authors, is referred to as Minimal Resource Allocation Networks (MRAN). The book describes the application of MRAN in different areas, including pattern recognition, time series prediction, system identification, control, communication and signal processing. Benchmark problems from these areas have been studied, and MRAN is compared with other algorithms. In order to make the book self-contained, a review of t

  19. Radial basis function (RBF) neural network control for mechanical systems design, analysis and Matlab simulation

    CERN Document Server

    Liu, Jinkun

    2013-01-01

    Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design.   This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronauti...

  20. Upset Prediction in Friction Welding Using Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Wei Liu

    2013-01-01

    Full Text Available This paper addresses the upset prediction problem of friction welded joints. Based on finite element simulations of inertia friction welding (IFW, a radial basis function (RBF neural network was developed initially to predict the final upset for a number of welding parameters. The predicted joint upset by the RBF neural network was compared to validated finite element simulations, producing an error of less than 8.16% which is reasonable. Furthermore, the effects of initial rotational speed and axial pressure on the upset were investigated in relation to energy conversion with the RBF neural network. The developed RBF neural network was also applied to linear friction welding (LFW and continuous drive friction welding (CDFW. The correlation coefficients of RBF prediction for LFW and CDFW were 0.963 and 0.998, respectively, which further suggest that an RBF neural network is an effective method for upset prediction of friction welded joints.

  1. Radial basis function neural network for power system load-flow

    International Nuclear Information System (INIS)

    Karami, A.; Mohammadi, M.S.

    2008-01-01

    This paper presents a method for solving the load-flow problem of the electric power systems using radial basis function (RBF) neural network with a fast hybrid training method. The main idea is that some operating conditions (values) are needed to solve the set of non-linear algebraic equations of load-flow by employing an iterative numerical technique. Therefore, we may view the outputs of a load-flow program as functions of the operating conditions. Indeed, we are faced with a function approximation problem and this can be done by an RBF neural network. The proposed approach has been successfully applied to the 10-machine and 39-bus New England test system. In addition, this method has been compared with that of a multi-layer perceptron (MLP) neural network model. The simulation results show that the RBF neural network is a simpler method to implement and requires less training time to converge than the MLP neural network. (author)

  2. Computing single step operators of logic programming in radial basis function neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong [School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang (Malaysia)

    2014-07-10

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

  3. Computing single step operators of logic programming in radial basis function neural networks

    Science.gov (United States)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

    2014-07-01

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (Tp:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

  4. Computing single step operators of logic programming in radial basis function neural networks

    International Nuclear Information System (INIS)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

    2014-01-01

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T p :I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks

  5. A fast identification algorithm for Box-Cox transformation based radial basis function neural network.

    Science.gov (United States)

    Hong, Xia

    2006-07-01

    In this letter, a Box-Cox transformation-based radial basis function (RBF) neural network is introduced using the RBF neural network to represent the transformed system output. Initially a fixed and moderate sized RBF model base is derived based on a rank revealing orthogonal matrix triangularization (QR decomposition). Then a new fast identification algorithm is introduced using Gauss-Newton algorithm to derive the required Box-Cox transformation, based on a maximum likelihood estimator. The main contribution of this letter is to explore the special structure of the proposed RBF neural network for computational efficiency by utilizing the inverse of matrix block decomposition lemma. Finally, the Box-Cox transformation-based RBF neural network, with good generalization and sparsity, is identified based on the derived optimal Box-Cox transformation and a D-optimality-based orthogonal forward regression algorithm. The proposed algorithm and its efficacy are demonstrated with an illustrative example in comparison with support vector machine regression.

  6. Design and Modeling of RF Power Amplifiers with Radial Basis Function Artificial Neural Networks

    OpenAIRE

    Ali Reza Zirak; Sobhan Roshani

    2016-01-01

    A radial basis function (RBF) artificial neural network model for a designed high efficiency radio frequency class-F power amplifier (PA) is presented in this paper. The presented amplifier is designed at 1.8 GHz operating frequency with 12 dB of gain and 36 dBm of 1dB output compression point. The obtained power added efficiency (PAE) for the presented PA is 76% under 26 dBm input power. The proposed RBF model uses input and DC power of the PA as inputs variables and considers output power a...

  7. Parallel Fixed Point Implementation of a Radial Basis Function Network in an FPGA

    Directory of Open Access Journals (Sweden)

    Alisson C. D. de Souza

    2014-09-01

    Full Text Available This paper proposes a parallel fixed point radial basis function (RBF artificial neural network (ANN, implemented in a field programmable gate array (FPGA trained online with a least mean square (LMS algorithm. The processing time and occupied area were analyzed for various fixed point formats. The problems of precision of the ANN response for nonlinear classification using the XOR gate and interpolation using the sine function were also analyzed in a hardware implementation. The entire project was developed using the System Generator platform (Xilinx, with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA.

  8. Combustion monitoring of a water tube boiler using a discriminant radial basis network.

    Science.gov (United States)

    Sujatha, K; Pappa, N

    2011-01-01

    This research work includes a combination of Fisher's linear discriminant (FLD) analysis and a radial basis network (RBN) for monitoring the combustion conditions for a coal fired boiler so as to allow control of the air/fuel ratio. For this, two-dimensional flame images are required, which were captured with a CCD camera; the features of the images-average intensity, area, brightness and orientation etc of the flame-are extracted after preprocessing the images. The FLD is applied to reduce the n-dimensional feature size to a two-dimensional feature size for faster learning of the RBN. Also, three classes of images corresponding to different burning conditions of the flames have been extracted from continuous video processing. In this, the corresponding temperatures, and the carbon monoxide (CO) emissions and those of other flue gases have been obtained through measurement. Further, the training and testing of Fisher's linear discriminant radial basis network (FLDRBN), with the data collected, have been carried out and the performance of the algorithms is presented. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Performance-oriented asymptotic tracking control of hydraulic systems with radial basis function network disturbance observer

    Directory of Open Access Journals (Sweden)

    Jian Hu

    2016-05-01

    Full Text Available Uncertainties, including parametric uncertainties and uncertain nonlinearities, always exist in positioning servo systems driven by a hydraulic actuator, which would degrade their tracking accuracy. In this article, an integrated control scheme, which combines adaptive robust control together with radial basis function neural network–based disturbance observer, is proposed for high-accuracy motion control of hydraulic systems. Not only parametric uncertainties but also uncertain nonlinearities (i.e. nonlinear friction, external disturbances, and/or unmodeled dynamics are taken into consideration in the proposed controller. The above uncertainties are compensated, respectively, by adaptive control and radial basis function neural network, which are ultimately integrated together by applying feedforward compensation technique, in which the global stabilization of the controller is ensured via a robust feedback path. A new kind of parameter and weight adaptation law is designed on the basis of Lyapunov stability theory. Furthermore, the proposed controller obtains an expected steady performance even if modeling uncertainties exist, and extensive simulation results in various working conditions have proven the high performance of the proposed control scheme.

  10. Fault diagnosis and performance evaluation for high current LIA based on radial basis function neural network

    International Nuclear Information System (INIS)

    Yang Xinglin; Wang Huacen; Chen Nan; Dai Wenhua; Li Jin

    2006-01-01

    High current linear induction accelerator (LIA) is a complicated experimental physics device. It is difficult to evaluate and predict its performance. this paper presents a method which combines wavelet packet transform and radial basis function (RBF) neural network to build fault diagnosis and performance evaluation in order to improve reliability of high current LIA. The signal characteristics vectors which are extracted based on energy parameters of wavelet packet transform can well present the temporal and steady features of pulsed power signal, and reduce data dimensions effectively. The fault diagnosis system for accelerating cell and the trend classification system for the beam current based on RBF networks can perform fault diagnosis and evaluation, and provide predictive information for precise maintenance of high current LIA. (authors)

  11. Adaptive Linear and Normalized Combination of Radial Basis Function Networks for Function Approximation and Regression

    Directory of Open Access Journals (Sweden)

    Yunfeng Wu

    2014-01-01

    Full Text Available This paper presents a novel adaptive linear and normalized combination (ALNC method that can be used to combine the component radial basis function networks (RBFNs to implement better function approximation and regression tasks. The optimization of the fusion weights is obtained by solving a constrained quadratic programming problem. According to the instantaneous errors generated by the component RBFNs, the ALNC is able to perform the selective ensemble of multiple leaners by adaptively adjusting the fusion weights from one instance to another. The results of the experiments on eight synthetic function approximation and six benchmark regression data sets show that the ALNC method can effectively help the ensemble system achieve a higher accuracy (measured in terms of mean-squared error and the better fidelity (characterized by normalized correlation coefficient of approximation, in relation to the popular simple average, weighted average, and the Bagging methods.

  12. Sea Surface Temperature Modeling using Radial Basis Function Networks With a Dynamically Weighted Particle Filter

    KAUST Repository

    Ryu, Duchwan

    2013-03-01

    The sea surface temperature (SST) is an important factor of the earth climate system. A deep understanding of SST is essential for climate monitoring and prediction. In general, SST follows a nonlinear pattern in both time and location and can be modeled by a dynamic system which changes with time and location. In this article, we propose a radial basis function network-based dynamic model which is able to catch the nonlinearity of the data and propose to use the dynamically weighted particle filter to estimate the parameters of the dynamic model. We analyze the SST observed in the Caribbean Islands area after a hurricane using the proposed dynamic model. Comparing to the traditional grid-based approach that requires a supercomputer due to its high computational demand, our approach requires much less CPU time and makes real-time forecasting of SST doable on a personal computer. Supplementary materials for this article are available online. © 2013 American Statistical Association.

  13. Application of radial basis function neural network to predict soil sorption partition coefficient using topological descriptors.

    Science.gov (United States)

    Sabour, Mohammad Reza; Moftakhari Anasori Movahed, Saman

    2017-02-01

    The soil sorption partition coefficient logK oc is an indispensable parameter that can be used in assessing the environmental risk of organic chemicals. In order to predict soil sorption partition coefficient for different and even unknown compounds in a fast and accurate manner, a radial basis function neural network (RBFNN) model was developed. Eight topological descriptors of 800 organic compounds were used as inputs of the model. These 800 organic compounds were chosen from a large and very diverse data set. Generalized Regression Neural Network (GRNN) was utilized as the function in this neural network model due to its capability to adapt very quickly. Hence, it can be used to predict logK oc for new chemicals, as well. Out of total data set, 560 organic compounds were used for training and 240 to test efficiency of the model. The obtained results indicate that the model performance is very well. The correlation coefficients (R2) for training and test sets were 0.995 and 0.933, respectively. The root-mean square errors (RMSE) were 0.2321 for training set and 0.413 for test set. As the results for both training and test set are extremely satisfactory, the proposed neural network model can be employed not only to predict logK oc of known compounds, but also to be adaptive for prediction of this value precisely for new products that enter the market each year. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. Vibration control of uncertain multiple launch rocket system using radial basis function neural network

    Science.gov (United States)

    Li, Bo; Rui, Xiaoting

    2018-01-01

    Poor dispersion characteristics of rockets due to the vibration of Multiple Launch Rocket System (MLRS) have always restricted the MLRS development for several decades. Vibration control is a key technique to improve the dispersion characteristics of rockets. For a mechanical system such as MLRS, the major difficulty in designing an appropriate control strategy that can achieve the desired vibration control performance is to guarantee the robustness and stability of the control system under the occurrence of uncertainties and nonlinearities. To approach this problem, a computed torque controller integrated with a radial basis function neural network is proposed to achieve the high-precision vibration control for MLRS. In this paper, the vibration response of a computed torque controlled MLRS is described. The azimuth and elevation mechanisms of the MLRS are driven by permanent magnet synchronous motors and supposed to be rigid. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, in order to deal with the nonlinearities, a computed torque controller is designed to control the vibration of the MLRS when it is firing a salvo of rockets. Furthermore, to compensate for the lumped uncertainty due to parametric variations and un-modeled dynamics in the design of the computed torque controller, a radial basis function neural network estimator is developed to adapt the uncertainty based on Lyapunov stability theory. Finally, the simulated results demonstrate the effectiveness of the proposed control system and show that the proposed controller is robust with regard to the uncertainty.

  15. Motion planning for autonomous vehicle based on radial basis function neural network in unstructured environment.

    Science.gov (United States)

    Chen, Jiajia; Zhao, Pan; Liang, Huawei; Mei, Tao

    2014-09-18

    The autonomous vehicle is an automated system equipped with features like environment perception, decision-making, motion planning, and control and execution technology. Navigating in an unstructured and complex environment is a huge challenge for autonomous vehicles, due to the irregular shape of road, the requirement of real-time planning, and the nonholonomic constraints of vehicle. This paper presents a motion planning method, based on the Radial Basis Function (RBF) neural network, to guide the autonomous vehicle in unstructured environments. The proposed algorithm extracts the drivable region from the perception grid map based on the global path, which is available in the road network. The sample points are randomly selected in the drivable region, and a gradient descent method is used to train the RBF network. The parameters of the motion-planning algorithm are verified through the simulation and experiment. It is observed that the proposed approach produces a flexible, smooth, and safe path that can fit any road shape. The method is implemented on autonomous vehicle and verified against many outdoor scenes; furthermore, a comparison of proposed method with the existing well-known Rapidly-exploring Random Tree (RRT) method is presented. The experimental results show that the proposed method is highly effective in planning the vehicle path and offers better motion quality.

  16. Reconstruction of gastric slow wave from finger photoplethysmographic signal using radial basis function neural network.

    Science.gov (United States)

    Mohamed Yacin, S; Srinivasa Chakravarthy, V; Manivannan, M

    2011-11-01

    Extraction of extra-cardiac information from photoplethysmography (PPG) signal is a challenging research problem with significant clinical applications. In this study, radial basis function neural network (RBFNN) is used to reconstruct the gastric myoelectric activity (GMA) slow wave from finger PPG signal. Finger PPG and GMA (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the sampling rate of 100 Hz from ten healthy subjects. Discrete wavelet transform (DWT) was used to extract slow wave (0-0.1953 Hz) component from the finger PPG signal; this slow wave PPG was used to reconstruct EGG. A RBFNN is trained on signals obtained from six subjects in both fasting and postprandial conditions. The trained network is tested on data obtained from the remaining four subjects. In the earlier study, we have shown the presence of GMA information in finger PPG signal using DWT and cross-correlation method. In this study, we explicitly reconstruct gastric slow wave from finger PPG signal by the proposed RBFNN-based method. It was found that the network-reconstructed slow wave provided significantly higher (P wave than the correlation obtained (≈0.7) between the PPG slow wave from DWT and the EEG slow wave. Our results showed that a simple finger PPG signal can be used to reconstruct gastric slow wave using RBFNN method.

  17. Statistical Downscaling of Gusts During Extreme European Winter Storms Using Radial-Basis-Function Networks

    Science.gov (United States)

    Voigt, M.; Lorenz, P.; Kruschke, T.; Osinski, R.; Ulbrich, U.; Leckebusch, G. C.

    2012-04-01

    Winterstorms and related gusts can cause extensive socio-economic damages. Knowledge about the occurrence and the small scale structure of such events may help to make regional estimations of storm losses. For a high spatial and temporal representation, the use of dynamical downscaling methods (RCM) is a cost-intensive and time-consuming option and therefore only applicable for a limited number of events. The current study explores a methodology to provide a statistical downscaling, which offers small scale structured gust fields from an extended large scale structured eventset. Radial-basis-function (RBF) networks in combination with bidirectional Kohonen (BDK) maps are used to generate the gustfields on a spatial resolution of 7 km from the 6-hourly mean sea level pressure field from ECMWF reanalysis data. BDK maps are a kind of neural network which handles supervised classification problems. In this study they are used to provide prototypes for the RBF network and give a first order approximation for the output data. A further interpolation is done by the RBF network. For the training process the 50 most extreme storm events over the North Atlantic area from 1957 to 2011 are used, which have been selected from ECMWF reanalysis datasets ERA40 and ERA-Interim by an objective wind based tracking algorithm. These events were downscaled dynamically by application of the DWD model chain GME → COSMO-EU. Different model parameters and their influence on the quality of the generated high-resolution gustfields are studied. It is shown that the statistical RBF network approach delivers reasonable results in modeling the regional gust fields for untrained events.

  18. Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm. (On-Line Harmonics Estimation Application

    Directory of Open Access Journals (Sweden)

    Eyad K Almaita

    2017-03-01

    Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application.  International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17

  19. Reconstruction of Daily Sea Surface Temperature Based on Radial Basis Function Networks

    Directory of Open Access Journals (Sweden)

    Zhihong Liao

    2017-11-01

    Full Text Available A radial basis function network (RBFN method is proposed to reconstruct daily Sea surface temperatures (SSTs with limited SST samples. For the purpose of evaluating the SSTs using this method, non-biased SST samples in the Pacific Ocean (10°N–30°N, 115°E–135°E are selected when the tropical storm Hagibis arrived in June 2014, and these SST samples are obtained from the Reynolds optimum interpolation (OI v2 daily 0.25° SST (OISST products according to the distribution of AVHRR L2p SST and in-situ SST data. Furthermore, an improved nearest neighbor cluster (INNC algorithm is designed to search for the optimal hidden knots for RBFNs from both the SST samples and the background fields. Then, the reconstructed SSTs from the RBFN method are compared with the results from the OI method. The statistical results show that the RBFN method has a better performance of reconstructing SST than the OI method in the study, and that the average RMSE is 0.48 °C for the RBFN method, which is quite smaller than the value of 0.69 °C for the OI method. Additionally, the RBFN methods with different basis functions and clustering algorithms are tested, and we discover that the INNC algorithm with multi-quadric function is quite suitable for the RBFN method to reconstruct SSTs when the SST samples are sparsely distributed.

  20. Radial basis function networks applied to DNBR calculation in digital core protection systems

    International Nuclear Information System (INIS)

    Lee, Gyu-Cheon; Heung Chang, Soon

    2003-01-01

    The nuclear power plant has to be operated with sufficient margin from the specified DNBR limit for assuring its safety. The digital core protection system calculates on-line real-time DNBR by using a complex subchannel analysis program, and triggers a reliable reactor shutdown if the calculated DNBR approaches the specified limit. However, it takes a relatively long calculation time even for a steady state condition, which may have an adverse effect on the operation flexibility. To overcome the drawback, a new method using a radial basis function network is presented in this paper. Nonparametric training approach is utilized, which shows dramatic reduction of the training time, no tedious heuristic process for optimizing parameters, and no local minima problem during the training. The test results show that the predicted DNBR is within about ±2% deviation from the target DNBR for the fixed axial flux shape case. For the variable axial flux case including severely skewed shapes that appeared during accidents, the deviation is within about ±10%. The suggested method could be the alternative that can calculate DNBR very quickly while guaranteeing the plant safety

  1. Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction.

    Science.gov (United States)

    Kumudha, P; Venkatesan, R

    Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.

  2. Prediction of water formation temperature in natural gas dehydrators using radial basis function (RBF neural networks

    Directory of Open Access Journals (Sweden)

    Tatar Afshin

    2016-03-01

    Full Text Available Raw natural gases usually contain water. It is very important to remove the water from these gases through dehydration processes due to economic reasons and safety considerations. One of the most important methods for water removal from these gases is using dehydration units which use Triethylene glycol (TEG. The TEG concentration at which all water is removed and dew point characteristics of mixture are two important parameters, which should be taken into account in TEG dehydration system. Hence, developing a reliable and accurate model to predict the performance of such a system seems to be very important in gas engineering operations. This study highlights the use of intelligent modeling techniques such as Multilayer perceptron (MLP and Radial Basis Function Neural Network (RBF-ANN to predict the equilibrium water dew point in a stream of natural gas based on the TEG concentration of stream and contractor temperature. Literature data set used in this study covers temperatures from 10 °C to 80 °C and TEG concentrations from 90.000% to 99.999%. Results showed that both models are accurate in prediction of experimental data and the MLP model gives more accurate predictions compared to RBF model.

  3. An Intelligent Approach to Educational Data: Performance Comparison of the Multilayer Perceptron and the Radial Basis Function Artificial Neural Networks

    Science.gov (United States)

    Kayri, Murat

    2015-01-01

    The objective of this study is twofold: (1) to investigate the factors that affect the success of university students by employing two artificial neural network methods (i.e., multilayer perceptron [MLP] and radial basis function [RBF]); and (2) to compare the effects of these methods on educational data in terms of predictive ability. The…

  4. Learning Errors by Radial Basis Function Neural Networks and Regularization Networks

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman; Vidnerová, Petra

    2009-01-01

    Roč. 1, č. 2 (2009), s. 49-57 ISSN 2005-4262 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : neural network * RBF networks * regularization * learning Subject RIV: IN - Informatics, Computer Science http://www.sersc.org/journals/IJGDC/vol2_no1/5.pdf

  5. Dynamic Fault Diagnosis for Semi-Batch Reactor under Closed-Loop Control via Independent Radial Basis Function Neural Network

    OpenAIRE

    Abdelkarim M. Ertiame; D. W. Yu; D. L. Yu; J. B. Gomm

    2015-01-01

    In this paper, a robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor, when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics, and using the weighted sum-squared prediction error as the residual. The Recursive Orthogonal Least Squares algorithm (ROLS) is emplo...

  6. Influence of the Training Methods in the Diagnosis of Multiple Sclerosis Using Radial Basis Functions Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Ángel Gutiérrez

    2015-04-01

    Full Text Available The data available in the average clinical study of a disease is very often small. This is one of the main obstacles in the application of neural networks to the classification of biological signals used for diagnosing diseases. A rule of thumb states that the number of parameters (weights that can be used for training a neural network should be around 15% of the available data, to avoid overlearning. This condition puts a limit on the dimension of the input space. Different authors have used different approaches to solve this problem, like eliminating redundancy in the data, preprocessing the data to find centers for the radial basis functions, or extracting a small number of features that were used as inputs. It is clear that the classification would be better the more features we could feed into the network. The approach utilized in this paper is incrementing the number of training elements with randomly expanding training sets. This way the number of original signals does not constraint the dimension of the input set in the radial basis network. Then we train the network using the method that minimizes the error function using the gradient descent algorithm and the method that uses the particle swarm optimization technique. A comparison between the two methods showed that for the same number of iterations on both methods, the particle swarm optimization was faster, it was learning to recognize only the sick people. On the other hand, the gradient method was not as good in general better at identifying those people.

  7. Decoupling control of a five-phase fault-tolerant permanent magnet motor by radial basis function neural network inverse

    Science.gov (United States)

    Chen, Qian; Liu, Guohai; Xu, Dezhi; Xu, Liang; Xu, Gaohong; Aamir, Nazir

    2018-05-01

    This paper proposes a new decoupled control for a five-phase in-wheel fault-tolerant permanent magnet (IW-FTPM) motor drive, in which radial basis function neural network inverse (RBF-NNI) and internal model control (IMC) are combined. The RBF-NNI system is introduced into original system to construct a pseudo-linear system, and IMC is used as a robust controller. Hence, the newly proposed control system incorporates the merits of the IMC and RBF-NNI methods. In order to verify the proposed strategy, an IW-FTPM motor drive is designed based on dSPACE real-time control platform. Then, the experimental results are offered to verify that the d-axis current and the rotor speed are successfully decoupled. Besides, the proposed motor drive exhibits strong robustness even under load torque disturbance.

  8. Robust and Stable Disturbance Observer of Servo System for Low Speed Operation Using the Radial Basis Function Network

    DEFF Research Database (Denmark)

    Lee, Kyo-Beum; Blaabjerg, Frede

    2005-01-01

    A new scheme to estimate the moment of inertia in the servo motor drive system in very low speed is proposed in this paper. The speed estimation scheme in most servo drive systems for low speed operation is sensitive to the variation of machine parameter, especially the moment of inertia....... To estimate the motor inertia value, the observer using the Radial Basis Function Network (RBFN) is applied. A control law for stabilizing the system and adaptive laws for updating both of the weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable...... in the sense of Lyapunov. The effectiveness of the proposed inertia estimation is verified by simulations and experiments. It is concluded that the speed control performance in low speed region is improved with the proposed disturbance observer using RBFN....

  9. Comparative Application of Radial Basis Function and Multilayer Perceptron Neural Networks to Predict Traffic Noise Pollution in Tehran Roads

    Directory of Open Access Journals (Sweden)

    Ali Mansourkhaki

    2018-01-01

    Full Text Available Noise pollution is a level of environmental noise which is considered as a disturbing and annoying phenomenon for human and wildlife. It is one of the environmental problems which has not been considered as harmful as the air and water pollution. Compared with other pollutants, the attempts to control noise pollution have largely been unsuccessful due to the inadequate knowledge of its effectson humans, as well as the lack of clear standards in previous years. However, with an increase of traveling vehicles, the adverse impact of increasing noise pollution on human health is progressively emerging. Hence, investigators all around the world are seeking to findnew approaches for predicting, estimating and controlling this problem and various models have been proposed. Recently, developing learning algorithms such as neural network has led to novel solutions for this challenge. These algorithms provide intelligent performance based on the situations and input data, enabling to obtain the best result for predicting noise level. In this study, two types of neural networks – multilayer perceptron and radial basis function – were developed for predicting equivalent continuous sound level (LA eq by measuring the traffivolume, average speed and percentage of heavy vehicles in some roads in west and northwest of Tehran. Then, their prediction results were compared based on the coefficienof determination (R 2 and the Mean Squared Error (MSE. Although both networks are of high accuracy in prediction of noise level, multilayer perceptron neural network based on selected criteria had a better performance.

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

    International Nuclear Information System (INIS)

    Vaziri, Nima; Hojabri, Alireza; Erfani, Ali; Monsefi, Mehrdad; Nilforooshan, Behnam

    2007-01-01

    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

  11. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network.

    Science.gov (United States)

    Falat, Lukas; Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  12. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Directory of Open Access Journals (Sweden)

    Lukas Falat

    2016-01-01

    Full Text Available This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process.

  13. Intelligent Soft Computing on Forex: Exchange Rates Forecasting with Hybrid Radial Basis Neural Network

    Science.gov (United States)

    Marcek, Dusan; Durisova, Maria

    2016-01-01

    This paper deals with application of quantitative soft computing prediction models into financial area as reliable and accurate prediction models can be very helpful in management decision-making process. The authors suggest a new hybrid neural network which is a combination of the standard RBF neural network, a genetic algorithm, and a moving average. The moving average is supposed to enhance the outputs of the network using the error part of the original neural network. Authors test the suggested model on high-frequency time series data of USD/CAD and examine the ability to forecast exchange rate values for the horizon of one day. To determine the forecasting efficiency, they perform a comparative statistical out-of-sample analysis of the tested model with autoregressive models and the standard neural network. They also incorporate genetic algorithm as an optimizing technique for adapting parameters of ANN which is then compared with standard backpropagation and backpropagation combined with K-means clustering algorithm. Finally, the authors find out that their suggested hybrid neural network is able to produce more accurate forecasts than the standard models and can be helpful in eliminating the risk of making the bad decision in decision-making process. PMID:26977450

  14. Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks

    Science.gov (United States)

    Meng, Qinggang; Lee, M. H.

    2007-03-01

    Advanced autonomous artificial systems will need incremental learning and adaptive abilities similar to those seen in humans. Knowledge from biology, psychology and neuroscience is now inspiring new approaches for systems that have sensory-motor capabilities and operate in complex environments. Eye/hand coordination is an important cross-modal cognitive function, and is also typical of many of the other coordinations that must be involved in the control and operation of embodied intelligent systems. This paper examines a biologically inspired approach for incrementally constructing compact mapping networks for eye/hand coordination. We present a simplified node-decoupled extended Kalman filter for radial basis function networks, and compare this with other learning algorithms. An experimental system consisting of a robot arm and a pan-and-tilt head with a colour camera is used to produce results and test the algorithms in this paper. We also present three approaches for adapting to structural changes during eye/hand coordination tasks, and the robustness of the algorithms under noise are investigated. The learning and adaptation approaches in this paper have similarities with current ideas about neural growth in the brains of humans and animals during tool-use, and infants during early cognitive development.

  15. [Application of wavelet transform-radial basis function neural network in NIRS for determination of rifampicin and isoniazide tablets].

    Science.gov (United States)

    Lu, Jia-hui; Zhang, Yi-bo; Zhang, Zhuo-yong; Meng, Qing-fan; Guo, Wei-liang; Teng, Li-rong

    2008-06-01

    A calibration model (WT-RBFNN) combination of wavelet transform (WT) and radial basis function neural network (RBFNN) was proposed for synchronous and rapid determination of rifampicin and isoniazide in Rifampicin and Isoniazide tablets by near infrared reflectance spectroscopy (NIRS). The approximation coefficients were used for input data in RBFNN. The network parameters including the number of hidden layer neurons and spread constant (SC) were investigated. WT-RBFNN model which compressed the original spectra data, removed the noise and the interference of background, and reduced the randomness, the capabilities of prediction were well optimized. The root mean square errors of prediction (RMSEP) for the determination of rifampicin and isoniazide obtained from the optimum WT-RBFNN model are 0.00639 and 0.00587, and the root mean square errors of cross-calibration (RMSECV) for them are 0.00604 and 0.00457, respectively which are superior to those obtained by the optimum RBFNN and PLS models. Regression coefficient (R) between NIRS predicted values and RP-HPLC values for rifampicin and isoniazide are 0.99522 and 0.99392, respectively and the relative error is lower than 2.300%. It was verified that WT-RBFNN model is a suitable approach to dealing with NIRS. The proposed WT-RBFNN model is convenient, and rapid and with no pollution for the determination of rifampicin and isoniazide tablets.

  16. Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

    Science.gov (United States)

    Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

    2010-02-01

    Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

  17. Intelligent Control of Welding Gun Pose for Pipeline Welding Robot Based on Improved Radial Basis Function Network and Expert System

    Directory of Open Access Journals (Sweden)

    Jingwen Tian

    2013-02-01

    Full Text Available Since the control system of the welding gun pose in whole-position welding is complicated and nonlinear, an intelligent control system of welding gun pose for a pipeline welding robot based on an improved radial basis function neural network (IRBFNN and expert system (ES is presented in this paper. The structure of the IRBFNN is constructed and the improved genetic algorithm is adopted to optimize the network structure. This control system makes full use of the characteristics of the IRBFNN and the ES. The ADXRS300 micro-mechanical gyro is used as the welding gun position sensor in this system. When the welding gun position is obtained, an appropriate pitch angle can be obtained through expert knowledge and the numeric reasoning capacity of the IRBFNN. ARM is used as the controller to drive the welding gun pitch angle step motor in order to adjust the pitch angle of the welding gun in real-time. The experiment results show that the intelligent control system of the welding gun pose using the IRBFNN and expert system is feasible and it enhances the welding quality. This system has wide prospects for application.

  18. Disturbance observer that uses radial basis function networks for the low speed control of a servo motor

    DEFF Research Database (Denmark)

    Lee, Kyo-Beum; Bae, C.H.; Blaabjerg, Frede

    2005-01-01

    A scheme to estimate the moment of inertia in a servo motor drive system at very low speed is proposed. The typical speed estimation scheme used in most servo systems operated at low speed is highly sensitive to variations in the moment of inertia. An observer that uses a radial basis function...

  19. Optimization of vehicle compartment low frequency noise based on Radial Basis Function Neuro-Network Approximation Model

    Directory of Open Access Journals (Sweden)

    HU Qi-guo

    2017-01-01

    Full Text Available For reducing the vehicle compartment low frequency noise, the Optimal Latin hypercube sampling method was applied to perform experimental design for sampling in the factorial design space. The thickness parameters of the panels with larger acoustic contribution was considered as factors, as well as the vehicle mass, seventh rank modal frequency of body, peak sound pressure of test point and sound pressure root-mean-square value as responses. By using the RBF(radial basis function neuro-network method, an approximation model of four responses about six factors was established. Further more, error analysis of established approximation model was performed in this paper. To optimize the panel’s thickness parameter, the adaptive simulated annealing algorithm was im-plemented. Optimization results show that the peak sound pressure of driver’s head was reduced by 4.45dB and 5.47dB at frequency 158HZ and 134Hz respec-tively. The test point pressure were significantly reduced at other frequency as well. The results indicate that through the optimization the vehicle interior cavity noise was reduced effectively, and the acoustical comfort of the vehicle was im-proved significantly.

  20. Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

    Science.gov (United States)

    Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

    2013-03-01

    Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

  1. Nonlinear Control of an Active Magnetic Bearing System Achieved Using a Fuzzy Control with Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Seng-Chi Chen

    2014-01-01

    Full Text Available Studies on active magnetic bearing (AMB systems are increasing in popularity and practical applications. Magnetic bearings cause less noise, friction, and vibration than the conventional mechanical bearings; however, the control of AMB systems requires further investigation. The magnetic force has a highly nonlinear relation to the control current and the air gap. This paper proposes an intelligent control method for positioning an AMB system that uses a neural fuzzy controller (NFC. The mathematical model of an AMB system comprises identification followed by collection of information from this system. A fuzzy logic controller (FLC, the parameters of which are adjusted using a radial basis function neural network (RBFNN, is applied to the unbalanced vibration in an AMB system. The AMB system exhibited a satisfactory control performance, with low overshoot, and produced improved transient and steady-state responses under various operating conditions. The NFC has been verified on a prototype AMB system. The proposed controller can be feasibly applied to AMB systems exposed to various external disturbances; demonstrating the effectiveness of the NFC with self-learning and self-improving capacities is proven.

  2. Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

    Science.gov (United States)

    DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

    2016-03-29

    We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

  3. The Matlab Radial Basis Function Toolbox

    Directory of Open Access Journals (Sweden)

    Scott A. Sarra

    2017-03-01

    Full Text Available Radial Basis Function (RBF methods are important tools for scattered data interpolation and for the solution of Partial Differential Equations in complexly shaped domains. The most straight forward approach used to evaluate the methods involves solving a linear system which is typically poorly conditioned. The Matlab Radial Basis Function toolbox features a regularization method for the ill-conditioned system, extended precision floating point arithmetic, and symmetry exploitation for the purpose of reducing flop counts of the associated numerical linear algebra algorithms.

  4. Designing an artificial neural network using radial basis function to model exergetic efficiency of nanofluids in mini double pipe heat exchanger

    Science.gov (United States)

    Ghasemi, Nahid; Aghayari, Reza; Maddah, Heydar

    2018-06-01

    The present study aims at predicting and optimizing exergetic efficiency of TiO2-Al2O3/water nanofluid at different Reynolds numbers, volume fractions and twisted ratios using Artificial Neural Networks (ANN) and experimental data. Central Composite Design (CCD) and cascade Radial Basis Function (RBF) were used to display the significant levels of the analyzed factors on the exergetic efficiency. The size of TiO2-Al2O3/water nanocomposite was 20-70 nm. The parameters of ANN model were adapted by a training algorithm of radial basis function (RBF) with a wide range of experimental data set. Total mean square error and correlation coefficient were used to evaluate the results which the best result was obtained from double layer perceptron neural network with 30 neurons in which total Mean Square Error(MSE) and correlation coefficient (R2) were equal to 0.002 and 0.999, respectively. This indicated successful prediction of the network. Moreover, the proposed equation for predicting exergetic efficiency was extremely successful. According to the optimal curves, the optimum designing parameters of double pipe heat exchanger with inner twisted tape and nanofluid under the constrains of exergetic efficiency 0.937 are found to be Reynolds number 2500, twisted ratio 2.5 and volume fraction( v/v%) 0.05.

  5. Fast radial basis functions for engineering applications

    CERN Document Server

    Biancolini, Marco Evangelos

    2017-01-01

    This book presents the first “How To” guide to the use of radial basis functions (RBF). It provides a clear vision of their potential, an overview of ready-for-use computational tools and precise guidelines to implement new engineering applications of RBF. Radial basis functions (RBF) are a mathematical tool mature enough for useful engineering applications. Their mathematical foundation is well established and the tool has proven to be effective in many fields, as the mathematical framework can be adapted in several ways. A candidate application can be faced considering the features of RBF:  multidimensional space (including 2D and 3D), numerous radial functions available, global and compact support, interpolation/regression. This great flexibility makes RBF attractive – and their great potential has only been partially discovered. This is because of the difficulty in taking a first step toward RBF as they are not commonly part of engineers’ cultural background, but also due to the numerical complex...

  6. Doubly stochastic radial basis function methods

    Science.gov (United States)

    Yang, Fenglian; Yan, Liang; Ling, Leevan

    2018-06-01

    We propose a doubly stochastic radial basis function (DSRBF) method for function recoveries. Instead of a constant, we treat the RBF shape parameters as stochastic variables whose distribution were determined by a stochastic leave-one-out cross validation (LOOCV) estimation. A careful operation count is provided in order to determine the ranges of all the parameters in our methods. The overhead cost for setting up the proposed DSRBF method is O (n2) for function recovery problems with n basis. Numerical experiments confirm that the proposed method not only outperforms constant shape parameter formulation (in terms of accuracy with comparable computational cost) but also the optimal LOOCV formulation (in terms of both accuracy and computational cost).

  7. Spherical radial basis functions, theory and applications

    CERN Document Server

    Hubbert, Simon; Morton, Tanya M

    2015-01-01

    This book is the first to be devoted to the theory and applications of spherical (radial) basis functions (SBFs), which is rapidly emerging as one of the most promising techniques for solving problems where approximations are needed on the surface of a sphere. The aim of the book is to provide enough theoretical and practical details for the reader to be able to implement the SBF methods to solve real world problems. The authors stress the close connection between the theory of SBFs and that of the more well-known family of radial basis functions (RBFs), which are well-established tools for solving approximation theory problems on more general domains. The unique solvability of the SBF interpolation method for data fitting problems is established and an in-depth investigation of its accuracy is provided. Two chapters are devoted to partial differential equations (PDEs). One deals with the practical implementation of an SBF-based solution to an elliptic PDE and another which describes an SBF approach for solvi...

  8. Neural network of Gaussian radial basis functions applied to the problem of identification of nuclear accidents in a PWR nuclear power plant

    International Nuclear Information System (INIS)

    Gomes, Carla Regina; Canedo Medeiros, Jose Antonio Carlos

    2015-01-01

    Highlights: • It is presented a new method based on Artificial Neural Network (ANN) developed to deal with accident identification in PWR nuclear power plants. • Obtained results have shown the efficiency of the referred technique. • Results obtained with this method are as good as or even better to similar optimization tools available in the literature. - Abstract: The task of monitoring a nuclear power plant consists on determining, continuously and in real time, the state of the plant’s systems in such a way to give indications of abnormalities to the operators and enable them to recognize anomalies in system behavior. The monitoring is based on readings of a large number of meters and alarm indicators which are located in the main control room of the facility. On the occurrence of a transient or of an accident on the nuclear power plant, even the most experienced operators can be confronted with conflicting indications due to the interactions between the various components of the plant systems; since a disturbance of a system can cause disturbances on another plant system, thus the operator may not be able to distinguish what is cause and what is the effect. This cognitive overload, to which operators are submitted, causes a difficulty in understanding clearly the indication of an abnormality in its initial phase of development and in taking the appropriate and immediate corrective actions to face the system failure. With this in mind, computerized monitoring systems based on artificial intelligence that could help the operators to detect and diagnose these failures have been devised and have been the subject of research. Among the techniques that can be used in such development, radial basis functions (RBFs) neural networks play an important role due to the fact that they are able to provide good approximations to functions of a finite number of real variables. This paper aims to present an application of a neural network of Gaussian radial basis

  9. Generalized unscented Kalman filtering based radial basis function neural network for the prediction of ground radioactivity time series with missing data

    International Nuclear Information System (INIS)

    Wu Xue-Dong; Liu Wei-Ting; Zhu Zhi-Yu; Wang Yao-Nan

    2011-01-01

    On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering (EKF) and the unscented Kalman filtering (UKF), which were shortened as GEKF and GUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network (RBFNN) prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent. (geophysics, astronomy, and astrophysics)

  10. A stock market forecasting model combining two-directional two-dimensional principal component analysis and radial basis function neural network.

    Science.gov (United States)

    Guo, Zhiqiang; Wang, Huaiqing; Yang, Jie; Miller, David J

    2015-01-01

    In this paper, we propose and implement a hybrid model combining two-directional two-dimensional principal component analysis ((2D)2PCA) and a Radial Basis Function Neural Network (RBFNN) to forecast stock market behavior. First, 36 stock market technical variables are selected as the input features, and a sliding window is used to obtain the input data of the model. Next, (2D)2PCA is utilized to reduce the dimension of the data and extract its intrinsic features. Finally, an RBFNN accepts the data processed by (2D)2PCA to forecast the next day's stock price or movement. The proposed model is used on the Shanghai stock market index, and the experiments show that the model achieves a good level of fitness. The proposed model is then compared with one that uses the traditional dimension reduction method principal component analysis (PCA) and independent component analysis (ICA). The empirical results show that the proposed model outperforms the PCA-based model, as well as alternative models based on ICA and on the multilayer perceptron.

  11. Multi-step ahead nonlinear identification of Lorenz's chaotic system using radial basis neural network with learning by clustering and particle swarm optimization

    International Nuclear Information System (INIS)

    Guerra, Fabio A.; Coelho, Leandro dos S.

    2008-01-01

    An important problem in engineering is the identification of nonlinear systems, among them radial basis function neural networks (RBF-NN) using Gaussian activation functions models, which have received particular attention due to their potential to approximate nonlinear behavior. Several design methods have been proposed for choosing the centers and spread of Gaussian functions and training the RBF-NN. The selection of RBF-NN parameters such as centers, spreads, and weights can be understood as a system identification problem. This paper presents a hybrid training approach based on clustering methods (k-means and c-means) to tune the centers of Gaussian functions used in the hidden layer of RBF-NNs. This design also uses particle swarm optimization (PSO) for centers (local clustering search method) and spread tuning, and the Penrose-Moore pseudoinverse for the adjustment of RBF-NN weight outputs. Simulations involving this RBF-NN design to identify Lorenz's chaotic system indicate that the performance of the proposed method is superior to that of the conventional RBF-NN trained for k-means and the Penrose-Moore pseudoinverse for multi-step ahead forecasting

  12. Study on Magneto-Hydro-Dynamics Disturbance Signal Feature Classification Using Improved S-Transform Algorithm and Radial Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Nan YU

    2014-09-01

    Full Text Available The interference signal in magneto-hydro-dynamics (MHD may be the disturbance from the power supply, the equipment itself, or the electromagnetic radiation. Interference signal mixed in normal signal, brings difficulties for signal analysis and processing. Recently proposed S-Transform algorithm combines advantages of short time Fourier transform and wavelet transform. It uses Fourier kernel and wavelet like Gauss window whose width is inversely proportional to the frequency. Therefore, S-Transform algorithm not only preserves the phase information of the signals but also has variable resolution like wavelet transform. This paper proposes a new method to establish a MHD signal classifier using S-transform algorithm and radial basis function neural network (RBFNN. Because RBFNN centers ascertained by k-means clustering algorithm probably are the local optimum, this paper analyzes the characteristics of k-means clustering algorithm and proposes an improved k-means clustering algorithm called GCW (Group-cluster-weight k-means clustering algorithm to improve the centers distribution. The experiment results show that the improvement greatly enhances the RBFNN performance.

  13. Predictive modelling of grain size distributions from marine electromagnetic profiling data using end-member analysis and a radial basis function network

    Science.gov (United States)

    Baasch, B.; M"uller, H.; von Dobeneck, T.

    2018-04-01

    In this work we present a new methodology to predict grain-size distributions from geophysical data. Specifically, electric conductivity and magnetic susceptibility of seafloor sediments recovered from electromagnetic profiling data are used to predict grain-size distributions along shelf-wide survey lines. Field data from the NW Iberian shelf are investigated and reveal a strong relation between the electromagnetic properties and grain-size distribution. The here presented workflow combines unsupervised and supervised machine learning techniques. Nonnegative matrix factorisation is used to determine grain-size end-members from sediment surface samples. Four end-members were found which well represent the variety of sediments in the study area. A radial-basis function network modified for prediction of compositional data is then used to estimate the abundances of these end-members from the electromagnetic properties. The end-members together with their predicted abundances are finally back transformed to grain-size distributions. A minimum spatial variation constraint is implemented in the training of the network to avoid overfitting and to respect the spatial distribution of sediment patterns. The predicted models are tested via leave-one-out cross-validation revealing high prediction accuracy with coefficients of determination (R2) between 0.76 and 0.89. The predicted grain-size distributions represent the well-known sediment facies and patterns on the NW Iberian shelf and provide new insights into their distribution, transition and dynamics. This study suggests that electromagnetic benthic profiling in combination with machine learning techniques is a powerful tool to estimate grain-size distribution of marine sediments.

  14. Multi nodal load forecasting in electric power systems using a radial basis neural network; Previsao de carga multinodal em sistemas eletricos de potencia usando uma rede neural de base radial

    Energy Technology Data Exchange (ETDEWEB)

    Altran, A.B.; Lotufo, A.D.P.; Minussi, C.R. [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Ilha Solteira, SP (Brazil). Dept. de Engenharia Eletrica], Emails: lealtran@yahoo.com.br, annadiva@dee.feis.unesp.br, minussi@dee.feis.unesp.br; Lopes, M.L.M. [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Ilha Solteira, SP (Brazil). Dept. de Matematica], E-mail: mara@mat.feis.unesp.br

    2009-07-01

    This paper presents a methodology for electrical load forecasting, using radial base functions as activation function in artificial neural networks with the training by backpropagation algorithm. This methodology is applied to short term electrical load forecasting (24 h ahead). Therefore, results are presented analyzing the use of radial base functions substituting the sigmoid function as activation function in multilayer perceptron neural networks. However, the main contribution of this paper is the proposal of a new formulation of load forecasting dedicated to the forecasting in several points of the electrical network, as well as considering several types of users (residential, commercial, industrial). It deals with the MLF (Multimodal Load Forecasting), with the same processing time as the GLF (Global Load Forecasting). (author)

  15. Point Set Denoising Using Bootstrap-Based Radial Basis Function.

    Directory of Open Access Journals (Sweden)

    Khang Jie Liew

    Full Text Available This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.

  16. Point Set Denoising Using Bootstrap-Based Radial Basis Function.

    Science.gov (United States)

    Liew, Khang Jie; Ramli, Ahmad; Abd Majid, Ahmad

    2016-01-01

    This paper examines the application of a bootstrap test error estimation of radial basis functions, specifically thin-plate spline fitting, in surface smoothing. The presence of noisy data is a common issue of the point set model that is generated from 3D scanning devices, and hence, point set denoising is one of the main concerns in point set modelling. Bootstrap test error estimation, which is applied when searching for the smoothing parameters of radial basis functions, is revisited. The main contribution of this paper is a smoothing algorithm that relies on a bootstrap-based radial basis function. The proposed method incorporates a k-nearest neighbour search and then projects the point set to the approximated thin-plate spline surface. Therefore, the denoising process is achieved, and the features are well preserved. A comparison of the proposed method with other smoothing methods is also carried out in this study.

  17. Radial Basis Function Based Quadrature over Smooth Surfaces

    Science.gov (United States)

    2016-03-24

    Radial Basis Functions φ(r) Piecewise Smooth (Conditionally Positive Definite) MN Monomial |r|2m+1 TPS thin plate spline |r|2mln|r| Infinitely Smooth...smooth surfaces using polynomial interpolants, while [27] couples Thin - Plate Spline interpolation (see table 1) with Green’s integral formula [29

  18. Surface interpolation with radial basis functions for medical imaging

    International Nuclear Information System (INIS)

    Carr, J.C.; Beatson, R.K.; Fright, W.R.

    1997-01-01

    Radial basis functions are presented as a practical solution to the problem of interpolating incomplete surfaces derived from three-dimensional (3-D) medical graphics. The specific application considered is the design of cranial implants for the repair of defects, usually holes, in the skull. Radial basis functions impose few restrictions on the geometry of the interpolation centers and are suited to problems where interpolation centers do not form a regular grid. However, their high computational requirements have previously limited their use to problems where the number of interpolation centers is small (<300). Recently developed fast evaluation techniques have overcome these limitations and made radial basis interpolation a practical approach for larger data sets. In this paper radial basis functions are fitted to depth-maps of the skull's surface, obtained from X-ray computed tomography (CT) data using ray-tracing techniques. They are used to smoothly interpolate the surface of the skull across defect regions. The resulting mathematical description of the skull's surface can be evaluated at any desired resolution to be rendered on a graphics workstation or to generate instructions for operating a computer numerically controlled (CNC) mill

  19. Radial basis function and its application in tourism management

    Science.gov (United States)

    Hu, Shan-Feng; Zhu, Hong-Bin; Zhao, Lei

    2018-05-01

    In this work, several applications and the performances of the radial basis function (RBF) are briefly reviewed at first. After that, the binomial function combined with three different RBFs including the multiquadric (MQ), inverse quadric (IQ) and inverse multiquadric (IMQ) distributions are adopted to model the tourism data of Huangshan in China. Simulation results showed that all the models match very well with the sample data. It is found that among the three models, the IMQ-RBF model is more suitable for forecasting the tourist flow.

  20. Separation and Determination of Honokiol and Magnolol in Chinese Traditional Medicines by Capillary Electrophoresis with the Application of Response Surface Methodology and Radial Basis Function Neural Network

    Science.gov (United States)

    Han, Ping; Luan, Feng; Yan, Xizu; Gao, Yuan; Liu, Huitao

    2012-01-01

    A method for the separation and determination of honokiol and magnolol in Magnolia officinalis and its medicinal preparation is developed by capillary zone electrophoresis and response surface methodology. The concentration of borate, content of organic modifier, and applied voltage are selected as variables. The optimized conditions (i.e., 16 mmol/L sodium tetraborate at pH 10.0, 11% methanol, applied voltage of 25 kV and UV detection at 210 nm) are obtained and successfully applied to the analysis of honokiol and magnolol in Magnolia officinalis and Huoxiang Zhengqi Liquid. Good separation is achieved within 6 min. The limits of detection are 1.67 µg/mL for honokiol and 0.83 µg/mL for magnolol, respectively. In addition, an artificial neural network with “3-7-1” structure based on the ratio of peak resolution to the migration time of the later component (Rs/t) given by Box-Behnken design is also reported, and the predicted results are in good agreement with the values given by the mathematic software and the experimental results. PMID:22291059

  1. Recent advances in radial basis function collocation methods

    CERN Document Server

    Chen, Wen; Chen, C S

    2014-01-01

    This book surveys the latest advances in radial basis function (RBF) meshless collocation methods which emphasis on recent novel kernel RBFs and new numerical schemes for solving partial differential equations. The RBF collocation methods are inherently free of integration and mesh, and avoid tedious mesh generation involved in standard finite element and boundary element methods. This book focuses primarily on the numerical algorithms, engineering applications, and highlights a large class of novel boundary-type RBF meshless collocation methods. These methods have shown a clear edge over the traditional numerical techniques especially for problems involving infinite domain, moving boundary, thin-walled structures, and inverse problems. Due to the rapid development in RBF meshless collocation methods, there is a need to summarize all these new materials so that they are available to scientists, engineers, and graduate students who are interest to apply these newly developed methods for solving real world’s ...

  2. The Gaussian radial basis function method for plasma kinetic theory

    Energy Technology Data Exchange (ETDEWEB)

    Hirvijoki, E., E-mail: eero.hirvijoki@chalmers.se [Department of Applied Physics, Chalmers University of Technology, SE-41296 Gothenburg (Sweden); Candy, J.; Belli, E. [General Atomics, PO Box 85608, San Diego, CA 92186-5608 (United States); Embréus, O. [Department of Applied Physics, Chalmers University of Technology, SE-41296 Gothenburg (Sweden)

    2015-10-30

    Description of a magnetized plasma involves the Vlasov equation supplemented with the non-linear Fokker–Planck collision operator. For non-Maxwellian distributions, the collision operator, however, is difficult to compute. In this Letter, we introduce Gaussian Radial Basis Functions (RBFs) to discretize the velocity space of the entire kinetic system, and give the corresponding analytical expressions for the Vlasov and collision operator. Outlining the general theory, we also highlight the connection to plasma fluid theories, and give 2D and 3D numerical solutions of the non-linear Fokker–Planck equation. Applications are anticipated in both astrophysical and laboratory plasmas. - Highlights: • A radically new method to address the velocity space discretization of the non-linear kinetic equation of plasmas. • Elegant and physically intuitive, flexible and mesh-free. • Demonstration of numerical solution of both 2-D and 3-D non-linear Fokker–Planck relaxation problem.

  3. Adaptive radial basis function mesh deformation using data reduction

    Science.gov (United States)

    Gillebaart, T.; Blom, D. S.; van Zuijlen, A. H.; Bijl, H.

    2016-09-01

    Radial Basis Function (RBF) mesh deformation is one of the most robust mesh deformation methods available. Using the greedy (data reduction) method in combination with an explicit boundary correction, results in an efficient method as shown in literature. However, to ensure the method remains robust, two issues are addressed: 1) how to ensure that the set of control points remains an accurate representation of the geometry in time and 2) how to use/automate the explicit boundary correction, while ensuring a high mesh quality. In this paper, we propose an adaptive RBF mesh deformation method, which ensures the set of control points always represents the geometry/displacement up to a certain (user-specified) criteria, by keeping track of the boundary error throughout the simulation and re-selecting when needed. Opposed to the unit displacement and prescribed displacement selection methods, the adaptive method is more robust, user-independent and efficient, for the cases considered. Secondly, the analysis of a single high aspect ratio cell is used to formulate an equation for the correction radius needed, depending on the characteristics of the correction function used, maximum aspect ratio, minimum first cell height and boundary error. Based on the analysis two new radial basis correction functions are derived and proposed. This proposed automated procedure is verified while varying the correction function, Reynolds number (and thus first cell height and aspect ratio) and boundary error. Finally, the parallel efficiency is studied for the two adaptive methods, unit displacement and prescribed displacement for both the CPU as well as the memory formulation with a 2D oscillating and translating airfoil with oscillating flap, a 3D flexible locally deforming tube and deforming wind turbine blade. Generally, the memory formulation requires less work (due to the large amount of work required for evaluating RBF's), but the parallel efficiency reduces due to the limited

  4. Meshfree Local Radial Basis Function Collocation Method with Image Nodes

    Energy Technology Data Exchange (ETDEWEB)

    Baek, Seung Ki; Kim, Minjae [Pukyong National University, Busan (Korea, Republic of)

    2017-07-15

    We numerically solve two-dimensional heat diffusion problems by using a simple variant of the meshfree local radial-basis function (RBF) collocation method. The main idea is to include an additional set of sample nodes outside the problem domain, similarly to the method of images in electrostatics, to perform collocation on the domain boundaries. We can thereby take into account the temperature profile as well as its gradients specified by boundary conditions at the same time, which holds true even for a node where two or more boundaries meet with different boundary conditions. We argue that the image method is computationally efficient when combined with the local RBF collocation method, whereas the addition of image nodes becomes very costly in case of the global collocation. We apply our modified method to a benchmark test of a boundary value problem, and find that this simple modification reduces the maximum error from the analytic solution significantly. The reduction is small for an initial value problem with simpler boundary conditions. We observe increased numerical instability, which has to be compensated for by a sufficient number of sample nodes and/or more careful parameter choices for time integration.

  5. Global sensitivity analysis using a Gaussian Radial Basis Function metamodel

    International Nuclear Information System (INIS)

    Wu, Zeping; Wang, Donghui; Okolo N, Patrick; Hu, Fan; Zhang, Weihua

    2016-01-01

    Sensitivity analysis plays an important role in exploring the actual impact of adjustable parameters on response variables. Amongst the wide range of documented studies on sensitivity measures and analysis, Sobol' indices have received greater portion of attention due to the fact that they can provide accurate information for most models. In this paper, a novel analytical expression to compute the Sobol' indices is derived by introducing a method which uses the Gaussian Radial Basis Function to build metamodels of computationally expensive computer codes. Performance of the proposed method is validated against various analytical functions and also a structural simulation scenario. Results demonstrate that the proposed method is an efficient approach, requiring a computational cost of one to two orders of magnitude less when compared to the traditional Quasi Monte Carlo-based evaluation of Sobol' indices. - Highlights: • RBF based sensitivity analysis method is proposed. • Sobol' decomposition of Gaussian RBF metamodel is obtained. • Sobol' indices of Gaussian RBF metamodel are derived based on the decomposition. • The efficiency of proposed method is validated by some numerical examples.

  6. Pricing and simulation for real estate index options: Radial basis point interpolation

    Science.gov (United States)

    Gong, Pu; Zou, Dong; Wang, Jiayue

    2018-06-01

    This study employs the meshfree radial basis point interpolation (RBPI) for pricing real estate derivatives contingent on real estate index. This method combines radial and polynomial basis functions, which can guarantee the interpolation scheme with Kronecker property and effectively improve accuracy. An exponential change of variables, a mesh refinement algorithm and the Richardson extrapolation are employed in this study to implement the RBPI. Numerical results are presented to examine the computational efficiency and accuracy of our method.

  7. DATA CLASSIFICATION WITH NEURAL CLASSIFIER USING RADIAL BASIS FUNCTION WITH DATA REDUCTION USING HIERARCHICAL CLUSTERING

    Directory of Open Access Journals (Sweden)

    M. Safish Mary

    2012-04-01

    Full Text Available Classification of large amount of data is a time consuming process but crucial for analysis and decision making. Radial Basis Function networks are widely used for classification and regression analysis. In this paper, we have studied the performance of RBF neural networks to classify the sales of cars based on the demand, using kernel density estimation algorithm which produces classification accuracy comparable to data classification accuracy provided by support vector machines. In this paper, we have proposed a new instance based data selection method where redundant instances are removed with help of a threshold thus improving the time complexity with improved classification accuracy. The instance based selection of the data set will help reduce the number of clusters formed thereby reduces the number of centers considered for building the RBF network. Further the efficiency of the training is improved by applying a hierarchical clustering technique to reduce the number of clusters formed at every step. The paper explains the algorithm used for classification and for conditioning the data. It also explains the complexities involved in classification of sales data for analysis and decision-making.

  8. Developing equivalent circuits for radial distribution networks

    Energy Technology Data Exchange (ETDEWEB)

    Prada, Ricardo; Coelho, Agnelo; Rodrigues, Anselmo [Catholic University of Rio de Janeiro (PUC-Rio), RJ (Brazil). Dept. of Electrical Engineering], Emails: prada@ele.puc-rio.br, agnelo@ele.puc-rio.br, nebulok_99@yahoo.com; Silva, Maria da Guia da [Federal University of Maranhao, Sao Luiz, MA (Brazil). Dept. of Electrical Engineering

    2009-07-01

    This paper presents a method for evaluating External Equivalent in Electric Distribution Networks (EDN).The proposed method has as its main objectives the reduction of the computational costs in distribution network reconfiguration, investigation of the optimal allocation of banks of capacitors, investigation of the allocation of distributed generation, etc. In these sorts of problems a large number of alternative projects must be assessed in order to identify the optimal solution. The optimal solution comes up with the voltage level in the load points within specified limits. Consequently, the EDN must retain the external network load points but without major increasing in the dimension of the equivalent circuit. The proposed method has been tested and validated in a substation of the Electricity Utility of Maranhao - CEMAR, in Brazil. (author)

  9. Exponential Convergence for Numerical Solution of Integral Equations Using Radial Basis Functions

    Directory of Open Access Journals (Sweden)

    Zakieh Avazzadeh

    2014-01-01

    Full Text Available We solve some different type of Urysohn integral equations by using the radial basis functions. These types include the linear and nonlinear Fredholm, Volterra, and mixed Volterra-Fredholm integral equations. Our main aim is to investigate the rate of convergence to solve these equations using the radial basis functions which have normic structure that utilize approximation in higher dimensions. Of course, the use of this method often leads to ill-posed systems. Thus we propose an algorithm to improve the results. Numerical results show that this method leads to the exponential convergence for solving integral equations as it was already confirmed for partial and ordinary differential equations.

  10. Computer network defense through radial wave functions

    Science.gov (United States)

    Malloy, Ian J.

    The purpose of this research is to synthesize basic and fundamental findings in quantum computing, as applied to the attack and defense of conventional computer networks. The concept focuses on uses of radio waves as a shield for, and attack against traditional computers. A logic bomb is analogous to a landmine in a computer network, and if one was to implement it as non-trivial mitigation, it will aid computer network defense. As has been seen in kinetic warfare, the use of landmines has been devastating to geopolitical regions in that they are severely difficult for a civilian to avoid triggering given the unknown position of a landmine. Thus, the importance of understanding a logic bomb is relevant and has corollaries to quantum mechanics as well. The research synthesizes quantum logic phase shifts in certain respects using the Dynamic Data Exchange protocol in software written for this work, as well as a C-NOT gate applied to a virtual quantum circuit environment by implementing a Quantum Fourier Transform. The research focus applies the principles of coherence and entanglement from quantum physics, the concept of expert systems in artificial intelligence, principles of prime number based cryptography with trapdoor functions, and modeling radio wave propagation against an event from unknown parameters. This comes as a program relying on the artificial intelligence concept of an expert system in conjunction with trigger events for a trapdoor function relying on infinite recursion, as well as system mechanics for elliptic curve cryptography along orbital angular momenta. Here trapdoor both denotes the form of cipher, as well as the implied relationship to logic bombs.

  11. New Method for Mesh Moving Based on Radial Basis Function Interpolation

    NARCIS (Netherlands)

    De Boer, A.; Van der Schoot, M.S.; Bijl, H.

    2006-01-01

    A new point-by-point mesh movement algorithm is developed for the deformation of unstructured grids. The method is based on using radial basis function, RBFs, to interpolate the displacements of the boundary nodes to the whole flow mesh. A small system of equations has to be solved, only involving

  12. Automatic Curve Fitting Based on Radial Basis Functions and a Hierarchical Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    G. Trejo-Caballero

    2015-01-01

    Full Text Available Curve fitting is a very challenging problem that arises in a wide variety of scientific and engineering applications. Given a set of data points, possibly noisy, the goal is to build a compact representation of the curve that corresponds to the best estimate of the unknown underlying relationship between two variables. Despite the large number of methods available to tackle this problem, it remains challenging and elusive. In this paper, a new method to tackle such problem using strictly a linear combination of radial basis functions (RBFs is proposed. To be more specific, we divide the parameter search space into linear and nonlinear parameter subspaces. We use a hierarchical genetic algorithm (HGA to minimize a model selection criterion, which allows us to automatically and simultaneously determine the nonlinear parameters and then, by the least-squares method through Singular Value Decomposition method, to compute the linear parameters. The method is fully automatic and does not require subjective parameters, for example, smooth factor or centre locations, to perform the solution. In order to validate the efficacy of our approach, we perform an experimental study with several tests on benchmarks smooth functions. A comparative analysis with two successful methods based on RBF networks has been included.

  13. PERAMALAN DERET WAKTU MENGGUNAKAN MODEL FUNGSI BASIS RADIAL (RBF DAN AUTO REGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA

    Directory of Open Access Journals (Sweden)

    DT Wiyanti

    2013-07-01

    Full Text Available Salah satu metode peramalan yang paling dikembangkan saat ini adalah time series, yakni menggunakan pendekatan kuantitatif dengan data masa lampau yang dijadikan acuan untuk peramalan masa depan. Berbagai penelitian telah mengusulkan metode-metode untuk menyelesaikan time series, di antaranya statistik, jaringan syaraf, wavelet, dan sistem fuzzy. Metode-metode tersebut memiliki kekurangan dan keunggulan yang berbeda. Namun permasalahan yang ada dalam dunia nyata merupakan masalah yang kompleks. Satu metode saja mungkin tidak mampu mengatasi masalah tersebut dengan baik. Dalam artikel ini dibahas penggabungan dua buah metode yaitu Auto Regressive Integrated Moving Average (ARIMA dan Radial Basis Function (RBF. Alasan penggabungan kedua metode ini adalah karena adanya asumsi bahwa metode tunggal tidak dapat secara total mengidentifikasi semua karakteristik time series. Pada artikel ini dibahas peramalan terhadap data Indeks Harga Perdagangan Besar (IHPB dan data inflasi komoditi Indonesia; kedua data berada pada rentang tahun 2006 hingga beberapa bulan di tahun 2012. Kedua data tersebut masing-masing memiliki enam variabel. Hasil peramalan metode ARIMA-RBF dibandingkan dengan metode ARIMA dan metode RBF secara individual. Hasil analisa menunjukkan bahwa dengan metode penggabungan ARIMA dan RBF, model yang diberikan memiliki hasil yang lebih akurat dibandingkan dengan penggunaan salah satu metode saja. Hal ini terlihat dalam visual plot, MAPE, dan RMSE dari semua variabel pada dua data uji coba. The accuracy of time series forecasting is the subject of many decision-making processes. Time series use a quantitative approach to employ data from the past to make forecast for the future. Many researches have proposed several methods to solve time series, such as using statistics, neural networks, wavelets, and fuzzy systems. These methods have different advantages and disadvantages. But often the problem in the real world is just too complex that a

  14. Modeling multivariate time series on manifolds with skew radial basis functions.

    Science.gov (United States)

    Jamshidi, Arta A; Kirby, Michael J

    2011-01-01

    We present an approach for constructing nonlinear empirical mappings from high-dimensional domains to multivariate ranges. We employ radial basis functions and skew radial basis functions for constructing a model using data that are potentially scattered or sparse. The algorithm progresses iteratively, adding a new function at each step to refine the model. The placement of the functions is driven by a statistical hypothesis test that accounts for correlation in the multivariate range variables. The test is applied on training and validation data and reveals nonstatistical or geometric structure when it fails. At each step, the added function is fit to data contained in a spatiotemporally defined local region to determine the parameters--in particular, the scale of the local model. The scale of the function is determined by the zero crossings of the autocorrelation function of the residuals. The model parameters and the number of basis functions are determined automatically from the given data, and there is no need to initialize any ad hoc parameters save for the selection of the skew radial basis functions. Compactly supported skew radial basis functions are employed to improve model accuracy, order, and convergence properties. The extension of the algorithm to higher-dimensional ranges produces reduced-order models by exploiting the existence of correlation in the range variable data. Structure is tested not just in a single time series but between all pairs of time series. We illustrate the new methodologies using several illustrative problems, including modeling data on manifolds and the prediction of chaotic time series.

  15. Reconfiguration of face expressions based on the discrete capture data of radial basis function interpolation

    Institute of Scientific and Technical Information of China (English)

    ZHENG Guangguo; ZHOU Dongsheng; WEI Xiaopeng; ZHANG Qiang

    2012-01-01

    Compactly supported radial basis function can enable the coefficient matrix of solving weigh linear system to have a sparse banded structure, thereby reducing the complexity of the algorithm. Firstly, based on the compactly supported radial basis function, the paper makes the complex quadratic function (Multiquadric, MQ for short) to be transformed and proposes a class of compactly supported MQ function. Secondly, the paper describes a method that interpolates discrete motion capture data to solve the motion vectors of the interpolation points and they are used in facial expression reconstruction. Finally, according to this characteris- tic of the uneven distribution of the face markers, the markers are numbered and grouped in accordance with the density level, and then be interpolated in line with each group. The approach not only ensures the accuracy of the deformation of face local area and smoothness, but also reduces the time complexity of computing.

  16. Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

    Science.gov (United States)

    Hoomod, Haider K.; Kareem Jebur, Tuka

    2018-05-01

    Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

  17. 基于径向基神经网络-遗传算法的海流能水轮机叶片翼型优化%Optimization of hydrofoil for marine current turbine based on radial basis function neural network and genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    朱国俊; 冯建军; 郭鹏程; 罗兴锜

    2014-01-01

    , the Bezier curve was used to parameterize the hydrofoil. The Latin Hypercube experiment design method was used to select the sample points in the design space which were used for training the Radial Basis Function neural network. The hydrodynamic performance for each sample was calculated by the computational fluid dynamic method, and then the Radial Basis Function neural network would be trained by these sample points. After the neural network had been trained, the multi-point optimization method of hydrofoil was solved by combining the NSGA-II method and the Radial Basis Function neural network. The method mentioned above was applied to the optimal design of NACA63-815 hydrofoil, and the optimization problems of the hydrofoil in three typical conditions in which the attack angle is 0, 6º and 12º were mainly studied in this paper. After optimization, two optimized hydrofoils were selected in the Pareto solution to compare with initial, which were named Optimal A and Optimal B. According to the CFD simulation, the optimized hydrofoil’s performance was gotten and compared with the initial hydrofoil. By comparison, it was found that the drag coefficient of the optimized hydrofoil in the three conditions are less than or equal to the initial. Moreover, the lift-drag ratios of the Optimal A hydrofoil in which the attack angles is 0, 6° and 12° have been improve by 4.6%, 4.4%and 22.8%respectively. And the lift-drag ratios of the Optimal B hydrofoils have also been improved by 6.6%, 3.8%and 16.6%respectively. In addition, according to the comparison of the optimized and initial hydrofoil’s pressure coefficient at the 12°attack angle, it can be found that the optimized hydrofoil can effectively suppress the stall phenomenon. Finally, two conclusions can be drawn from the optimal results. Firstly, use the Radial Basis Function neural network to replace the CFD simulation can effectively decrease the time that the optimization cycle spent. Secondly, the hydrofoil

  18. Algorithm for detection of the broken phase conductor in the radial networks

    Directory of Open Access Journals (Sweden)

    Ostojić Mladen M.

    2016-01-01

    Full Text Available The paper presents an algorithm for a directional relay to be used for a detection of the broken phase conductor in the radial networks. The algorithm would use synchronized voltages, measured at the beginning and at the end of the line, as input signals. During the process, the measured voltages would be phase-compared. On the basis of the normalized energy, the direction of the phase conductor, with a broken point, would be detected. Software tool Matlab/Simulink package has developed a radial network model which simulates the broken phase conductor. The simulations generated required input signals by which the algorithm was tested. Development of the algorithm along with the formation of the simulation model and the test results of the proposed algorithm are presented in this paper.

  19. radial

    Directory of Open Access Journals (Sweden)

    JOHN WILLIAM BRANCH

    2007-01-01

    Full Text Available La creación de modelos de objetos reales es una tarea compleja para la cual se ha visto que el uso de técnicas tradicionales de modelamiento tiene restricciones. Para resolver algunos de estos problemas, los sensores de rango basados en láser se usan con frecuencia para muestrear la superficie de un objeto desde varios puntos de vista, lo que resulta en un conjunto de imágenes de rango que son registradas e integradas en un modelo final triangulado. En la práctica, debido a las propiedades reflectivas de la superficie, las oclusiones, y limitaciones de acceso, ciertas áreas de la superficie del objeto usualmente no son muestreadas, dejando huecos que pueden crear efectos indeseables en el modelo integrado. En este trabajo, presentamos un nuevo algoritmo para el llenado de huecos a partir de modelos triangulados. El algoritmo comienza localizando la frontera de las regiones donde están los huecos. Un hueco consiste de un camino cerrado de bordes de los triángulos en la frontera que tienen al menos un borde que no es compartido con ningún otro triangulo. El borde del hueco es entonces adaptado mediante un B-Spline donde la variación promedio de la torsión del la aproximación del B-spline es calculada. Utilizando un simple umbral de la variación promedio a lo largo del borde, se puede clasificar automáticamente, entre huecos reales o generados por intervención humana. Siguiendo este proceso de clasificación, se usa entonces una versión automatizada del interpolador de funciones de base radial para llenar el interior del hueco usando los bordes vecinos.

  20. Calculation of parameters of radial-piston reducer based on the use of functional semantic networks

    Directory of Open Access Journals (Sweden)

    Pashkevich V.M.

    2016-12-01

    Full Text Available The questions of сalculation of parameters of radial-piston reducer are considered in this article. It is used the approach which is based technologies of functional semantic networks. It is considered possibility applications of functional se-mantic networks for calculation of parameters of radial-piston reducer. Semantic networks to calculate the mass of the radial piston reducer are given.

  1. Radial basis functions in mathematical modelling of flow boiling in minichannels

    Directory of Open Access Journals (Sweden)

    Hożejowska Sylwia

    2017-01-01

    Full Text Available The paper addresses heat transfer processes in flow boiling in a vertical minichannel of 1.7 mm depth with a smooth heated surface contacting fluid. The heated element for FC-72 flowing in a minichannel was a 0.45 mm thick plate made of Haynes-230 alloy. An infrared camera positioned opposite the central, axially symmetric part of the channel measured the plate temperature. K-type thermocouples and pressure converters were installed at the inlet and outlet of the minichannel. In the study radial basis functions were used to solve a problem concerning heat transfer in a heated plate supplied with the controlled direct current. According to the model assumptions, the problem is treated as twodimensional and governed by the Poisson equation. The aim of the study lies in determining the temperature field and the heat transfer coefficient. The results were verified by comparing them with those obtained by the Trefftz method.

  2. Sample Data Synchronization and Harmonic Analysis Algorithm Based on Radial Basis Function Interpolation

    Directory of Open Access Journals (Sweden)

    Huaiqing Zhang

    2014-01-01

    Full Text Available The spectral leakage has a harmful effect on the accuracy of harmonic analysis for asynchronous sampling. This paper proposed a time quasi-synchronous sampling algorithm which is based on radial basis function (RBF interpolation. Firstly, a fundamental period is evaluated by a zero-crossing technique with fourth-order Newton’s interpolation, and then, the sampling sequence is reproduced by the RBF interpolation. Finally, the harmonic parameters can be calculated by FFT on the synchronization of sampling data. Simulation results showed that the proposed algorithm has high accuracy in measuring distorted and noisy signals. Compared to the local approximation schemes as linear, quadric, and fourth-order Newton interpolations, the RBF is a global approximation method which can acquire more accurate results while the time-consuming is about the same as Newton’s.

  3. Big geo data surface approximation using radial basis functions: A comparative study

    Science.gov (United States)

    Majdisova, Zuzana; Skala, Vaclav

    2017-12-01

    Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for big scattered datasets in n-dimensional space. It is a non-separable approximation, as it is based on the distance between two points. This method leads to the solution of an overdetermined linear system of equations. In this paper the RBF approximation methods are briefly described, a new approach to the RBF approximation of big datasets is presented, and a comparison for different Compactly Supported RBFs (CS-RBFs) is made with respect to the accuracy of the computation. The proposed approach uses symmetry of a matrix, partitioning the matrix into blocks and data structures for storage of the sparse matrix. The experiments are performed for synthetic and real datasets.

  4. Radial Basis Function (RBF Interpolation and Investigating its Impact on Rainfall Duration Mapping

    Directory of Open Access Journals (Sweden)

    Hassan Derakhshan

    2012-01-01

    Full Text Available The missing data in database must be reproduced primarily by appropriate interpolation techniques. Radial basis function (RBF interpolators can play a significant role in data completion of precipitation mapping. Five RBF techniques were engaged to be employed in compensating the missing data in event-wised dataset of Upper Paramatta River Catchment in the western suburbs of Sydney, Australia. The related shape parameter, C, of RBFs was optimized for first event of database during a cross-validation process. The Normalized mean square error (NMSE, percent average estimation error (PAEE and coefficient of determination (R2 were the statistics used as validation tools. Results showed that the multiquadric RBF technique with the least error, best suits compensation of the related database.

  5. New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model.

    Science.gov (United States)

    Chen, Zhaoxue; Chen, Hao

    2014-01-01

    A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy-Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.

  6. THE ALGORITHM OF MESHFREE METHOD OF RADIAL BASIS FUNCTIONS IN TASKS OF UNDERGROUND HYDROMECHANICS

    Directory of Open Access Journals (Sweden)

    N. V. Medvid

    2016-01-01

    Full Text Available A Mathematical model of filtering consolidation in the body of soil dam with conduit andwashout zone in two-dimensional case is considered. The impact of such technogenic factors as temperature, salt concentration, subsidence of upper boundary and interior points of the dam with time is taken into account. The software to automate the calculation of numerical solution of the boundary problem by radial basis functions has been created, which enables to conduct numerical experiments by varying the input parameters and shape. The influence of the presence of conduit and washout zone on the pressure, temperature and concentration of salts in the dam body at different time intervals isinvestigated. A number of numerical experiments is conducted and the analysis of dam accidents is performed.

  7. A novel method for flow pattern identification in unstable operational conditions using gamma ray and radial basis function

    International Nuclear Information System (INIS)

    Roshani, G.H.; Nazemi, E.; Roshani, M.M.

    2017-01-01

    Changes of fluid properties (especially density) strongly affect the performance of radiation-based multiphase flow meter and could cause error in recognizing the flow pattern and determining void fraction. In this work, we proposed a methodology based on combination of multi-beam gamma ray attenuation and dual modality densitometry techniques using RBF neural network in order to recognize the flow regime and determine the void fraction in gas-liquid two phase flows independent of the liquid phase changes. The proposed system is consisted of one 137 Cs source, two transmission detectors and one scattering detector. The registered counts in two transmission detectors were used as the inputs of one primary Radial Basis Function (RBF) neural network for recognizing the flow regime independent of liquid phase density. Then, after flow regime identification, three RBF neural networks were utilized for determining the void fraction independent of liquid phase density. Registered count in scattering detector and first transmission detector were used as the inputs of these three RBF neural networks. Using this simple methodology, all the flow patterns were correctly recognized and the void fraction was predicted independent of liquid phase density with mean relative error (MRE) of less than 3.28%. - Highlights: • Flow regime and void fraction were determined in two phase flows independent of the liquid phase density changes. • An experimental structure was set up and the required data was obtained. • 3 detectors and one gamma source were used in detection geometry. • RBF networks were utilized for flow regime and void fraction determination.

  8. Mejoramiento de imágenes usando funciones de base radial Images improvement using radial basis functions

    Directory of Open Access Journals (Sweden)

    Jaime Alberto Echeverri Arias

    2009-07-01

    Full Text Available La eliminación del ruido impulsivo es un problema clásico del procesado no lineal para el mejoramiento de imágenes y las funciones de base radial de soporte global son útiles para enfrentarlo. Este trabajo presenta una técnica de interpolación que disminuye eficientemente el ruido impulsivo en imágenes, mediante el uso de interpolante obtenido por funciones de base radial en el marco de la investigación enfocada en el desarrollo de un Sistema de recuperación de imágenes de recursos acuáticos amazónicos. Esta técnica primero etiqueta los píxeles de la imagen que son ruidosos y, mediante la interpolación, genera un valor de reconstrucción de dicho píxel usando sus vecinos. Los resultados obtenidos son comparables y muchas veces mejores que otras técnicas ya publicadas y reconocidas. Según el análisis de resultados, se puede aplicar a imágenes con altas tasas de ruido, manteniendo un bajo error de reconstrucción de los píxeles "ruidosos", así como la calidad visual.Global support radial base functions are effective in eliminating impulsive noise in non-linear processing. This paper introduces an interpolation technique which efficiently reduces image impulsive noise by means of an interpolant obtained through radial base functions. These functions have been used in a research project designed to develop a system for the recovery of images of Amazonian aquatic resources. This technique starts with the tagging by interpolation of noisy image pixels. Thus, a value of reconstruction for the noisy pixels is generated using neighboring pixels. The results obtained with this technique have proved comparable and often better than those obtained with previously known techniques. According to results analysis, this technique can be successfully applied on images with high noise levels. The results are low error in noisy pixel reconstruction and better visual quality.

  9. Use of radial basis functions for meshless numerical solutions applied to financial engineering barrier options

    Directory of Open Access Journals (Sweden)

    Gisele Tessari Santos

    2009-08-01

    Full Text Available A large number of financial engineering problems involve non-linear equations with non-linear or time-dependent boundary conditions. Despite available analytical solutions, many classical and modified forms of the well-known Black-Scholes (BS equation require fast and accurate numerical solutions. This work introduces the radial basis function (RBF method as applied to the solution of the BS equation with non-linear boundary conditions, related to path-dependent barrier options. Furthermore, the diffusional method for solving advective-diffusive equations is explored as to its effectiveness to solve BS equations. Cubic and Thin-Plate Spline (TPS radial basis functions were employed and evaluated as to their effectiveness to solve barrier option problems. The numerical results, when compared against analytical solutions, allow affirming that the RBF method is very accurate and easy to be implemented. When the RBF method is applied, the diffusional method leads to the same results as those obtained from the classical formulation of Black-Scholes equation.Muitos problemas de engenharia financeira envolvem equações não-lineares com condições de contorno não-lineares ou dependentes do tempo. Apesar de soluções analíticas disponíveis, várias formas clássicas e modificadas da conhecida equação de Black-Scholes (BS requerem soluções numéricas rápidas e acuradas. Este trabalho introduz o método de função de base radial (RBF aplicado à solução da equação BS com condições de contorno não-lineares relacionadas a opções de barreira dependentes da trajetória. Além disso, explora-se o método difusional para solucionar equações advectivo-difusivas quanto à sua efetividade para solucionar equações BS. Utilizam-se funções de base radial Cúbica e Thin-Plate Spline (TPS, aplicadas à solução de problemas de opções de barreiras. Os resultados numéricos, quando comparados com as soluções analíticas, permitem afirmar

  10. GRACE L1b inversion through a self-consistent modified radial basis function approach

    Science.gov (United States)

    Yang, Fan; Kusche, Juergen; Rietbroek, Roelof; Eicker, Annette

    2016-04-01

    Implementing a regional geopotential representation such as mascons or, more general, RBFs (radial basis functions) has been widely accepted as an efficient and flexible approach to recover the gravity field from GRACE (Gravity Recovery and Climate Experiment), especially at higher latitude region like Greenland. This is since RBFs allow for regionally specific regularizations over areas which have sufficient and dense GRACE observations. Although existing RBF solutions show a better resolution than classical spherical harmonic solutions, the applied regularizations cause spatial leakage which should be carefully dealt with. It has been shown that leakage is a main error source which leads to an evident underestimation of yearly trend of ice-melting over Greenland. Unlike some popular post-processing techniques to mitigate leakage signals, this study, for the first time, attempts to reduce the leakage directly in the GRACE L1b inversion by constructing an innovative modified (MRBF) basis in place of the standard RBFs to retrieve a more realistic temporal gravity signal along the coastline. Our point of departure is that the surface mass loading associated with standard RBF is smooth but disregards physical consistency between continental mass and passive ocean response. In this contribution, based on earlier work by Clarke et al.(2007), a physically self-consistent MRBF representation is constructed from standard RBFs, with the help of the sea level equation: for a given standard RBF basis, the corresponding MRBF basis is first obtained by keeping the surface load over the continent unchanged, but imposing global mass conservation and equilibrium response of the oceans. Then, the updated set of MRBFs as well as standard RBFs are individually employed as the basis function to determine the temporal gravity field from GRACE L1b data. In this way, in the MRBF GRACE solution, the passive (e.g. ice melting and land hydrology response) sea level is automatically

  11. A radial basis classifier for the automatic detection of aspiration in children with dysphagia

    Directory of Open Access Journals (Sweden)

    Blain Stefanie

    2006-07-01

    Full Text Available Abstract Background Silent aspiration or the inhalation of foodstuffs without overt physiological signs presents a serious health issue for children with dysphagia. To date, there are no reliable means of detecting aspiration in the home or community. An assistive technology that performs in these environments could inform caregivers of adverse events and potentially reduce the morbidity and anxiety of the feeding experience for the child and caregiver, respectively. This paper proposes a classifier for automatic classification of aspiration and swallow vibration signals non-invasively recorded on the neck of children with dysphagia. Methods Vibration signals associated with safe swallows and aspirations, both identified via videofluoroscopy, were collected from over 100 children with neurologically-based dysphagia using a single-axis accelerometer. Five potentially discriminatory mathematical features were extracted from the accelerometry signals. All possible combinations of the five features were investigated in the design of radial basis function classifiers. Performance of different classifiers was compared and the best feature sets were identified. Results Optimal feature combinations for two, three and four features resulted in statistically comparable adjusted accuracies with a radial basis classifier. In particular, the feature pairing of dispersion ratio and normality achieved an adjusted accuracy of 79.8 ± 7.3%, a sensitivity of 79.4 ± 11.7% and specificity of 80.3 ± 12.8% for aspiration detection. Addition of a third feature, namely energy, increased adjusted accuracy to 81.3 ± 8.5% but the change was not statistically significant. A closer look at normality and dispersion ratio features suggest leptokurticity and the frequency and magnitude of atypical values as distinguishing characteristics between swallows and aspirations. The achieved accuracies are 30% higher than those reported for bedside cervical auscultation. Conclusion

  12. A meshless local radial basis function method for two-dimensional incompressible Navier-Stokes equations

    KAUST Repository

    Wang, Zhiheng

    2014-12-10

    A meshless local radial basis function method is developed for two-dimensional incompressible Navier-Stokes equations. The distributed nodes used to store the variables are obtained by the philosophy of an unstructured mesh, which results in two main advantages of the method. One is that the unstructured nodes generation in the computational domain is quite simple, without much concern about the mesh quality; the other is that the localization of the obtained collocations for the discretization of equations is performed conveniently with the supporting nodes. The algebraic system is solved by a semi-implicit pseudo-time method, in which the convective and source terms are explicitly marched by the Runge-Kutta method, and the diffusive terms are implicitly solved. The proposed method is validated by several benchmark problems, including natural convection in a square cavity, the lid-driven cavity flow, and the natural convection in a square cavity containing a circular cylinder, and very good agreement with the existing results are obtained.

  13. Gaussian Radial Basis Function for Efficient Computation of Forest Indirect Illumination

    Science.gov (United States)

    Abbas, Fayçal; Babahenini, Mohamed Chaouki

    2018-06-01

    Global illumination of natural scenes in real time like forests is one of the most complex problems to solve, because the multiple inter-reflections between the light and material of the objects composing the scene. The major problem that arises is the problem of visibility computation. In fact, the computing of visibility is carried out for all the set of leaves visible from the center of a given leaf, given the enormous number of leaves present in a tree, this computation performed for each leaf of the tree which also reduces performance. We describe a new approach that approximates visibility queries, which precede in two steps. The first step is to generate point cloud representing the foliage. We assume that the point cloud is composed of two classes (visible, not-visible) non-linearly separable. The second step is to perform a point cloud classification by applying the Gaussian radial basis function, which measures the similarity in term of distance between each leaf and a landmark leaf. It allows approximating the visibility requests to extract the leaves that will be used to calculate the amount of indirect illumination exchanged between neighbor leaves. Our approach allows efficiently treat the light exchanges in the scene of a forest, it allows a fast computation and produces images of good visual quality, all this takes advantage of the immense power of computation of the GPU.

  14. Radial Basis Functional Model of Multi-Point Dieless Forming Process for Springback Reduction and Compensation

    Directory of Open Access Journals (Sweden)

    Misganaw Abebe

    2017-11-01

    Full Text Available Springback in multi-point dieless forming (MDF is a common problem because of the small deformation and blank holder free boundary condition. Numerical simulations are widely used in sheet metal forming to predict the springback. However, the computational time in using the numerical tools is time costly to find the optimal process parameters value. This study proposes radial basis function (RBF to replace the numerical simulation model by using statistical analyses that are based on a design of experiment (DOE. Punch holding time, blank thickness, and curvature radius are chosen as effective process parameters for determining the springback. The Latin hypercube DOE method facilitates statistical analyses and the extraction of a prediction model in the experimental process parameter domain. Finite element (FE simulation model is conducted in the ABAQUS commercial software to generate the springback responses of the training and testing samples. The genetic algorithm is applied to find the optimal value for reducing and compensating the induced springback for the different blank thicknesses using the developed RBF prediction model. Finally, the RBF numerical result is verified by comparing with the FE simulation result of the optimal process parameters and both results show that the springback is almost negligible from the target shape.

  15. Solution to PDEs using radial basis function finite-differences (RBF-FD) on multiple GPUs

    International Nuclear Information System (INIS)

    Bollig, Evan F.; Flyer, Natasha; Erlebacher, Gordon

    2012-01-01

    This paper presents parallelization strategies for the radial basis function-finite difference (RBF-FD) method. As a generalized finite differencing scheme, the RBF-FD method functions without the need for underlying meshes to structure nodes. It offers high-order accuracy approximation and scales as O(N) per time step, with N being with the total number of nodes. To our knowledge, this is the first implementation of the RBF-FD method to leverage GPU accelerators for the solution of PDEs. Additionally, this implementation is the first to span both multiple CPUs and multiple GPUs. OpenCL kernels target the GPUs and inter-processor communication and synchronization is managed by the Message Passing Interface (MPI). We verify our implementation of the RBF-FD method with two hyperbolic PDEs on the sphere, and demonstrate up to 9x speedup on a commodity GPU with unoptimized kernel implementations. On a high performance cluster, the method achieves up to 7x speedup for the maximum problem size of 27,556 nodes.

  16. Global and Regional Gravity Field Determination from GOCE Kinematic Orbit by Means of Spherical Radial Basis Functions

    Czech Academy of Sciences Publication Activity Database

    Bucha, B.; Bezděk, Aleš; Sebera, Josef; Janak, J.

    2015-01-01

    Roč. 36, č. 6 (2015), s. 773-801 ISSN 0169-3298 R&D Projects: GA ČR GA13-36843S Grant - others:SAV(SK) VEGA 1/0954/15 Institutional support: RVO:67985815 Keywords : spherical radial basis functions * spherical harmonics * geopotential Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 3.622, year: 2015

  17. The orthogonal gradients method: A radial basis functions method for solving partial differential equations on arbitrary surfaces

    KAUST Repository

    Piret, Cé cile

    2012-01-01

    Much work has been done on reconstructing arbitrary surfaces using the radial basis function (RBF) method, but one can hardly find any work done on the use of RBFs to solve partial differential equations (PDEs) on arbitrary surfaces. In this paper

  18. Application of radial basis function in densitometry of stratified regime of liquid-gas two phase flows

    International Nuclear Information System (INIS)

    Roshani, G.H.; Nazemi, E.; Roshani, M.M.

    2017-01-01

    In this paper, a novel method is proposed for predicting the density of liquid phase in stratified regime of liquid-gas two phase flows by utilizing dual modality densitometry technique and artificial neural network (ANN) model of radial basis function (RBF). The detection system includes a 137 Cs radioactive source and two NaI(Tl) detectors for registering transmitted and scattered photons. At the first step, a Monte Carlo simulation model was utilized to obtain the optimum position for the scattering detector in dual modality densitometry configuration. At the next step, an experimental setup was designed based on obtained optimum position for detectors from simulation in order to generate the required data for training and testing the ANN. The results show that the proposed approach could be successfully applied for predicting the density of liquid phase in stratified regime of gas-liquid two phase flows with mean relative error (MRE) of less than 0.701. - Highlights: • Density of liquid phase in stratified regime of two phase flows was predicted. • Combination of dual modality densitometry technique and ANN was utilized. • Detection system includes a 137 Cs radioactive source and two NaI(Tl) detectors. • MCNP simulation was done to obtain the optimum position for the scattering detector. • An experimental setup was designed to generate the required data for training the ANN.

  19. Radial basis function interpolation of unstructured, three-dimensional, volumetric particle tracking velocimetry data

    International Nuclear Information System (INIS)

    Casa, L D C; Krueger, P S

    2013-01-01

    Unstructured three-dimensional fluid velocity data were interpolated using Gaussian radial basis function (RBF) interpolation. Data were generated to imitate the spatial resolution and experimental uncertainty of a typical implementation of defocusing digital particle image velocimetry. The velocity field associated with a steadily rotating infinite plate was simulated to provide a bounded, fully three-dimensional analytical solution of the Navier–Stokes equations, allowing for robust analysis of the interpolation accuracy. The spatial resolution of the data (i.e. particle density) and the number of RBFs were varied in order to assess the requirements for accurate interpolation. Interpolation constraints, including boundary conditions and continuity, were included in the error metric used for the least-squares minimization that determines the interpolation parameters to explore methods for improving RBF interpolation results. Even spacing and logarithmic spacing of RBF locations were also investigated. Interpolation accuracy was assessed using the velocity field, divergence of the velocity field, and viscous torque on the rotating boundary. The results suggest that for the present implementation, RBF spacing of 0.28 times the boundary layer thickness is sufficient for accurate interpolation, though theoretical error analysis suggests that improved RBF positioning may yield more accurate results. All RBF interpolation results were compared to standard Gaussian weighting and Taylor expansion interpolation methods. Results showed that RBF interpolation improves interpolation results compared to the Taylor expansion method by 60% to 90% based on the average squared velocity error and provides comparable velocity results to Gaussian weighted interpolation in terms of velocity error. RMS accuracy of the flow field divergence was one to two orders of magnitude better for the RBF interpolation compared to the other two methods. RBF interpolation that was applied to

  20. Controlling Voltage Levels of Distribution Network-Radial Feeder after Connecting Wind Turbines to the Network

    Directory of Open Access Journals (Sweden)

    Muhammad Al Badri

    2017-11-01

    Full Text Available Several factors in power generation and supply need to be taken into account such as shortages of energy supply, system stability, and energy quality and system disruption due to network losses, industrial development and population expansion. The addition of wind turbines to the distribution network is of great benefit in providing additional power and solving these problems, but this addition is accompanied by the problem of low voltage network. This research found optimal solutions to the problem of low voltage distribution network after connecting wind turbines. The main idea of this paper is to optimize the low-voltage problem as a result of connecting the wind turbines to the "far end" of the radial feeder for a distribution network and to obtain a voltage level within an acceptable and stable range. The problem of low voltage solved by using the load-drop compensation, capacitor-bank and “doubly-fed” induction generators. The results of this study were based on the operation of the entire design of the simulation system which would be compatible with the reality of the energy flow of all network components by using the PSCAD program. The present analysis program revealed an optimum solution for the low voltage profile of the distribution network after connecting the wind turbine.

  1. Application of a proposed overcurrent relay in radial distribution networks

    Energy Technology Data Exchange (ETDEWEB)

    Conde, A.; Vazquez, E. [Universidad Autonoma de Nuevo Leon, Facultad de Ingenieria Mecanica y Electrica, A.P. 36-F, CU, CP 66450, San Nicolas de los Garza, Nuevo Leon (Mexico)

    2011-02-15

    This paper contains the application criteria and coordination process for a proposed overcurrent relay in a radial power system with feed from one or multiple sources. This relay uses independent functions to detect faults and to calculate the operation time. Also this relay uses a time element function that allows it to reduce the time relay operation, enhancing the backup protection. Some of the proposed approaches improve the sensitivity of the relay. The selection of the best approach in the proposed relay is defined by the needs of the application. The proposed protection can be considered as an additional function protection to conventional overcurrent relays. (author)

  2. Weighted radial dimension: an improved fractal measurement for highway transportation networks distribution

    Science.gov (United States)

    Feng, Yongjiu; Liu, Miaolong; Tong, Xiaohua

    2007-06-01

    An improved fractal measurement, the weighted radial dimension, is put forward for highway transportation networks distribution. The radial dimension (DL), originated from subway investigation in Stuttgart, is a fractal measurement for transportation systems under ideal assumption considering all the network lines to be homogeneous curves, ignoring the difference on spatial structure, quality and level, especially the highway networks. Considering these defects of radial dimension, an improved fractal measurement called weighted radial dimension (D WL) is introduced and the transportation system in Guangdong province is studied in detail using this novel method. Weighted radial dimensions are measured and calculated, and the spatial structure, intensity and connectivity of transportation networks are discussed in Guangdong province and the four sub-areas: the Pearl River Delta area, the East Costal area, the West Costal area and the Northern Guangdong area. In Guangdong province, the fractal spatial pattern characteristics of transportation system vary remarkably: it is the highest in the Pearl River Delta area, moderate in Costal area and lowest in the Northern Guangdong area. With the Pearl River Delta area as the centre, the weighted radial dimensions decrease with the distance increasing, while the decline level is smaller in the costal area and greater in the Northern Guangdong province. By analysis of the conic of highway density, it is recognized that the density decrease with the distance increasing from the calculation centre (Guangzhou), demonstrating the same trend as weighted radial dimensions shown. Evidently, the improved fractal measurement, weighted radial dimension, is an indictor describing the characteristics of highway transportation system more effectively and accurately.

  3. Tensor Basis Neural Network v. 1.0 (beta)

    Energy Technology Data Exchange (ETDEWEB)

    2017-03-28

    This software package can be used to build, train, and test a neural network machine learning model. The neural network architecture is specifically designed to embed tensor invariance properties by enforcing that the model predictions sit on an invariant tensor basis. This neural network architecture can be used in developing constitutive models for applications such as turbulence modeling, materials science, and electromagnetism.

  4. Extruded Bread Classification on the Basis of Acoustic Emission Signal With Application of Artificial Neural Networks

    Science.gov (United States)

    Świetlicka, Izabela; Muszyński, Siemowit; Marzec, Agata

    2015-04-01

    The presented work covers the problem of developing a method of extruded bread classification with the application of artificial neural networks. Extruded flat graham, corn, and rye breads differening in water activity were used. The breads were subjected to the compression test with simultaneous registration of acoustic signal. The amplitude-time records were analyzed both in time and frequency domains. Acoustic emission signal parameters: single energy, counts, amplitude, and duration acoustic emission were determined for the breads in four water activities: initial (0.362 for rye, 0.377 for corn, and 0.371 for graham bread), 0.432, 0.529, and 0.648. For classification and the clustering process, radial basis function, and self-organizing maps (Kohonen network) were used. Artificial neural networks were examined with respect to their ability to classify or to cluster samples according to the bread type, water activity value, and both of them. The best examination results were achieved by the radial basis function network in classification according to water activity (88%), while the self-organizing maps network yielded 81% during bread type clustering.

  5. Radial microstrip slotline feed network for circular mobile communications array

    Science.gov (United States)

    Simons, Rainee N.; Kelly, Eron S.; Lee, Richard Q.; Taub, Susan R.

    1994-01-01

    In mobile and satellite communications there is a need for low cost and low profile antennas which have a toroidal pattern. Antennas that have been developed for mobile communications include a L-Band electronically steered stripline phased array, a Ka-Band mechanically steered elliptical reflector antenna and a Ka-Band printed dipole. In addition, a L-Band mechanically steered microstrip array, a L-Band microstrip phased array tracking antenna for mounting on a car roof and an X-Band radial line slotted waveguide antenna have been demonstrated. In the above electronically scanned printed arrays, the individual element radiates normally to the plane of the array and hence require a phase shifter to scan the beam towards the horizon. Scanning in the azimuth is by mechanical or electronic steering. An alternate approach is to mount microstrip patch radiators on the surface of a cone to achieve the required elevation angle. The array then scans in the azimuth by beam switching.

  6. Solving one-dimensional phase change problems with moving grid method and mesh free radial basis functions

    International Nuclear Information System (INIS)

    Vrankar, L.; Turk, G.; Runovc, F.; Kansa, E.J.

    2006-01-01

    Many heat-transfer problems involve a change of phase of material due to solidification or melting. Applications include: the safety studies of nuclear reactors (molten core concrete interaction), the drilling of high ice-content soil, the storage of thermal energy, etc. These problems are often called Stefan's or moving boundary value problems. Mathematically, the interface motion is expressed implicitly in an equation for the conservation of thermal energy at the interface (Stefan's conditions). This introduces a non-linear character to the system which treats each problem somewhat uniquely. The exact solution of phase change problems is limited exclusively to the cases in which e.g. the heat transfer regions are infinite or semi-infinite one dimensional-space. Therefore, solution is obtained either by approximate analytical solution or by numerical methods. Finite-difference methods and finite-element techniques have been used extensively for numerical solution of moving boundary problems. Recently, the numerical methods have focused on the idea of using a mesh-free methodology for the numerical solution of partial differential equations based on radial basis functions. In our case we will study solid-solid transformation. The numerical solutions will be compared with analytical solutions. Actually, in our work we will examine usefulness of radial basis functions (especially multiquadric-MQ) for one-dimensional Stefan's problems. The position of the moving boundary will be simulated by moving grid method. The resultant system of RBF-PDE will be solved by affine space decomposition. (author)

  7. Interface information transfer between non-matching, nonconforming interfaces using radial basis function interpolation

    CSIR Research Space (South Africa)

    Bogaers, Alfred EJ

    2016-10-01

    Full Text Available words, gB = [ φBA PB ] [ MAA PA P TA 0 ]−1 [ gA 0 ] . (15) NAME: DEFINITION C0 compactly supported piecewise polynomial (C0): (1− (||x|| /r))2+ C2 compactly supported piecewise polynomial (C2): (1− (||x|| /r))4+ (4 (||x|| /r) + 1) Thin-plate spline (TPS... a numerical comparison to Kriging and the moving least-squares method, see Krishnamurthy [16]). RBF interpolation is based on fitting a series of splines, or basis functions to interpolate information from one point cloud to another. Let us assume we...

  8. RECONSTRUCCIÓN TRIDIMENSIONAL DE ROSTROS A PARTIR DE IMÁGENES DE RANGO POR MEDIO DE FUNCIONES DE BASE RADIAL DE SOPORTE COMPACTO TRI-DIMENSIONAL RECONSTRUCTION OF FACES FROM RANGE IMAGES THROUGH COMPACT SUPPORT RADIAL BASIS FUNCTIONS

    Directory of Open Access Journals (Sweden)

    Jaime A. Echeverri A.

    2007-07-01

    Full Text Available En este trabajo se muestra la utilización de funciones de base radial de soporte compacto para la reconstrucción tridimensional de rostros. En trabajos anteriores se habían explorado diferentes técnicas y diferentes funciones de base radial para reconstrucción de superficies; ahora presentamos los algoritmos y los resultados de la utilización de funciones de base radial de soporte compacto las cuales presentan ventajas comparativas en términos del tiempo de construcción de un interpolante para la reconstrucción. Se presentan comparaciones con técnicas ampliamente utilizadas en este campo y se detalla el proceso global de reconstrucción de superficies.In previous works, we have explored several radial basis techniques and functions for the reconstruction of surfaces. We now present the use of compact support radial basis functions for the tri-dimensional reconstruction of human faces. Therefore, we present algorithms and results coming from the application of compact support radial basis functions which have revealed comparative advantages in terms of the amount of time needed for the construction of an interpolant to be used in the reconstruction. We are also presenting some comparisons with techniques widely used in this field and we explain in detail the global process for the surfaces reconstruction.

  9. Seismic modeling with radial basis function-generated finite differences (RBF-FD) – a simplified treatment of interfaces

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Bradley, E-mail: brma7253@colorado.edu; Fornberg, Bengt, E-mail: Fornberg@colorado.edu

    2017-04-15

    In a previous study of seismic modeling with radial basis function-generated finite differences (RBF-FD), we outlined a numerical method for solving 2-D wave equations in domains with material interfaces between different regions. The method was applicable on a mesh-free set of data nodes. It included all information about interfaces within the weights of the stencils (allowing the use of traditional time integrators), and was shown to solve problems of the 2-D elastic wave equation to 3rd-order accuracy. In the present paper, we discuss a refinement of that method that makes it simpler to implement. It can also improve accuracy for the case of smoothly-variable model parameter values near interfaces. We give several test cases that demonstrate the method solving 2-D elastic wave equation problems to 4th-order accuracy, even in the presence of smoothly-curved interfaces with jump discontinuities in the model parameters.

  10. The orthogonal gradients method: A radial basis functions method for solving partial differential equations on arbitrary surfaces

    KAUST Repository

    Piret, Cécile

    2012-05-01

    Much work has been done on reconstructing arbitrary surfaces using the radial basis function (RBF) method, but one can hardly find any work done on the use of RBFs to solve partial differential equations (PDEs) on arbitrary surfaces. In this paper, we investigate methods to solve PDEs on arbitrary stationary surfaces embedded in . R3 using the RBF method. We present three RBF-based methods that easily discretize surface differential operators. We take advantage of the meshfree character of RBFs, which give us a high accuracy and the flexibility to represent the most complex geometries in any dimension. Two out of the three methods, which we call the orthogonal gradients (OGr) methods are the result of our work and are hereby presented for the first time. © 2012 Elsevier Inc.

  11. Application of radial basis functions and sinc method for solving the forced vibration of fractional viscoelastic beam

    Energy Technology Data Exchange (ETDEWEB)

    Permoon, M. R.; Haddadpour, H. [Sharif University of Tech, Tehran (Iran, Islamic Republic of); Rashidinia, J.; Parsa, A.; Salehi, R. [Iran University of Science and Technology, Tehran (Iran, Islamic Republic of)

    2016-07-15

    In this paper, the forced vibrations of the fractional viscoelastic beam with the Kelvin-Voigt fractional order constitutive relationship is studied. The equation of motion is derived from Newton's second law and the Galerkin method is used to discretize the equation of motion in to a set of linear ordinary differential equations. For solving the discretized equations, the radial basis functions and Sinc quadrature rule are used. In order to show the effectiveness and accuracy of this method, some test problem are considered, and it is shown that the obtained results are in very good agreement with exact solution. In the following, the proposed numerical solution is applied to exploring the effects of fractional parameters on the response of the beam and finally some conclusions are outlined.

  12. Classification of endoscopic capsule images by using color wavelet features, higher order statistics and radial basis functions.

    Science.gov (United States)

    Lima, C S; Barbosa, D; Ramos, J; Tavares, A; Monteiro, L; Carvalho, L

    2008-01-01

    This paper presents a system to support medical diagnosis and detection of abnormal lesions by processing capsule endoscopic images. Endoscopic images possess rich information expressed by texture. Texture information can be efficiently extracted from medium scales of the wavelet transform. The set of features proposed in this paper to code textural information is named color wavelet covariance (CWC). CWC coefficients are based on the covariances of second order textural measures, an optimum subset of them is proposed. Third and forth order moments are added to cope with distributions that tend to become non-Gaussian, especially in some pathological cases. The proposed approach is supported by a classifier based on radial basis functions procedure for the characterization of the image regions along the video frames. The whole methodology has been applied on real data containing 6 full endoscopic exams and reached 95% specificity and 93% sensitivity.

  13. Application of Radial Basis Function Methods in the Development of a 95th Percentile Male Seated FEA Model.

    Science.gov (United States)

    Vavalle, Nicholas A; Schoell, Samantha L; Weaver, Ashley A; Stitzel, Joel D; Gayzik, F Scott

    2014-11-01

    Human body finite element models (FEMs) are a valuable tool in the study of injury biomechanics. However, the traditional model development process can be time-consuming. Scaling and morphing an existing FEM is an attractive alternative for generating morphologically distinct models for further study. The objective of this work is to use a radial basis function to morph the Global Human Body Models Consortium (GHBMC) average male model (M50) to the body habitus of a 95th percentile male (M95) and to perform validation tests on the resulting model. The GHBMC M50 model (v. 4.3) was created using anthropometric and imaging data from a living subject representing a 50th percentile male. A similar dataset was collected from a 95th percentile male (22,067 total images) and was used in the morphing process. Homologous landmarks on the reference (M50) and target (M95) geometries, with the existing FE node locations (M50 model), were inputs to the morphing algorithm. The radial basis function was applied to morph the FE model. The model represented a mass of 103.3 kg and contained 2.2 million elements with 1.3 million nodes. Simulations of the M95 in seven loading scenarios were presented ranging from a chest pendulum impact to a lateral sled test. The morphed model matched anthropometric data to within a rootmean square difference of 4.4% while maintaining element quality commensurate to the M50 model and matching other anatomical ranges and targets. The simulation validation data matched experimental data well in most cases.

  14. Chaos control and generalized projective synchronization of heavy symmetric chaotic gyroscope systems via Gaussian radial basis adaptive variable structure control

    International Nuclear Information System (INIS)

    Farivar, Faezeh; Aliyari Shoorehdeli, Mahdi; Nekoui, Mohammad Ali; Teshnehlab, Mohammad

    2012-01-01

    Highlights: ► A systematic procedure for GPS of unknown heavy chaotic gyroscope systems. ► Proposed methods are based on Lyapunov stability theory. ► Without calculating Lyapunov exponents and Eigen values of the Jacobian matrix. ► Capable to extend for a variety of chaotic systems. ► Useful for practical applications in the future. - Abstract: This paper proposes the chaos control and the generalized projective synchronization methods for heavy symmetric gyroscope systems via Gaussian radial basis adaptive variable structure control. Because of the nonlinear terms of the gyroscope system, the system exhibits chaotic motions. Occasionally, the extreme sensitivity to initial states in a system operating in chaotic mode can be very destructive to the system because of unpredictable behavior. In order to improve the performance of a dynamic system or avoid the chaotic phenomena, it is necessary to control a chaotic system with a periodic motion beneficial for working with a particular condition. As chaotic signals are usually broadband and noise like, synchronized chaotic systems can be used as cipher generators for secure communication. This paper presents chaos synchronization of two identical chaotic motions of symmetric gyroscopes. In this paper, the switching surfaces are adopted to ensure the stability of the error dynamics in variable structure control. Using the neural variable structure control technique, control laws are established which guarantees the chaos control and the generalized projective synchronization of unknown gyroscope systems. In the neural variable structure control, Gaussian radial basis functions are utilized to on-line estimate the system dynamic functions. Also, the adaptation laws of the on-line estimator are derived in the sense of Lyapunov function. Thus, the unknown gyro systems can be guaranteed to be asymptotically stable. Also, the proposed method can achieve the control objectives. Numerical simulations are presented to

  15. ROAM: A Radial-Basis-Function Optimization Approximation Method for Diagnosing the Three-Dimensional Coronal Magnetic Field

    International Nuclear Information System (INIS)

    Dalmasse, Kevin; Nychka, Douglas W.; Gibson, Sarah E.; Fan, Yuhong; Flyer, Natasha

    2016-01-01

    The Coronal Multichannel Polarimeter (CoMP) routinely performs coronal polarimetric measurements using the Fe XIII 10747 and 10798 lines, which are sensitive to the coronal magnetic field. However, inverting such polarimetric measurements into magnetic field data is a difficult task because the corona is optically thin at these wavelengths and the observed signal is therefore the integrated emission of all the plasma along the line of sight. To overcome this difficulty, we take on a new approach that combines a parameterized 3D magnetic field model with forward modeling of the polarization signal. For that purpose, we develop a new, fast and efficient, optimization method for model-data fitting: the Radial-basis-functions Optimization Approximation Method (ROAM). Model-data fitting is achieved by optimizing a user-specified log-likelihood function that quantifies the differences between the observed polarization signal and its synthetic/predicted analog. Speed and efficiency are obtained by combining sparse evaluation of the magnetic model with radial-basis-function (RBF) decomposition of the log-likelihood function. The RBF decomposition provides an analytical expression for the log-likelihood function that is used to inexpensively estimate the set of parameter values optimizing it. We test and validate ROAM on a synthetic test bed of a coronal magnetic flux rope and show that it performs well with a significantly sparse sample of the parameter space. We conclude that our optimization method is well-suited for fast and efficient model-data fitting and can be exploited for converting coronal polarimetric measurements, such as the ones provided by CoMP, into coronal magnetic field data.

  16. A hybrid self-adaptive Particle Swarm Optimization–Genetic Algorithm–Radial Basis Function model for annual electricity demand prediction

    International Nuclear Information System (INIS)

    Yu, Shiwei; Wang, Ke; Wei, Yi-Ming

    2015-01-01

    Highlights: • A hybrid self-adaptive PSO–GA-RBF model is proposed for electricity demand prediction. • Each mixed-coding particle is composed by two coding parts of binary and real. • Five independent variables have been selected to predict future electricity consumption in Wuhan. • The proposed model has a simpler structure or higher estimating precision than other ANN models. • No matter what the scenario, the electricity consumption of Wuhan will grow rapidly. - Abstract: The present study proposes a hybrid Particle Swarm Optimization and Genetic Algorithm optimized Radial Basis Function (PSO–GA-RBF) neural network for prediction of annual electricity demand. In the model, each mixed-coding particle (or chromosome) is composed of two coding parts, binary and real, which optimizes the structure of the RBF by GA operation and the parameters of the basis and weights by a PSO–GA implementation. Five independent variables have been selected to predict future electricity consumption in Wuhan by using optimized networks. The results shows that (1) the proposed PSO–GA-RBF model has a simpler network structure (fewer hidden neurons) or higher estimation precision than other selected ANN models; and (2) no matter what the scenario, the electricity consumption of Wuhan will grow rapidly at average annual growth rates of about 9.7–11.5%. By 2020, the electricity demand in the planning scenario, the highest among the scenarios, will be 95.85 billion kW h. The lowest demand is estimated for the business-as-usual scenario, and will be 88.45 billion kW h

  17. Feature Extraction Method for High Impedance Ground Fault Localization in Radial Power Distribution Networks

    DEFF Research Database (Denmark)

    Jensen, Kåre Jean; Munk, Steen M.; Sørensen, John Aasted

    1998-01-01

    A new approach to the localization of high impedance ground faults in compensated radial power distribution networks is presented. The total size of such networks is often very large and a major part of the monitoring of these is carried out manually. The increasing complexity of industrial...... of three phase voltages and currents. The method consists of a feature extractor, based on a grid description of the feeder by impulse responses, and a neural network for ground fault localization. The emphasis of this paper is the feature extractor, and the detection of the time instance of a ground fault...... processes and communication systems lead to demands for improved monitoring of power distribution networks so that the quality of power delivery can be kept at a controlled level. The ground fault localization method for each feeder in a network is based on the centralized frequency broadband measurement...

  18. A hybrid radial basis function-pseudospectral method for thermal convection in a 3-D spherical shell

    KAUST Repository

    Wright, G. B.

    2010-07-01

    A novel hybrid spectral method that combines radial basis function (RBF) and Chebyshev pseudospectral methods in a "2 + 1" approach is presented for numerically simulating thermal convection in a 3-D spherical shell. This is the first study to apply RBFs to a full 3-D physical model in spherical geometry. In addition to being spectrally accurate, RBFs are not defined in terms of any surface-based coordinate system such as spherical coordinates. As a result, when used in the lateral directions, as in this study, they completely circumvent the pole issue with the further advantage that nodes can be "scattered" over the surface of a sphere. In the radial direction, Chebyshev polynomials are used, which are also spectrally accurate and provide the necessary clustering near the boundaries to resolve boundary layers. Applications of this new hybrid methodology are given to the problem of convection in the Earth\\'s mantle, which is modeled by a Boussinesq fluid at infinite Prandtl number. To see whether this numerical technique warrants further investigation, the study limits itself to an isoviscous mantle. Benchmark comparisons are presented with other currently used mantle convection codes for Rayleigh number (Ra) 7 × 103 and 105. Results from a Ra = 106 simulation are also given. The algorithmic simplicity of the code (mostly due to RBFs) allows it to be written in less than 400 lines of MATLAB and run on a single workstation. We find that our method is very competitive with those currently used in the literature. Copyright 2010 by the American Geophysical Union.

  19. A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems

    Energy Technology Data Exchange (ETDEWEB)

    Sahoo, N.C. [Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka (Malaysia); Prasad, K. [Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka (Malaysia)

    2006-11-15

    This paper presents a fuzzy genetic approach for reconfiguration of radial distribution systems (RDS) so as to maximize the voltage stability of the network for a specific set of loads. The network reconfiguration involves a mechanism for selection of the best set of branches to be opened, one from each loop, such that the reconfigured RDS possesses desired performance characteristics. This discrete solution space is better handled by the proposed scheme, which maximizes a suitable optimizing function (computed using two different approaches). In the first approach, this function is chosen as the average of a voltage stability index of all the buses in the RDS, while in the second approach, the complete RDS is reduced to a two bus equivalent system and the optimizing function is the voltage stability index of this reduced two bus system. The fuzzy genetic algorithm uses a suitable coding and decoding scheme for maintaining the radial nature of the network at every stage of genetic evolution, and it also uses a fuzzy rule based mutation controller for efficient search of the solution space. This method, tested on 69 bus and 33 bus RDSs, shows promising results for the both approaches. It is also observed that the network losses are reduced when the voltage stability is enhanced by the network reconfiguration. (author)

  20. A fuzzy genetic approach for network reconfiguration to enhance voltage stability in radial distribution systems

    International Nuclear Information System (INIS)

    Sahoo, N.C.; Prasad, K.

    2006-01-01

    This paper presents a fuzzy genetic approach for reconfiguration of radial distribution systems (RDS) so as to maximize the voltage stability of the network for a specific set of loads. The network reconfiguration involves a mechanism for selection of the best set of branches to be opened, one from each loop, such that the reconfigured RDS possesses desired performance characteristics. This discrete solution space is better handled by the proposed scheme, which maximizes a suitable optimizing function (computed using two different approaches). In the first approach, this function is chosen as the average of a voltage stability index of all the buses in the RDS, while in the second approach, the complete RDS is reduced to a two bus equivalent system and the optimizing function is the voltage stability index of this reduced two bus system. The fuzzy genetic algorithm uses a suitable coding and decoding scheme for maintaining the radial nature of the network at every stage of genetic evolution, and it also uses a fuzzy rule based mutation controller for efficient search of the solution space. This method, tested on 69 bus and 33 bus RDSs, shows promising results for the both approaches. It is also observed that the network losses are reduced when the voltage stability is enhanced by the network reconfiguration

  1. Optimal siting of capacitors in radial distribution network using Whale Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    D.B. Prakash

    2017-12-01

    Full Text Available In present days, continuous effort is being made in bringing down the line losses of the electrical distribution networks. Therefore proper allocation of capacitors is of utmost importance because, it will help in reducing the line losses and maintaining the bus voltage. This in turn results in improving the stability and reliability of the system. In this paper Whale Optimization Algorithm (WOA is used to find optimal sizing and placement of capacitors for a typical radial distribution system. Multi objectives such as operating cost reduction and power loss minimization with inequality constraints on voltage limits are considered and the proposed algorithm is validated by applying it on standard radial systems: IEEE-34 bus and IEEE-85 bus radial distribution test systems. The results obtained are compared with those of existing algorithms. The results show that the proposed algorithm is more effective in bringing down the operating costs and in maintaining better voltage profile. Keywords: Whale Optimization Algorithm (WOA, Optimal allocation and sizing of capacitors, Power loss reduction and voltage stability improvement, Radial distribution system, Operating cost minimization

  2. Constrained optimization by radial basis function interpolation for high-dimensional expensive black-box problems with infeasible initial points

    Science.gov (United States)

    Regis, Rommel G.

    2014-02-01

    This article develops two new algorithms for constrained expensive black-box optimization that use radial basis function surrogates for the objective and constraint functions. These algorithms are called COBRA and Extended ConstrLMSRBF and, unlike previous surrogate-based approaches, they can be used for high-dimensional problems where all initial points are infeasible. They both follow a two-phase approach where the first phase finds a feasible point while the second phase improves this feasible point. COBRA and Extended ConstrLMSRBF are compared with alternative methods on 20 test problems and on the MOPTA08 benchmark automotive problem (D.R. Jones, Presented at MOPTA 2008), which has 124 decision variables and 68 black-box inequality constraints. The alternatives include a sequential penalty derivative-free algorithm, a direct search method with kriging surrogates, and two multistart methods. Numerical results show that COBRA algorithms are competitive with Extended ConstrLMSRBF and they generally outperform the alternatives on the MOPTA08 problem and most of the test problems.

  3. Modeling of Tsunami Equations and Atmospheric Swirling Flows with a Graphics Processing Unit (GPU) and Radial Basis Functions (RBF)

    Science.gov (United States)

    Schmidt, J.; Piret, C.; Zhang, N.; Kadlec, B. J.; Liu, Y.; Yuen, D. A.; Wright, G. B.; Sevre, E. O.

    2008-12-01

    The faster growth curves in the speed of GPUs relative to CPUs in recent years and its rapidly gained popularity has spawned a new area of development in computational technology. There is much potential in utilizing GPUs for solving evolutionary partial differential equations and producing the attendant visualization. We are concerned with modeling tsunami waves, where computational time is of extreme essence, for broadcasting warnings. In order to test the efficacy of the GPU on the set of shallow-water equations, we employed the NVIDIA board 8600M GT on a MacBook Pro. We have compared the relative speeds between the CPU and the GPU on a single processor for two types of spatial discretization based on second-order finite-differences and radial basis functions. RBFs are a more novel method based on a gridless and a multi- scale, adaptive framework. Using the NVIDIA 8600M GT, we received a speed up factor of 8 in favor of GPU for the finite-difference method and a factor of 7 for the RBF scheme. We have also studied the atmospheric dynamics problem of swirling flows over a spherical surface and found a speed-up of 5.3 using the GPU. The time steps employed for the RBF method are larger than those used in finite-differences, because of the much fewer number of nodal points needed by RBF. Thus, in modeling the same physical time, RBF acting in concert with GPU would be the fastest way to go.

  4. Heuristic for solving capacitor allocation problems in electric energy radial distribution networks

    Directory of Open Access Journals (Sweden)

    Maria A. Biagio

    2012-04-01

    Full Text Available The goal of the capacitor allocation problem in radial distribution networks is to minimize technical losses with consequential positive impacts on economic and environmental areas. The main objective is to define the size and location of the capacitors while considering load variations in a given horizon. The mathematical formulation for this planning problem is given by an integer nonlinear mathematical programming model that demands great computational effort to be solved. With the goal of solving this problem, this paper proposes a methodology that is composed of heuristics and Tabu Search procedures. The methodology presented explores network system characteristics of the network system reactive loads for identifying regions where procedures of local and intensive searches should be performed. A description of the proposed methodology and an analysis of computational results obtained which are based on several test systems including actual systems are presented. The solutions reached are as good as or better than those indicated by well referenced methodologies. The technique proposed is simple in its use and does not require calibrating an excessive amount of parameters, making it an attractive alternative for companies involved in the planning of radial distribution networks.

  5. Conjunction of radial basis function interpolator and artificial intelligence models for time-space modeling of contaminant transport in porous media

    Science.gov (United States)

    Nourani, Vahid; Mousavi, Shahram; Dabrowska, Dominika; Sadikoglu, Fahreddin

    2017-05-01

    As an innovation, both black box and physical-based models were incorporated into simulating groundwater flow and contaminant transport. Time series of groundwater level (GL) and chloride concentration (CC) observed at different piezometers of study plain were firstly de-noised by the wavelet-based de-noising approach. The effect of de-noised data on the performance of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) was evaluated. Wavelet transform coherence was employed for spatial clustering of piezometers. Then for each cluster, ANN and ANFIS models were trained to predict GL and CC values. Finally, considering the predicted water heads of piezometers as interior conditions, the radial basis function as a meshless method which solves partial differential equations of GFCT, was used to estimate GL and CC values at any point within the plain where there is not any piezometer. Results indicated that efficiency of ANFIS based spatiotemporal model was more than ANN based model up to 13%.

  6. User-friendly Tool for Power Flow Analysis and Distributed Generation Optimisation in Radial Distribution Networks

    Directory of Open Access Journals (Sweden)

    M. F. Akorede

    2017-06-01

    Full Text Available The intent of power distribution companies (DISCOs is to deliver electric power to their customers in an efficient and reliable manner – with minimal energy loss cost. One major way to minimise power loss on a given power system is to install distributed generation (DG units on the distribution networks. However, to maximise benefits, it is highly crucial for a DISCO to ensure that these DG units are of optimal size and sited in the best locations on the network. This paper gives an overview of a software package developed in this study, called Power System Analysis and DG Optimisation Tool (PFADOT. The main purpose of the graphical user interface-based package is to guide a DISCO in finding the optimal size and location for DG placement in radial distribution networks. The package, which is also suitable for load flow analysis, employs the GUI feature of MATLAB. Three objective functions are formulated into a single optimisation problem and solved with fuzzy genetic algorithm to simultaneously obtain DG optimal size and location. The accuracy and reliability of the developed tool was validated using several radial test systems, and the results obtained are evaluated against the existing similar package cited in the literature, which are impressive and computationally efficient.

  7. Fiber Bragg Grating Sensor for Fault Detection in Radial and Network Transmission Lines

    Directory of Open Access Journals (Sweden)

    Mehdi Shadaram

    2010-10-01

    Full Text Available In this paper, a fiber optic based sensor capable of fault detection in both radial and network overhead transmission power line systems is investigated. Bragg wavelength shift is used to measure the fault current and detect fault in power systems. Magnetic fields generated by currents in the overhead transmission lines cause a strain in magnetostrictive material which is then detected by Fiber Bragg Grating (FBG. The Fiber Bragg interrogator senses the reflected FBG signals, and the Bragg wavelength shift is calculated and the signals are processed. A broadband light source in the control room scans the shift in the reflected signal. Any surge in the magnetic field relates to an increased fault current at a certain location. Also, fault location can be precisely defined with an artificial neural network (ANN algorithm. This algorithm can be easily coordinated with other protective devices. It is shown that the faults in the overhead transmission line cause a detectable wavelength shift on the reflected signal of FBG and can be used to detect and classify different kind of faults. The proposed method has been extensively tested by simulation and results confirm that the proposed scheme is able to detect different kinds of fault in both radial and network system.

  8. Stochastic Evaluation of Maximum Wind Installation in a Radial Distribution Network

    DEFF Research Database (Denmark)

    Chen, Peiyuan; Bak-Jensen, Birgitte; Chen, Zhe

    2011-01-01

    This paper proposes an optimization algorithm to find the maximum wind installation in a radial distribution network. The algorithm imposes a limit on the amount of wind energy that can be curtailed annually. The algorithm implements the wind turbine reactive power control and wind energy...... curtailment using sensitivity factors. The optimization is integrated with Monte Carlo simulation to account for the stochastic behavior of load demand and wind power generation. The proposed algorithm is tested on a real 20 kV Danish distribution system in Støvring. It is demonstrated that the algorithm...... executes reactive compensation and energy curtailment sequentially in an effective and efficient manner....

  9. Musculocutaneous nerve substituting for the distal part of radial nerve: A case report and its embryological basis

    Directory of Open Access Journals (Sweden)

    A S Yogesh

    2011-01-01

    Full Text Available In the present case, we have reported a unilateral variation of the radial and musculocutaneous nerves on the left side in a 64-year-old male cadaver. The radial nerve supplied all the heads of the triceps brachii muscle and gave cutaneous branches such as lower lateral cutaneous nerve of the arm and posterior cutaneous nerve of forearm. The radial nerve ended without continuing further. The musculocutaneous nerve supplied the brachioradialis, extensor carpi radialis longus and extensor carpi radialis brevis muscles. The musculocutaneous nerve divided terminally into two branches, superficial and deep. The deep branch of musculocutaneous nerve corresponded to usual deep branch of the radial nerve while the superficial branch of musculocutaneous nerve corresponded to usual superficial branch of the radial nerve. The dissection was continued to expose the entire brachial plexus from its origin and it was found to be normal. The structures on the right upper limb were found to be normal. Surgeons should keep such variations in mind while performing the surgeries of the upper limb.

  10. A QCQP Approach for OPF in Multiphase Radial Networks with Wye and Delta Connections: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zamzam, Ahmed, S.; Zhaoy, Changhong; Dall' Anesey, Emiliano; Sidiropoulos, Nicholas D.

    2017-06-27

    This paper examines the AC Optimal Power Flow (OPF) problem for multiphase distribution networks featuring renewable energy resources (RESs). We start by outlining a power flow model for radial multiphase systems that accommodates wye-connected and delta-connected RESs and non-controllable energy assets. We then formalize an AC OPF problem that accounts for both types of connections. Similar to various AC OPF renditions, the resultant problem is a non convex quadratically-constrained quadratic program. However, the so-called Feasible Point Pursuit-Successive Convex Approximation algorithm is leveraged to obtain a feasible and yet locally-optimal solution. The merits of the proposed solution approach are demonstrated using two unbalanced multiphase distribution feeders with both wye and delta connections.

  11. Radial Peripapillary Capillary Network Visualized Using Wide-Field Montage Optical Coherence Tomography Angiography.

    Science.gov (United States)

    Mase, Tomoko; Ishibazawa, Akihiro; Nagaoka, Taiji; Yokota, Harumasa; Yoshida, Akitoshi

    2016-07-01

    We quantitatively analyzed the features of a radial peripapillary capillary (RPC) network visualized using wide-field montage optical coherence tomography (OCT) angiography in healthy human eyes. Twenty eyes of 20 healthy subjects were recruited. En face 3 × 3-mm OCT angiograms of multiple locations in the posterior pole were acquired using the RTVue XR Avanti, and wide-field montage images of the RPC were created. To evaluate the RPC density, the montage images were binarized and skeletonized. The correlation between the RPC density and the retinal nerve fiber layer (RNFL) thickness measured by an OCT circle scan was investigated. The RPC at the temporal retina was detected as far as 7.6 ± 0.7 mm from the edge of the optic disc but not around the perifoveal area within 0.9 ± 0.1 mm of the fovea. Capillary-free zones beside the first branches of the arterioles were significantly (P optic disc edge were 13.6 ± 0.8, 11.9 ± 0.9, and 10.4 ± 0.9 mm-1. The RPC density also was correlated significantly (r = 0.64, P network. The RPC is present in the superficial peripapillary retina in proportion to the RNFL thickness, supporting the idea that the RPC may be the vascular network primarily responsible for RNFL nourishment.

  12. Improving the Transmission System Reliability for the 154kV Radial Network Operation

    Energy Technology Data Exchange (ETDEWEB)

    Choo, Jin Boo; Yoo, Myeong Ho; Yoon, Young Beum; Kim, Tae Won [Korea Electric Power Research Institute, Taejon (Korea, Republic of); Lee, Gi Won; Chung, Beom Jin; Jung, Jung Won; Park, Kyu Hyun; Lee, Myung Hee; Kim, Hyun Jong; Kim, Chae Hee [KEYIN CO., (Korea, Republic of)

    1996-12-31

    Analyzing that 154kV radial network current ed operated, we developed Automatic Power Reconfiguration System(APRS) which restore blackout area. It consists of special data acquisition system(DAU) and central monitoring system for reason of protecting currently operating power system. In addition, it communicates using optical communication network for high speed data transmission and accuracy. An Accuracy of operation and stability of the developed system is tested using Real Time Digital Simulator in 3-bus equivalent model system. In An Outage case, our developed system can restore a blackout area in three second. An ability of the restoration of a blackout was verified by simulations. For the field test, the developed system was set up at SINCHON S/S, SESOMUN S/S, SINDANG S/S and MAJANG S/S governed by Seoul Power Transmission Center. If the system reliability is proved for a one year test in real power system, application of the system will be extended to the other substations.

  13. Optimum topology for radial networks by using evolutionary computer programming; Topologia optima de redes radiais utilizando programacao evolucionaria

    Energy Technology Data Exchange (ETDEWEB)

    Pinto, Joao Luis [Instituto de Engenhariade Sistemas e Computadores (INESC), Porto (Portugal). E-mail: jpinto@duque.inescn.pt; Proenca, Luis Miguel [Instituto Superior de Linguas e Administracao (ISLA), Gaia (Portugal). E-mail: lproenca@inescn.pt

    1999-07-01

    This paper describes the using of Evolutionary Programming techniques for determination of the radial electric network topology, considering investment costs and losses. The work aims to demonstrate the particular easiness of coding and implementation and the parallelism implicit to the method as well, giving outstanding performance levels. As test example, a 43 bars and 75 alternative lines network has been used by describing an implementation of the algorithm in an Object Oriented platform.

  14. The Anatomical Basis for Dystonia: The Motor Network Model

    Directory of Open Access Journals (Sweden)

    H.A. Jinnah

    2017-10-01

    Full Text Available Background: The dystonias include a clinically and etiologically very diverse group of disorders. There are both degenerative and non-degenerative subtypes resulting from genetic or acquired causes. Traditionally, all dystonias have been viewed as disorders of the basal ganglia. However, there has been increasing appreciation for involvement of other brain regions including the cerebellum, thalamus, midbrain, and cortex. Much of the early evidence for these other brain regions has come from studies of animals, but multiple recent studies have been done with humans, in an effort to confirm or refute involvement of these other regions. The purpose of this article is to review the new evidence from animals and humans regarding the motor network model, and to address the issues important to translational neuroscience.Methods: The English literature was reviewed for articles relating to the neuroanatomical basis for various types of dystonia in both animals and humans.Results: There is evidence from both animals and humans that multiple brain regions play an important role in various types of dystonia. The most direct evidence for specific brain regions comes from animal studies using pharmacological, lesion, or genetic methods. In these studies, experimental manipulations of specific brain regions provide direct evidence for involvement of the basal ganglia, cerebellum, thalamus and other regions. Additional evidence also comes from human studies using neuropathological, neuroimaging, non-invasive brain stimulation, and surgical interventions. In these studies, the evidence is less conclusive, because discriminating the regions that cause dystonia from those that reflect secondary responses to abnormal movements is more challenging.Discussion: Overall, the evidence from both animals and humans suggests that different regions may play important roles in different subtypes of dystonia. The evidence so far provides strong support for the motor

  15. Comparison of Feedforward Network and Radial Basis Function to Detect Leukemia

    Directory of Open Access Journals (Sweden)

    Pragya Bagwari

    2017-08-01

    Full Text Available Leukemia is a fast growing cancer also called as blood cancer. It normally originates near bone marrow. The need for automatic leukemia detection system rises ever since the existing working methods include labor-intensive inspection of the blood marking as the initial step in the direction of diagnosis. This is very time consuming and also the correctness of the technique rest on the worker’s capability. This paper describes few image segmentation and feature extraction methods used for leukemia detection. Analyzing through images is very important as from images; diseases can be detected and diagnosed at earlier stage. From there, further actions like controlling, monitoring and prevention of diseases can be done. Images are used as they are cheap and do not require expensive testing and lab equipment. The system will focus on white blood cells disease, leukemia. Changes in features will be used as a classifier input.

  16. Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties.

    Science.gov (United States)

    Le, Nguyen-Quoc-Khanh; Nguyen, Trinh-Trung-Duong; Ou, Yu-Yen

    2017-05-01

    The electron transport proteins have an important role in storing and transferring electrons in cellular respiration, which is the most proficient process through which cells gather energy from consumed food. According to the molecular functions, the electron transport chain components could be formed with five complexes with several different electron carriers and functions. Therefore, identifying the molecular functions in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. This work includes two phases for discriminating electron transport proteins from transport proteins and classifying categories of five complexes in electron transport proteins. In the first phase, the performances from PSSM with AAIndex feature set were successful in identifying electron transport proteins in transport proteins with achieved sensitivity of 73.2%, specificity of 94.1%, and accuracy of 91.3%, with MCC of 0.64 for independent data set. With the second phase, our method can approach a precise model for identifying of five complexes with different molecular functions in electron transport proteins. The PSSM with AAIndex properties in five complexes achieved MCC of 0.51, 0.47, 0.42, 0.74, and 1.00 for independent data set, respectively. We suggest that our study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins. Copyright © 2017 Elsevier Inc. All rights reserved.

  17. Convex Relaxation of OPF in Multiphase Radial Networks with Wye and Delta Connections

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Low, Steven [California Institute of Technology

    2017-08-01

    This panel presentation focuses on multiphase radial distribution networks with wye and delta connections, and proposes a semidefinite relaxation of the AC optimal power flow (OPF) problem. Two multiphase power flow models are developed to facilitate the integration of delta-connected loads or generation resources in the OPF problem. The first model is referred to as the extended branch flow model (EBFM). The second model leverages a linear relationship between phase-to-ground power injections and delta connections that holds under a balanced voltage approximation (BVA). Based on these models, pertinent OPF problems are formulated and relaxed to semidefinite programs (SDPs). Numerical studies on IEEE test feeders show that the proposed SDP relaxations can be solved efficiently by a generic optimization solver. Numerical evidence also indicates that solving the resultant SDP under BVA is faster than under EBFM. Moreover, both SDP solutions are numerically exact with respect to voltages and branch flows. It is further shown that the SDP solution under BVA has a small optimality gap, and the BVA model is accurate in the sense that it reproduces actual system voltages.

  18. Optimal placement of capacitors in a radial network using conic and mixed integer linear programming

    Energy Technology Data Exchange (ETDEWEB)

    Jabr, R.A. [Electrical, Computer and Communication Engineering Department, Notre Dame University, P.O. Box: 72, Zouk Mikhael, Zouk Mosbeh (Lebanon)

    2008-06-15

    This paper considers the problem of optimally placing fixed and switched type capacitors in a radial distribution network. The aim of this problem is to minimize the costs associated with capacitor banks, peak power, and energy losses whilst satisfying a pre-specified set of physical and technical constraints. The proposed solution is obtained using a two-phase approach. In phase-I, the problem is formulated as a conic program in which all nodes are candidates for placement of capacitor banks whose sizes are considered as continuous variables. A global solution of the phase-I problem is obtained using an interior-point based conic programming solver. Phase-II seeks a practical optimal solution by considering capacitor sizes as discrete variables. The problem in this phase is formulated as a mixed integer linear program based on minimizing the L1-norm of deviations from the phase-I state variable values. The solution to the phase-II problem is obtained using a mixed integer linear programming solver. The proposed method is validated via extensive comparisons with previously published results. (author)

  19. Optimal Power Flow in Multiphase Radial Networks with Delta Connections: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Changhong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Low, Steven H. [California Institute of Technology

    2017-11-27

    This paper focuses on multiphase radial distribution networks with mixed wye and delta connections, and proposes a semidefinite relaxation of the AC optimal power flow (OPF) problem. Two multiphase power-flow models are developed to facilitate the integration of delta-connected generation units/loads in the OPF problem. The first model extends traditional branch flow models - and it is referred to as extended branch flow model (EBFM). The second model leverages a linear relationship between per-phase power injections and delta connections, which holds under a balanced voltage approximation (BVA). Based on these models, pertinent OPF problems are formulated and relaxed to semidefinite programs (SDPs). Numerical studies on IEEE test feeders show that SDP relaxations can be solved efficiently by a generic optimization solver. Numerical evidences indicate that solving the resultant SDP under BVA is faster than under EBFM. Moreover, both SDP solutions are numerically exact with respect to voltages and branch flows. It is also shown that the SDP solution under BVA has a small optimality gap, while the BVA model is accurate in the sense that it reflects actual system voltages.

  20. An Improved Collocation Meshless Method Based on the Variable Shaped Radial Basis Function for the Solution of the Interior Acoustic Problems

    Directory of Open Access Journals (Sweden)

    Shuang Wang

    2012-01-01

    Full Text Available As an efficient tool, radial basis function (RBF has been widely used for the multivariate approximation, interpolating continuous, and the solution of the particle differential equations. However, ill-conditioned interpolation matrix may be encountered when the interpolation points are very dense or irregularly arranged. To avert this problem, RBFs with variable shape parameters are introduced, and several new variation strategies are proposed. Comparison with the RBF with constant shape parameters are made, and the results show that the condition number of the interpolation matrix grows much slower with our strategies. As an application, an improved collocation meshless method is formulated by employing the new RBF. In addition, the Hermite-type interpolation is implemented to handle the Neumann boundary conditions and an additional sine/cosine basis is introduced for the Helmlholtz equation. Then, two interior acoustic problems are solved with the presented method; the results demonstrate the robustness and effectiveness of the method.

  1. Common spatial pattern combined with kernel linear discriminate and generalized radial basis function for motor imagery-based brain computer interface applications

    Science.gov (United States)

    Hekmatmanesh, Amin; Jamaloo, Fatemeh; Wu, Huapeng; Handroos, Heikki; Kilpeläinen, Asko

    2018-04-01

    Brain Computer Interface (BCI) can be a challenge for developing of robotic, prosthesis and human-controlled systems. This work focuses on the implementation of a common spatial pattern (CSP) base algorithm to detect event related desynchronization patterns. Utilizing famous previous work in this area, features are extracted by filter bank with common spatial pattern (FBCSP) method, and then weighted by a sensitive learning vector quantization (SLVQ) algorithm. In the current work, application of the radial basis function (RBF) as a mapping kernel of linear discriminant analysis (KLDA) method on the weighted features, allows the transfer of data into a higher dimension for more discriminated data scattering by RBF kernel. Afterwards, support vector machine (SVM) with generalized radial basis function (GRBF) kernel is employed to improve the efficiency and robustness of the classification. Averagely, 89.60% accuracy and 74.19% robustness are achieved. BCI Competition III, Iva data set is used to evaluate the algorithm for detecting right hand and foot imagery movement patterns. Results show that combination of KLDA with SVM-GRBF classifier makes 8.9% and 14.19% improvements in accuracy and robustness, respectively. For all the subjects, it is concluded that mapping the CSP features into a higher dimension by RBF and utilization GRBF as a kernel of SVM, improve the accuracy and reliability of the proposed method.

  2. METHODS OF TEXT INFORMATION CLASSIFICATION ON THE BASIS OF ARTIFICIAL NEURAL AND SEMANTIC NETWORKS

    Directory of Open Access Journals (Sweden)

    L. V. Serebryanaya

    2016-01-01

    Full Text Available The article covers the use of perseptron, Hopfild artificial neural network and semantic network for classification of text information. Network training algorithms are studied. An algorithm of inverse mistake spreading for perceptron network and convergence algorithm for Hopfild network are implemented. On the basis of the offered models and algorithms automatic text classification software is developed and its operation results are evaluated.

  3. Wave forecasting in near real time basis by neural network

    Digital Repository Service at National Institute of Oceanography (India)

    Rao, S.; Mandal, S.; Prabaharan, N.

    ., forecasting of waves become an important aspect of marine environment. This paper presents application of the neural network (NN) with better update algorithms, namely rprop, quickprop and superSAB for wave forecasting. Measured waves off Marmagoa, Goa, India...

  4. Radial Peripapillary Capillary Network in Patients with Retinitis Pigmentosa: An Optical Coherence Tomography Angiography Study.

    Science.gov (United States)

    Mastropasqua, Rodolfo; Borrelli, Enrico; Agnifili, Luca; Toto, Lisa; Di Antonio, Luca; Senatore, Alfonso; Palmieri, Michele; D'Uffizi, Alessandro; Carpineto, Paolo

    2017-01-01

    To investigate radial peripapillary capillary (RPC) network in patients affected by retinitis pigmentosa (RP). Eleven patients (22 eyes) with previous diagnosis of RP and 16 age-matched healthy subjects (16 eyes) were enrolled. The diagnosis of RP was made based on both clinical features and electrophysiological examination. All patients underwent a complete ophthalmologic examination, including optical coherence tomography angiography and visual field (VF). The primary outcomes were the RPC vessel density in the peripapillary and disk areas; the secondary outcomes were the peripapillary retinal nerve fiber layer (RNFL) thickness and the mean defect at VF. A total of 19 eyes of 11 RP patients (5 males, 6 females) and 16 eyes of 16 healthy subjects (10 males, 6 females) were included for the analysis. RPC vessel density in the disk area was 46.5 ± 7.1% in the RP group and 45.4 ± 10.6% in the control group ( p  = 0.754). RPC vessel density in the peripapillary area was significantly reduced in the RP group after the comparison with the control group (52.5 ± 5.0 and 57.2 ± 5.1%, respectively, p  = 0.011). RNFL thickness was 85.9 ± 20.4 μm in the RP group and 104.0 ± 6.4 μm in the control group ( p  = 0.002). RPC vessel density was significantly correlated with RNFL thickness values in RP patients, both in the disk and in the peripapillary area (Rho = 0.599 and p  = 0.007 in the disk area, Rho = 0.665 and p  = 0.002 in the peripapillary area, respectively). We showed that density of RPC is reduced in these patients in the peripapillary area. Moreover, the RPC vessel density correlates with the RNFL thickness.

  5. Study of the Radial Peripapillary Capillary Network in Congenital Optic Disc Anomalies With Optical Coherence Tomography Angiography.

    Science.gov (United States)

    Cennamo, Gilda; Rossi, Claudia; Ruggiero, Pasquale; de Crecchio, Giuseppe; Cennamo, Giovanni

    2017-04-01

    To evaluate the radial peripapillary capillary network with optical coherence tomography angiography (angio-OCT) in morning glory syndrome (MGS), optic disc colobomas, and optic disc pits, and to explore possible correlations between the neural vascular structure and the pathogenesis of congenital optic disc anomalies. Prospective observational comparative case series. Fifteen eyes of 15 patients with congenital optic disc anomalies were enrolled in this study. All patients underwent angio-OCT. The scans were centered on optic discs. The mean age at presentation was 33 years (range: 19-50 years). Congenital optic disc anomalies were identified in all 15 eyes. Three eyes had the characteristic funduscopic signs of MGS, and angio-OCT scans of the peripapillary retina revealed a dense microvascular network. Optic disc colobomas were found in 5 eyes, and the characteristic funduscopic signs of optic pits were found in 7 eyes. Angio-OCT showed the absence of a radial peripapillary microvascular network in these 12 eyes. The finding that angio-OCT scans confirmed the presence of a peripapillary microvascular network only in MGS cases supports the hypothesis that a primary neuroectodermal abnormality and a secondary mesenchymal abnormality leads to MGS. Angio-OCT is a safe, rapid imaging technique that could shed light on the pathogenesis of rare diseases of the optic disc. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. The effect of time duration in the network and radial method toward the accuracy in measuring the deformation at Muria

    International Nuclear Information System (INIS)

    Ari Nugroho and Hadi Suntoko

    2011-01-01

    The Deformation monitoring activities in the vicinity of Mount Muria are recommended by the IAEA (International Atomic Energy Agency) to be done for 5 years. The purpose of these activities is to determine the rate of the deformation caused by the volcanic activity of Mount Muria, as a basic study in analyzing the volcanic hazard toward the NPP (Nuclear Power Plant). The whole coordinate points measured encompass the district of Jepara, Pati, Demak, and Kudus. In 2010 deformation measurements were periodically conducted for 4 times a year using two geodetic GPS units of Trimble R7 GNSS type through the network method. The measurements were carried out at seven points of interest and at one reference point in March, April, May and December. Each session of the measurements was performed for 2.5 hours. In 2011 the deformation measurements were periodically conducted for 4 times a year by means of the radial method. The measurements were made at eight points of interest and at one reference point in April and May, June and July. Each session of measurements was performed for 10 hours. Based on the results of the measurements by means of the network method in 2010, it was concluded that the range of horizontal and vertical accuracy is between 6-10 mm and 25-46 mm, while the results of the measurements of the radial method in 2011 is 4-7 mm, and 16-28 mm respectively. Furthermore, it provides the evidence that the radial method tends to has better result than the network method if it is applied 4 times longer than the network method, resulting the accuracy below 7 mm and 28 mm for horizontal and vertical respectively. (author)

  7. Decoupling Research on Flexible Tactile Sensors Interfered by White Gaussian Noise Using Improved Radical Basis Function Neural Network

    Directory of Open Access Journals (Sweden)

    Feilu Wang

    2014-04-01

    Full Text Available Research on tactile sensors to enhance their flexibility and ability of multi- dimensional information detection is a key issue to develop humanoid robots. In view of that the tactile sensor is often affected by noise, this paper adds different white Gaussian noises (WGN into the ideal model of flexible tactile sensors based on conductive rubber purposely, then improves the standard radial basis function neural network (RNFNN to deal with the noises. The modified RBFNN is applied to approximate and decouple the mapping relationship between row-column resistance with WGNs and three-dimensional deformation. Numerical experiments demonstrate that the decoupling result of the deformation for the sensor is quite good. The results show that the improved RBFNN which doesn’t rely on the mathematical model of the system has good anti-noise ability and robustness.

  8. Revisiting Earth's radial seismic structure using a Bayesian neural network approach

    NARCIS (Netherlands)

    de Wit, R.W.L.

    2015-01-01

    The gross features of seismic observations can be explained by relatively simple spherically symmetric (1-D) models of wave velocities, density and attenuation, which describe the Earth's average(radial) structure. 1-D earth models are often used as a reference for studies on Earth's thermo-chemical

  9. Neural Networks For Electrohydrodynamic Effect Modelling

    Directory of Open Access Journals (Sweden)

    Wiesław Wajs

    2004-01-01

    Full Text Available This paper presents currently achieved results concerning methods of electrohydrodynamiceffect used in geophysics simulated with feedforward networks trained with backpropagation algorithm, radial basis function networks and generalized regression networks.

  10. Assessing the performance of Taiwan’s environmental protection system with a non-radial network DEA approach

    International Nuclear Information System (INIS)

    Huang, Chin-wei; Chiu, Yung-ho; Fang, Wei-ta; Shen, Neng

    2014-01-01

    Previous studies involving environmental performance purely focus on analyzing environmental or waste treatment efficiencies. This study combines various aspects of environmental protection and establishes a non-radial network DEA approach to evaluate the performance of an environmental protection system. The empirical methodology assumes that the system consists of three stages: administrative, executive processes, and protection effectiveness. The executive process includes waste treatment and pollution auditing divisions. In addition to assessing efficiencies, the empirical evaluation further explores the internal and external influences on performances and contributes implications and suggestions for environmental policy makers. The proposed model is utilized to gauge the performance of an environmental protection system for 20 municipalities in Taiwan. The results indicate the following: (1) for improving environmental quality, the government needs to put forth greater efforts in environmental audits; (2) improving productivity per unit so as to increase achievements in the executive process is more important for raising performance on environmental work, in addition to increasing workers and equipment for environmental protection; (3) a high degree of industrialization negatively influences administrative efficiency and educated residents have a greater comprehension for administrative operations, which can help in efficient budget utilization. - Highlights: • A non-radial network DEA approach to evaluate the Performance of Environmental Protection System. • The performance of waste treatment performs better than the efficiency of auditing. • Governmental expenditure is more efficiently utilized in the administrative process. • The effectiveness of achieved protection is a critical indicator for revealing environmental quality in a region

  11. Two-step superresolution approach for surveillance face image through radial basis function-partial least squares regression and locality-induced sparse representation

    Science.gov (United States)

    Jiang, Junjun; Hu, Ruimin; Han, Zhen; Wang, Zhongyuan; Chen, Jun

    2013-10-01

    Face superresolution (SR), or face hallucination, refers to the technique of generating a high-resolution (HR) face image from a low-resolution (LR) one with the help of a set of training examples. It aims at transcending the limitations of electronic imaging systems. Applications of face SR include video surveillance, in which the individual of interest is often far from cameras. A two-step method is proposed to infer a high-quality and HR face image from a low-quality and LR observation. First, we establish the nonlinear relationship between LR face images and HR ones, according to radial basis function and partial least squares (RBF-PLS) regression, to transform the LR face into the global face space. Then, a locality-induced sparse representation (LiSR) approach is presented to enhance the local facial details once all the global faces for each LR training face are constructed. A comparison of some state-of-the-art SR methods shows the superiority of the proposed two-step approach, RBF-PLS global face regression followed by LiSR-based local patch reconstruction. Experiments also demonstrate the effectiveness under both simulation conditions and some real conditions.

  12. The numerical study and comparison of radial basis functions in applications of the dual reciprocity boundary element method to convection-diffusion problems

    Science.gov (United States)

    Chanthawara, Krittidej; Kaennakham, Sayan; Toutip, Wattana

    2016-02-01

    The methodology of Dual Reciprocity Boundary Element Method (DRBEM) is applied to the convection-diffusion problems and investigating its performance is our first objective of the work. Seven types of Radial Basis Functions (RBF); Linear, Thin-plate Spline, Cubic, Compactly Supported, Inverse Multiquadric, Quadratic, and that proposed by [12], were closely investigated in order to numerically compare their effectiveness drawbacks etc. and this is taken as our second objective. A sufficient number of simulations were performed covering as many aspects as possible. Varidated against both exacts and other numerical works, the final results imply strongly that the Thin-Plate Spline and Linear type of RBF are superior to others in terms of both solutions' quality and CPU-time spent while the Inverse Multiquadric seems to poorly yield the results. It is also found that DRBEM can perform relatively well at moderate level of convective force and as anticipated becomes unstable when the problem becomes more convective-dominated, as normally found in all classical mesh-dependence methods.

  13. Simultaneous determination of penicillin G salts by infrared spectroscopy: Evaluation of combining orthogonal signal correction with radial basis function-partial least squares regression

    Science.gov (United States)

    Talebpour, Zahra; Tavallaie, Roya; Ahmadi, Seyyed Hamid; Abdollahpour, Assem

    2010-09-01

    In this study, a new method for the simultaneous determination of penicillin G salts in pharmaceutical mixture via FT-IR spectroscopy combined with chemometrics was investigated. The mixture of penicillin G salts is a complex system due to similar analytical characteristics of components. Partial least squares (PLS) and radial basis function-partial least squares (RBF-PLS) were used to develop the linear and nonlinear relation between spectra and components, respectively. The orthogonal signal correction (OSC) preprocessing method was used to correct unexpected information, such as spectral overlapping and scattering effects. In order to compare the influence of OSC on PLS and RBF-PLS models, the optimal linear (PLS) and nonlinear (RBF-PLS) models based on conventional and OSC preprocessed spectra were established and compared. The obtained results demonstrated that OSC clearly enhanced the performance of both RBF-PLS and PLS calibration models. Also in the case of some nonlinear relation between spectra and component, OSC-RBF-PLS gave satisfactory results than OSC-PLS model which indicated that the OSC was helpful to remove extrinsic deviations from linearity without elimination of nonlinear information related to component. The chemometric models were tested on an external dataset and finally applied to the analysis commercialized injection product of penicillin G salts.

  14. Modelling cell cycle synchronisation in networks of coupled radial glial cells.

    Science.gov (United States)

    Barrack, Duncan S; Thul, Rüdiger; Owen, Markus R

    2015-07-21

    Radial glial cells play a crucial role in the embryonic mammalian brain. Their proliferation is thought to be controlled, in part, by ATP mediated calcium signals. It has been hypothesised that these signals act to locally synchronise cell cycles, so that clusters of cells proliferate together, shedding daughter cells in uniform sheets. In this paper we investigate this cell cycle synchronisation by taking an ordinary differential equation model that couples the dynamics of intracellular calcium and the cell cycle and extend it to populations of cells coupled via extracellular ATP signals. Through bifurcation analysis we show that although ATP mediated calcium release can lead to cell cycle synchronisation, a number of other asynchronous oscillatory solutions including torus solutions dominate the parameter space and cell cycle synchronisation is far from guaranteed. Despite this, numerical results indicate that the transient and not the asymptotic behaviour of the system is important in accounting for cell cycle synchronisation. In particular, quiescent cells can be entrained on to the cell cycle via ATP mediated calcium signals initiated by a driving cell and crucially will cycle in near synchrony with the driving cell for the duration of neurogenesis. This behaviour is highly sensitive to the timing of ATP release, with release at the G1/S phase transition of the cell cycle far more likely to lead to near synchrony than release during mid G1 phase. This result, which suggests that ATP release timing is critical to radial glia cell cycle synchronisation, may help us to understand normal and pathological brain development. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. The capability of radial basis function to forecast the volume fractions of the annular three-phase flow of gas-oil-water.

    Science.gov (United States)

    Roshani, G H; Karami, A; Salehizadeh, A; Nazemi, E

    2017-11-01

    The problem of how to precisely measure the volume fractions of oil-gas-water mixtures in a pipeline remains as one of the main challenges in the petroleum industry. This paper reports the capability of Radial Basis Function (RBF) in forecasting the volume fractions in a gas-oil-water multiphase system. Indeed, in the present research, the volume fractions in the annular three-phase flow are measured based on a dual energy metering system including the 152 Eu and 137 Cs and one NaI detector, and then modeled by a RBF model. Since the summation of volume fractions are constant (equal to 100%), therefore it is enough for the RBF model to forecast only two volume fractions. In this investigation, three RBF models are employed. The first model is used to forecast the oil and water volume fractions. The next one is utilized to forecast the water and gas volume fractions, and the last one to forecast the gas and oil volume fractions. In the next stage, the numerical data obtained from MCNP-X code must be introduced to the RBF models. Then, the average errors of these three models are calculated and compared. The model which has the least error is picked up as the best predictive model. Based on the results, the best RBF model, forecasts the oil and water volume fractions with the mean relative error of less than 0.5%, which indicates that the RBF model introduced in this study ensures an effective enough mechanism to forecast the results. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Systems and Methods for Optimal Power Flow on a Radial Network

    OpenAIRE

    Low, Steven H.; Peng, Qiuyu

    2015-01-01

    Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control. One embodiment includes a node controller including a distributed power control application; a plurality of node operating parameters describing the operating parameter of a node and a set of at least one node selected from the group consisting of an ancestor node and at least one child node; wherein send node operating parameters to nodes in the set of at least o...

  17. Distributed Gradient Descent for Solving Optimal Power Flow in Radial Networks

    OpenAIRE

    Gan, Lingwen; Low, Steven H.

    2016-01-01

    Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control, One embodiment includes a node controller comprising a memory containing: a plurality of node operating parameters; and a plurality of node operating parameters describing operating parameters for a set of at least one node selected from the group consisting of at least one downstream node and at least one upstream node; wherein the processor is configured by the ...

  18. Main concept of local area network protection on the basis of the SAAM 'TRAFFIC'

    International Nuclear Information System (INIS)

    Vasil'ev, P.M.; Kryukov, Yu.A.; Kuptsov, S.I.; Ivanov, V.V.; Koren'kov, V.V.

    2002-01-01

    In our previous paper we developed a system for acquisition, analysis and management of the network traffic (SAAM 'Traffic') for a segment of the JINR local area computer network (JINR LAN). In our present work we consider well-known scenarios of attacks on local area networks and propose protection methods based on the SAAM 'Traffic'. Although the system for LAN protection is installed on a router computer, it is not analogous to the firewall scheme and, thus, it does not hinder the performance of distributed network applications. This provides a possibility to apply such an approach to GRID-technologies, where network protection on the firewall basis can not be basically used. (author)

  19. Material basis of Chinese herbal formulas explored by combining pharmacokinetics with network pharmacology.

    Directory of Open Access Journals (Sweden)

    Lixia Pei

    Full Text Available The clinical application of Traditional Chinese medicine (TCM, using several herbs in combination (called formulas, has a history of more than one thousand years. However, the bioactive compounds that account for their therapeutic effects remain unclear. We hypothesized that the material basis of a formula are those compounds with a high content in the decoction that are maintained at a certain level in the system circulation. Network pharmacology provides new methodological insights for complicated system studies. In this study, we propose combining pharmacokinetic (PK analysis with network pharmacology to explore the material basis of TCM formulas as exemplified by the Bushen Zhuanggu formula (BZ composed of Psoralea corylifolia L., Aconitum carmichaeli Debx., and Cnidium monnieri (L. Cuss. A sensitive and credible liquid chromatography tandem mass spectrometry (LC-MS/MS method was established for the simultaneous determination of 15 compounds present in the three herbs. The concentrations of these compounds in the BZ decoction and in rat plasma after oral BZ administration were determined. Up to 12 compounds were detected in the BZ decoction, but only 5 could be analyzed using PK parameters. Combined PK results, network pharmacology analysis revealed that 4 compounds might serve as the material basis for BZ. We concluded that a sensitive, reliable, and suitable LC-MS/MS method for both the composition and pharmacokinetic study of BZ has been established. The combination of PK with network pharmacology might be a potent method for exploring the material basis of TCM formulas.

  20. Systems and methods for optimal power flow on a radial network

    Science.gov (United States)

    Low, Steven H.; Peng, Qiuyu

    2018-04-24

    Node controllers and power distribution networks in accordance with embodiments of the invention enable distributed power control. One embodiment includes a node controller including a distributed power control application; a plurality of node operating parameters describing the operating parameter of a node and a set of at least one node selected from the group consisting of an ancestor node and at least one child node; wherein send node operating parameters to nodes in the set of at least one node; receive operating parameters from the nodes in the set of at least one node; calculate a plurality of updated node operating parameters using an iterative process to determine the updated node operating parameters using the node operating parameters that describe the operating parameters of the node and the set of at least one node, where the iterative process involves evaluation of a closed form solution; and adjust node operating parameters.

  1. Contour interpolated radial basis functions with spline boundary correction for fast 3D reconstruction of the human articular cartilage from MR images

    International Nuclear Information System (INIS)

    Javaid, Zarrar; Unsworth, Charles P.; Boocock, Mark G.; McNair, Peter J.

    2016-01-01

    Purpose: The aim of this work is to demonstrate a new image processing technique that can provide a “near real-time” 3D reconstruction of the articular cartilage of the human knee from MR images which is user friendly. This would serve as a point-of-care 3D visualization tool which would benefit a consultant radiologist in the visualization of the human articular cartilage. Methods: The authors introduce a novel fusion of an adaptation of the contour method known as “contour interpolation (CI)” with radial basis functions (RBFs) which they describe as “CI-RBFs.” The authors also present a spline boundary correction which further enhances volume estimation of the method. A subject cohort consisting of 17 right nonpathological knees (ten female and seven male) is assessed to validate the quality of the proposed method. The authors demonstrate how the CI-RBF method dramatically reduces the number of data points required for fitting an implicit surface to the entire cartilage, thus, significantly improving the speed of reconstruction over the comparable RBF reconstruction method of Carr. The authors compare the CI-RBF method volume estimation to a typical commercial package (3D DOCTOR), Carr’s RBF method, and a benchmark manual method for the reconstruction of the femoral, tibial, and patellar cartilages. Results: The authors demonstrate how the CI-RBF method significantly reduces the number of data points (p-value < 0.0001) required for fitting an implicit surface to the cartilage, by 48%, 31%, and 44% for the patellar, tibial, and femoral cartilages, respectively. Thus, significantly improving the speed of reconstruction (p-value < 0.0001) by 39%, 40%, and 44% for the patellar, tibial, and femoral cartilages over the comparable RBF model of Carr providing a near real-time reconstruction of 6.49, 8.88, and 9.43 min for the patellar, tibial, and femoral cartilages, respectively. In addition, it is demonstrated how the CI-RBF method matches the volume

  2. Contour interpolated radial basis functions with spline boundary correction for fast 3D reconstruction of the human articular cartilage from MR images

    Energy Technology Data Exchange (ETDEWEB)

    Javaid, Zarrar; Unsworth, Charles P., E-mail: c.unsworth@auckland.ac.nz [Department of Engineering Science, The University of Auckland, Auckland 1010 (New Zealand); Boocock, Mark G.; McNair, Peter J. [Health and Rehabilitation Research Center, Auckland University of Technology, Auckland 1142 (New Zealand)

    2016-03-15

    Purpose: The aim of this work is to demonstrate a new image processing technique that can provide a “near real-time” 3D reconstruction of the articular cartilage of the human knee from MR images which is user friendly. This would serve as a point-of-care 3D visualization tool which would benefit a consultant radiologist in the visualization of the human articular cartilage. Methods: The authors introduce a novel fusion of an adaptation of the contour method known as “contour interpolation (CI)” with radial basis functions (RBFs) which they describe as “CI-RBFs.” The authors also present a spline boundary correction which further enhances volume estimation of the method. A subject cohort consisting of 17 right nonpathological knees (ten female and seven male) is assessed to validate the quality of the proposed method. The authors demonstrate how the CI-RBF method dramatically reduces the number of data points required for fitting an implicit surface to the entire cartilage, thus, significantly improving the speed of reconstruction over the comparable RBF reconstruction method of Carr. The authors compare the CI-RBF method volume estimation to a typical commercial package (3D DOCTOR), Carr’s RBF method, and a benchmark manual method for the reconstruction of the femoral, tibial, and patellar cartilages. Results: The authors demonstrate how the CI-RBF method significantly reduces the number of data points (p-value < 0.0001) required for fitting an implicit surface to the cartilage, by 48%, 31%, and 44% for the patellar, tibial, and femoral cartilages, respectively. Thus, significantly improving the speed of reconstruction (p-value < 0.0001) by 39%, 40%, and 44% for the patellar, tibial, and femoral cartilages over the comparable RBF model of Carr providing a near real-time reconstruction of 6.49, 8.88, and 9.43 min for the patellar, tibial, and femoral cartilages, respectively. In addition, it is demonstrated how the CI-RBF method matches the volume

  3. Bounds on Rates of Variable-Basis and Neural-Network Approximation

    Czech Academy of Sciences Publication Activity Database

    Kůrková, Věra; Sanguineti, M.

    2001-01-01

    Roč. 47, č. 6 (2001), s. 2659-2665 ISSN 0018-9448 R&D Projects: GA ČR GA201/00/1482 Institutional research plan: AV0Z1030915 Keywords : approximation by variable-basis functions * bounds on rates of approximation * complexity of neural networks * high-dimensional optimal decision problems Subject RIV: BA - General Mathematics Impact factor: 2.077, year: 2001

  4. Evaluation of Strains of Metarhizium anisopliae and Beauveria bassiana against Spodoptera litura on the Basis of Their Virulence, Germination Rate, Conidia Production, Radial Growth and Enzyme Activity.

    Science.gov (United States)

    Petlamul, Wanida; Prasertsan, Poonsuk

    2012-06-01

    Ten strains of the entomopathogenic fungi Metarhizium anisopliae and Beauveria bassiana were evaluated to find the most effective strain for optimization studies. The first criterion tested for strain selection was the mortality (> 50%) of Spodoptera litura larvae after inoculation of the fungus for 4 days. Results on several bioassays revealed that B. bassiana BNBCRC showed the most virulence on mortality S. litura larvae (80% mortality). B. bassiana BNBCRC also showed the highest germination rate (72.22%). However, its conidia yield (7.2 × 10(8) conidia/mL) was lower than those of B. bassiana B 14841 (8.3 × 10(8) conidia/mL) and M. anisopliae M6 (8.2 × 10(8) conidia/mL). The highest accumulative radial growth was obtained from the strain B14841 (37.10 mm/day) while the strain BNBCRC showed moderate radial growth (24.40 mm/day). M. anisopliae M6 possessed the highest protease activity (145.00 mU/mL) while M. anisopliae M8 possessed the highest chitinase activity (20.00 mU/mL) during 96~144 hr cultivation. Amongst these criteria, selection based on virulence and germination rate lead to the selection of B. bassiana BNBCRC. B. bassiana B14841 would be selected if based on growth rate while M. anisopliae M6 and M8 possessed the highest enzyme activities.

  5. Development of automobile distribution networks on the basis of multi-criteria evaluation of distribution channels

    Directory of Open Access Journals (Sweden)

    A. Vasilis Vasiliauskas

    2010-12-01

    Full Text Available .The days when a buyer was forced to choose from what is being offered have passed. These days, buyers demand a product that would answer their exclusive expectations at a time of their preference and at an acceptable price. Therefore, manufacturers aiming to survive the competition battle have to rethink their operation strategies. Special importance is attached to the process of development and reconstruction of supply chains, and the process which may feature particularities, depending on the branch of industry. Automobile manufacturing is the biggest the fastest industry developing across the globe. New automobiles are listed as luxury commodities and are, therefore, subjected to very strict requirements with regard to various logistic operations and technologies, which are vital for ensuring efficient automobile delivery to the final users. Due to the growing demand for brand-new automobiles and the distance to the user, automobile manufacturers are constantly searching for solutions to the development and support of an efficient distribution network. Strategy shaping of distribution network requires evaluation of a number of criteria, which influence the distribution system. The article analyzes the development of automobile distribution networks on the basis of multi-criteria evaluation of distribution channels.

  6. The Method of Building a Network of Online Showcases on the Basis of the MVC Architecture

    Directory of Open Access Journals (Sweden)

    Pursky Oleg I.

    2017-10-01

    Full Text Available A method to build a network of online showcases that support a large number of customer orders and visits, which meets the current performance standards and the reliability of Internet solutions in the sphere electronic commerce, has been developed. The method involves the creation of a typical showcase and the implementation for the information management system of a showcases network of an own database operating on the data from the central management information system with the two-way data replication. A mechanism for «cloning» the online showcases, which are part of the network, and their quick integration with the business processes of enterprise and a management system based on a typical showcase, has been proposed. The development of typical online showcases is implemented on the basis of MVC concept (Model-View-Controller, the ASP.NET MVC Framework Technology, and the visual templates of web pages, thus ensuring that the algorithms for the behavior of objects are independent of both the objects themselves and their visual representation. This enhances the development of e-commerce projects significantly, speeds up the implementation process, and provides a high degree of flexibility and functionality of the online showcases.

  7. Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG

    Directory of Open Access Journals (Sweden)

    R. Rajaram

    2015-11-01

    Full Text Available Network reconfiguration which is constrained non linear optimization problem has been solved for loss minimization, load balancing, etc. for last two decades using various heuristic search evolutionary algorithms like binary particle swarm optimization, neuro-fuzzy techniques, etc. The contribution of this paper lies in considering distributed generation which are smaller power sources like solar photovoltaic cells or wind turbines connected in the customer roof top. This new connection in the radial network has made unidirectional current flow to become bidirectional there by increasing the efficiency but sometimes reducing stability of the system. Modified plant growth simulation algorithm has been applied here successfully to minimize real power loss because it does not require barrier factors or cross over rates because the objectives and constraints are dealt separately. The main advantage of this algorithm is continuous guiding search along with changing objective function because power from distributed generation is continuously varying so this can be applied for real time applications with required modifications. This algorithm here is tested for a standard 33 bus radial distribution system for loss minimization and test results here shows that this algorithm is efficient and suitable for real time applications.

  8. Latitudinal and radial variation of >2 GeV/n protons and alpha-particles at solar maximum: ULYSSES COSPIN/KET and neutron monitor network observations

    Directory of Open Access Journals (Sweden)

    A. V. Belov

    2003-06-01

    Full Text Available Ulysses, launched in October 1990, began its second out-of-ecliptic orbit in September 1997. In 2000/2001 the spacecraft passed from the south to the north polar regions of the Sun in the inner heliosphere. In contrast to the first rapid pole to pole passage in 1994/1995 close to solar minimum, Ulysses experiences now solar maximum conditions. The Kiel Electron Telescope (KET measures also protons and alpha-particles in the energy range from 5 MeV/n to >2 GeV/n. To derive radial and latitudinal gradients for >2 GeV/n protons and alpha-particles, data from the Chicago instrument on board IMP-8 and the neutron monitor network have been used to determine the corresponding time profiles at Earth. We obtain a spatial distribution at solar maximum which differs greatly from the solar minimum distribution. A steady-state approximation, which was characterized by a small radial and significant latitudinal gradient at solar minimum, was interchanged with a highly variable one with a large radial and a small – consistent with zero – latitudinal gradient. A significant deviation from a spherically symmetric cosmic ray distribution following the reversal of the solar magnetic field in 2000/2001 has not been observed yet. A small deviation has only been observed at northern polar regions, showing an excess of particles instead of the expected depression. This indicates that the reconfiguration of the heliospheric magnetic field, caused by the reappearance of the northern polar coronal hole, starts dominating the modulation of galactic cosmic rays already at solar maximum.Key words. Interplanetary physics (cosmic rays; energetic particles – Space plasma physics (charged particle motion and acceleration

  9. A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods

    Science.gov (United States)

    Tien Bui, Dieu; Hoang, Nhat-Duc

    2017-09-01

    In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM), radial-basis-function Fisher discriminant analysis (RBFDA), and a geographic information system (GIS) database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.

  10. A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1 for spatial prediction of floods

    Directory of Open Access Journals (Sweden)

    D. Tien Bui

    2017-09-01

    Full Text Available In this study, a probabilistic model, named as BayGmmKda, is proposed for flood susceptibility assessment in a study area in central Vietnam. The new model is a Bayesian framework constructed by a combination of a Gaussian mixture model (GMM, radial-basis-function Fisher discriminant analysis (RBFDA, and a geographic information system (GIS database. In the Bayesian framework, GMM is used for modeling the data distribution of flood-influencing factors in the GIS database, whereas RBFDA is utilized to construct a latent variable that aims at enhancing the model performance. As a result, the posterior probabilistic output of the BayGmmKda model is used as flood susceptibility index. Experiment results showed that the proposed hybrid framework is superior to other benchmark models, including the adaptive neuro-fuzzy inference system and the support vector machine. To facilitate the model implementation, a software program of BayGmmKda has been developed in MATLAB. The BayGmmKda program can accurately establish a flood susceptibility map for the study region. Accordingly, local authorities can overlay this susceptibility map onto various land-use maps for the purpose of land-use planning or management.

  11. Radial nerve dysfunction

    Science.gov (United States)

    Neuropathy - radial nerve; Radial nerve palsy; Mononeuropathy ... Damage to one nerve group, such as the radial nerve, is called mononeuropathy . Mononeuropathy means there is damage to a single nerve. Both ...

  12. The NOVO Network: the original scientific basis for its establishment and our R&D vision

    OpenAIRE

    Winkel, Jørgen; Edwards, Kasper; Dellve, L.; Schiller, B.; Westgaard, Rolf H.

    2017-01-01

    The NOVO network is a Nordic non-governmental professional association whose aims are to foster the scientific progress, knowledge and development of the working environment within Healthcare as an integrated part of production system development. The vision is a “Nordic Model for Sustainable Systems” in the healthcare sector. It was founded in 2006 in Copenhagen and was financially supported by the Nordic Council of Ministers from 2007 to 2015. The motivation to establish the NOVO Network ar...

  13. Development of the disable software reporting system on the basis of the neural network

    Science.gov (United States)

    Gavrylenko, S.; Babenko, O.; Ignatova, E.

    2018-04-01

    The PE structure of malicious and secure software is analyzed, features are highlighted, binary sign vectors are obtained and used as inputs for training the neural network. A software model for detecting malware based on the ART-1 neural network was developed, optimal similarity coefficients were found, and testing was performed. The obtained research results showed the possibility of using the developed system of identifying malicious software in computer systems protection systems

  14. Dynamic neural networking as a basis for plasticity in the control of heart rate.

    Science.gov (United States)

    Kember, G; Armour, J A; Zamir, M

    2013-01-21

    A model is proposed in which the relationship between individual neurons within a neural network is dynamically changing to the effect of providing a measure of "plasticity" in the control of heart rate. The neural network on which the model is based consists of three populations of neurons residing in the central nervous system, the intrathoracic extracardiac nervous system, and the intrinsic cardiac nervous system. This hierarchy of neural centers is used to challenge the classical view that the control of heart rate, a key clinical index, resides entirely in central neuronal command (spinal cord, medulla oblongata, and higher centers). Our results indicate that dynamic networking allows for the possibility of an interplay among the three populations of neurons to the effect of altering the order of control of heart rate among them. This interplay among the three levels of control allows for different neural pathways for the control of heart rate to emerge under different blood flow demands or disease conditions and, as such, it has significant clinical implications because current understanding and treatment of heart rate anomalies are based largely on a single level of control and on neurons acting in unison as a single entity rather than individually within a (plastically) interconnected network. Copyright © 2012 Elsevier Ltd. All rights reserved.

  15. New strong motion network in Georgia: basis for specifying seismic hazard

    Science.gov (United States)

    Kvavadze, N.; Tsereteli, N. S.

    2017-12-01

    Risk created by hazardous natural events is closely related to sustainable development of the society. Global observations have confirmed tendency of growing losses resulting from natural disasters, one of the most dangerous and destructive if which are earthquakes. Georgia is located in seismically active region. So, it is imperative to evaluate probabilistic seismic hazard and seismic risk with proper accuracy. National network of Georgia includes 35 station all of which are seismometers. There are significant gaps in strong motion recordings, which essential for seismic hazard assessment. To gather more accelerometer recordings, we have built a strong motion network distributed on the territory of Georgia. The network includes 6 stations for now, with Basalt 4x datalogger and strong motion sensor Episensor ES-T. For each site, Vs30 and soil resonance frequencies have been measured. Since all but one station (Tabakhmelam near Tbilisi), are located far from power and internet lines special system was created for instrument operation. Solar power is used to supply the system with electricity and GSM/LTE modems for internet access. VPN tunnel was set up using Raspberry pi, for two-way communication with stations. Tabakhmela station is located on grounds of Ionosphere Observatory, TSU and is used as a hub for the network. This location also includes a broadband seismometer and VLF electromagnetic waves observation antenna, for possible earthquake precursor studies. On server, located in Tabakhmela, the continues data is collected from all the stations, for later use. The recordings later will be used in different seismological and engineering problems, namely selecting and creating GMPE model for Caucasus, for probabilistic seismic hazard and seismic risk evaluation. These stations are a start and in the future expansion of strong motion network is planned. Along with this, electromagnetic wave observations will continue and additional antennas will be implemented

  16. Information transfer among widely spaced individuals: latrines as a basis for communication networks in the swift fox

    DEFF Research Database (Denmark)

    Darden, Safi-Kirstine; Steffensen, Lise K.; Dabelsteen, Torben

    2008-01-01

    In species where individuals are widely spaced instantaneous signals cannot readily form the basis of communication networks, that is several individuals within signalling range of each other. However, markings, signals that remain in the environment after the signaller has left, may fulfil...... this role. In this study, we have investigated the possible function of swift fox, Vulpes velox, latrines, collections of scat, urine and possibly other secretions, in a communication network context. We found that latrines had higher frequencies of occurrence inside the core (defined as the 50% kernel...... contour) of a pair's home-range when compared with outside the core and in areas of a pair's home-range that overlapped with neighbouring individuals when compared with those areas that did not overlap with neighbours. These were also the two areas where latrines were most likely to reoccur in the next...

  17. DIAGNOSIS AND PREDICTION OF CHOLECYSTITIS DEVELOPMENT ON THE BASIS OF NEURAL NETWORK ANALYSIS OF RISK FACTORS

    Directory of Open Access Journals (Sweden)

    V. A. Lazarenko

    2017-01-01

    Full Text Available Purpose. To develop an artificial neural network for diagnosing and predicting the development of cholecystitis based on an analysis of data on risk factors, and to explore the possibilities of its application in real clinical practice.Materials and methods. The collection of materials was held in at the hospitals of the city of Kursk and included a survey of 488 patients with hepatopancreatoduodenal diseases. 203 patients were suffering from cholecystitis, in 285 patients the diagnosis of cholecystitis was excluded. Analysis of risk factors’ data (such as sex, age, bad habits, profession, family relationships, etc. was carried out using an internally developed artificial neural network (multilayer perceptron with hyperbolic tangent as the activation function. The computer program “System of Intellectual Analysis and Diagnosis of Diseases” was registered in accordance with established procedure (Certificate No. 2017613090.Results. The use of neural network analysis of data on risk factors in comparison with the processing of information that forms a clinical picture allows the diagnosis of a potential disease with cholecystitis before the onset of symptoms. The training of the artificial neural network with a quantitative output coding the age of probable hospitalization made it possible to generate an array of values, signifficantly (α ≤ 0.001 not differing from the empirical data. The difference between the mean calculated and mean empirical values was 0.45 for the training set and 1.75 for the clinical approbation group. The mean absolute error was within the range of 1.87–2.07 years.Conclusion. 1. The proposed new approach to the diagnosis and prognosis of cholecystitis has demonstrated its effectiveness, which is confirmed in clinical approbation by the levels of sensitivity (94.44%, m = 2.26 and specificity (80.6%, m = 3.9.2. The error in predicting the age of probable hospitalization of patients with cholecystitis did not

  18. The NOVO Network: the original scientific basis for its establishment and our R&D vision

    DEFF Research Database (Denmark)

    Winkel, Jørgen; Edwards, Kasper; Dellve, L.

    2017-01-01

    Systems” in the healthcare sector. It was founded in 2006 in Copenhagen and was financially supported by the Nordic Council of Ministers from 2007 to 2015. The motivation to establish the NOVO Network arose when reviewing the literature regarding opportunities to create sustainable production systems....... This work was initiated year 2002 and resultet in a systematic review published 2011 (Westgaard and Winkel 2011). Already in 2006 it was concluded that ergonomic interventions have limited musculoskeletal and mental health effects in a long-range perspective while rationalization has predominant negative...... be challenged due to the frequent negative impact of rationalization on ergonomics and vice versa. This call for dialogue processes between the stakeholders taking more holistic systems perspectives. Dialogue-based change processes may be more common in the Nordic countries compared to other parts of the world...

  19. Memory and neural networks on the basis of color centers in solids.

    Science.gov (United States)

    Winnacker, Albrecht; Osvet, Andres

    2009-11-01

    Optical data recording is one of the most widely used and efficient systems of memory in the non-living world. The application of color centers in this context offers not only systems of high speed in writing and read-out due to a high degree of parallelism in data handling but also a possibility to set up models of neural networks. In this way, systems with a high potential for image processing, pattern recognition and logical operations can be constructed. A limitation to storage density is given by the diffraction limit of optical data recording. It is shown that this limitation can at least in principle be overcome by the principle of spectral hole burning, which results in systems of storage capacities close to the human brain system.

  20. Stock market index prediction using neural networks

    Science.gov (United States)

    Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

    1994-03-01

    A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

  1. Multi-modular neural networks for the classification of e+e- hadronic events

    International Nuclear Information System (INIS)

    Proriol, J.

    1994-01-01

    Some multi-modular neural network methods of classifying e + e - hadronic events are presented. We compare the performances of the following neural networks: MLP (multilayer perceptron), MLP and LVQ (learning vector quantization) trained sequentially, and MLP and RBF (radial basis function) trained sequentially. We introduce a MLP-RBF cooperative neural network. Our last study is a multi-MLP neural network. (orig.)

  2. Artificial Neural Network Modeling of an Inverse Fluidized Bed ...

    African Journals Online (AJOL)

    A Radial Basis Function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. In the proposed model, the trained neural network represents the kinetics of biological decomposition of pollutants in the reactor. The neural network has been trained with experimental data ...

  3. Pediatric Emergency Care Applied Research Network head injuryprediction rules: on the basis of cost and effectiveness

    Science.gov (United States)

    Gökharman, Fatma Dilek; Aydın, Sonay; Fatihoğlu, Erdem; Koşar, Pınar Nercis

    2017-12-19

    Background/aim: Head injuries are commonly seen in the pediatric population. Noncontrast enhanced cranial CT is the method of choice to detect possible traumatic brain injury (TBI). Concerns about ionizing radiation exposure make the evaluation more challenging. The aim of this study was to evaluate the effectiveness of the Pediatric Emergency Care Applied Research Network (PECARN) rules in predicting clinically important TBI and to determine the amount of medical resource waste and unnecessary radiation exposure.Materials and methods: This retrospective study included 1041 pediatric patients presented to the emergency department. The patients were divided into subgroups of "appropriate for cranial CT", "not appropriate for cranial CT" and "cranial CT/observation of patient; both are appropriate". To determine the effectiveness of the PECARN rules, data were analyzed according to the presence of pathological findings Results: "Appropriate for cranial CT" results can predict pathology presence 118,056-fold compared to the "not appropriate for cranial CT" results. With "cranial CT/observation of patient; both are appropriate" results, pathology presence was predicted 11,457-fold compared to "not appropriate for cranial CT" results.Conclusion: PECARN rules can predict pathology presence successfully in pediatric TBI. Using PECARN can decrease resource waste and exposure to ionizing radiation.

  4. Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.

    Science.gov (United States)

    Le, Nguyen-Quoc-Khanh; Ou, Yu-Yen

    2016-07-30

    Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9-45 % and its Matthew's correlation coefficient was 0.14-0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron transport proteins and can help biologists understand the functions of the electron transport chain, particularly those of FAD binding sites. We also developed a web server which identifies FAD binding sites in electron transporters available for academics.

  5. Integrated electrification solution for autonomous electrical networks on the basis of RES and energy storage configurations

    International Nuclear Information System (INIS)

    Kaldellis, J.K.

    2008-01-01

    Most medium and small islands of the Aegean Archipelagos face serious infrastructure problems, strongly related with the limited electrical energy available at extremely high cost. On the other hand, the area is characterized by very high wind speeds and abundant solar energy, thus the exploitation of the available renewable energy sources (RES) may significantly contribute to the fulfillment of the local societies energy demand at minimum environmental and macroeconomic cost. However, the stochastic availability of wind energy and the variable availability of solar energy, the daily and seasonal electricity demand fluctuations, as well as the limited local electrical network capacity result in serious restrictions concerning the maximum renewable power penetration. In this context, the present paper investigates the possibility of creating a combined electricity generation facility based on the exploitation of wind or/and solar potential of an area as well as on the utilization of an appropriate energy storage configuration in order to replace the existing thermal power stations with rational investment requirements. For this purpose, the major parameters of the proposed integrated configuration are firstly calculated and its financial viability is accordingly analyzed. One of the main targets of the proposed solution is to maximize the RES exploitation of the area at a minimum electricity generation cost, while special emphasis is given in order to select the most cost-efficient energy storage device available. According to the results obtained the proposed solution is not only financially attractive but also improves the quality of the electricity offered to the local communities, substituting the expensive and heavily polluting existing thermal power stations

  6. Simulation and prediction of the thuringiensin abiotic degradation processes in aqueous solution by a radius basis function neural network model.

    Science.gov (United States)

    Zhou, Jingwen; Xu, Zhenghong; Chen, Shouwen

    2013-04-01

    The thuringiensin abiotic degradation processes in aqueous solution under different conditions, with a pH range of 5.0-9.0 and a temperature range of 10-40°C, were systematically investigated by an exponential decay model and a radius basis function (RBF) neural network model, respectively. The half-lives of thuringiensin calculated by the exponential decay model ranged from 2.72 d to 16.19 d under the different conditions mentioned above. Furthermore, an RBF model with accuracy of 0.1 and SPREAD value 5 was employed to model the degradation processes. The results showed that the model could simulate and predict the degradation processes well. Both the half-lives and the prediction data showed that thuringiensin was an easily degradable antibiotic, which could be an important factor in the evaluation of its safety. Copyright © 2012 Elsevier Ltd. All rights reserved.

  7. Surgical Anatomy of the Radial Nerve at the Elbow and in the Forearm: Anatomical Basis for Intraplexus Nerve Transfer to Reconstruct Thumb and Finger Extension in C7 - T1 Brachial Plexus Palsy.

    Science.gov (United States)

    Zhang, Lei; Dong, Zhen; Zhang, Chun-Lin; Gu, Yu-Dong

    2016-11-01

    Background  C7 - T1 palsy results in complete loss of finger motion and poses a surgical challenge. This study investigated the anatomy of the radial nerve in the elbow and forearm and the feasibility of intraplexus nerve transfer to restore thumb and finger extension. Methods  The radial nerves were dissected in 28 formalin-fixed upper extremities. Branching pattern, length, diameter, and number of myelinated fibers were recorded. Results  Commonly, the branching pattern (from proximal to distal) was to the brachioradialis, extensor carpi radialis longus, superficial sensory proximal to the lateral epicondyle, extensor carpi radialis brevis, supinator, extensor digitorum communis, extensor digiti minimi, extensor carpi ulnaris, abductor pollicis longus, extensor pollicis brevis, extensor pollicis longus, and extensor indicis distal to the lateral epicondyle. Conclusions  Branches to the brachioradialis, extensor carpi radialis longus, and supinator can be transferred to the posterior interosseous nerve to restore hand movement in patients with C7 - T1 brachial plexus palsies; the supinator branch is probably the best choice in this regard. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

  8. Research on Electronic-nose Application Based on Wireless Sensor Networks

    International Nuclear Information System (INIS)

    Zhao, A; Wang, L; Yao, C H

    2006-01-01

    The paper proposed a structure of Wireless Sensor Networks based Electronic-nose system to monitors air quality in the building. In the study, the authors researched a data processing algorithm: fuzzy neural network based on RBF(Radial Basis Function) network model, to quantitatively analyze the gas ingredient and put forward a routing protocol for the system

  9. The Threats Model Construction by means of Fuzzy Cognitive Map on the basis of the Networks Security Policy

    Directory of Open Access Journals (Sweden)

    M. B. Guzairov

    2011-06-01

    Full Text Available The threats matrix construction on the basis of the access matrixes is discussed. Development of threats model on the basis of fuzzy cognitive maps displaying the threats spreading pathways from attack sources to objects is described.

  10. Radial nerve dysfunction (image)

    Science.gov (United States)

    The radial nerve travels down the arm and supplies movement to the triceps muscle at the back of the upper arm. ... the wrist and hand. The usual causes of nerve dysfunction are direct trauma, prolonged pressure on the ...

  11. Spectral problem for the radial Schroedinger equation

    International Nuclear Information System (INIS)

    Vshivtsev, A.S.; Tatarintsev, A.V.; Prokopov, A.V.; Sorokin, V. N.

    1998-01-01

    For the first time, a procedure for determining spectra on the basis of generalized integral transformations is implemented for a wide class of radial Schroedinger equations. It is shown that this procedure works well for known types of potentials. Concurrently, this method makes it possible to obtain new analytic results for the Cornell potential. This may prove important for hadron physics

  12. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  13. Criminal groups and transnational illegal markets : A more detailed examination on the basis of Social Network Theory

    NARCIS (Netherlands)

    Bruinsma, Gerben; Bernasco, Wim

    In the study of organised crime, the traditional view of criminal groups as centrally controlled organisations has been replaced by the notion of criminal networks. However, little use has been made of concepts and theories of social networks that have developed in other social sciences. This paper

  14. Review of Evidence Suggesting That the Fascia Network Could Be the Anatomical Basis for Acupoints and Meridians in the Human Body

    Directory of Open Access Journals (Sweden)

    Yu Bai

    2011-01-01

    Full Text Available The anatomical basis for the concept of meridians in traditional Chinese medicine (TCM has not been resolved. This paper reviews the evidence supporting a relationship between acupuncture points/meridians and fascia. The reviewed evidence supports the view that the human body's fascia network may be the physical substrate represented by the meridians of TCM. Specifically, this hypothesis is supported by anatomical observations of body scan data demonstrating that the fascia network resembles the theoretical meridian system in salient ways, as well as physiological, histological, and clinical observations. This view represents a theoretical basis and means for applying modern biomedical research to examining TCM principles and therapies, and it favors a holistic approach to diagnosis and treatment.

  15. Radial wedge flange clamp

    Science.gov (United States)

    Smith, Karl H.

    2002-01-01

    A radial wedge flange clamp comprising a pair of flanges each comprising a plurality of peripheral flat wedge facets having flat wedge surfaces and opposed and mating flat surfaces attached to or otherwise engaged with two elements to be joined and including a series of generally U-shaped wedge clamps each having flat wedge interior surfaces and engaging one pair of said peripheral flat wedge facets. Each of said generally U-shaped wedge clamps has in its opposing extremities apertures for the tangential insertion of bolts to apply uniform radial force to said wedge clamps when assembled about said wedge segments.

  16. The Network Model of Depression as a Basis for New Therapeutic Strategies for Treating Major Depressive Disorder in Parkinson’s Disease

    Science.gov (United States)

    D’Ostilio, Kevin; Garraux, Gaëtan

    2016-01-01

    The high prevalence of major depressive disorder in people with Parkinson’s disease (PD), its negative impact on health-related quality of life and the low response rate to conventional pharmacological therapies call to seek innovative treatments. Here, we review the new approaches for treating major depressive disorder in patients with PD within the framework of the network model of depression. According to this model, major depressive disorder reflects maladaptive neuronal plasticity. Non-invasive brain stimulation (NIBS) using high frequency repetitive transcranial magnetic stimulation (rTMS) over the prefrontal cortex has been proposed as a feasible and effective strategy with minimal risk. The neurobiological basis of its therapeutic effect may involve neuroplastic modifications in limbic and cognitive networks. However, the way this networks reorganize might be strongly influenced by the environment. To address this issue, we propose a combined strategy that includes NIBS together with cognitive and behavioral interventions. PMID:27148016

  17. Sirenomelia with radial dysplasia.

    Science.gov (United States)

    Kulkarni, M L; Abdul Manaf, K M; Prasannakumar, D G; Kulkarni, Preethi M

    2004-05-01

    Sirenomelia is a rare anomaly usually associated with other multiple malformations. In this communication the authors report a case of sirenomelia associated with multiple malformations, which include radial hypoplasia also. Though several theories have been proposed regarding the etiology of multiple malformation syndromes in the past, the recent theory of primary developmental defect during blastogenesis holds good in this case.

  18. Radially truncated galactic discs

    NARCIS (Netherlands)

    Grijs, R. de; Kregel, M.; Wesson, K H

    2000-01-01

    Abstract: We present the first results of a systematic analysis of radially truncatedexponential discs for four galaxies of a sample of disc-dominated edge-onspiral galaxies. Edge-on galaxies are very useful for the study of truncatedgalactic discs, since we can follow their light distributions out

  19. relay coordination in the protection of radially-connected power

    African Journals Online (AJOL)

    ... PROTECTION OF. RADIALLY-CONNECTED POWER SYSTEM NETWORK ... Protective relays detect intolerable or unwanted conditions within an assigned area, and then trip or open one ... time, and current transformer ratio errors. 2.2.1.

  20. Adiabatic superconducting cells for ultra-low-power artificial neural networks

    Directory of Open Access Journals (Sweden)

    Andrey E. Schegolev

    2016-10-01

    Full Text Available We propose the concept of using superconducting quantum interferometers for the implementation of neural network algorithms with extremely low power dissipation. These adiabatic elements are Josephson cells with sigmoid- and Gaussian-like activation functions. We optimize their parameters for application in three-layer perceptron and radial basis function networks.

  1. Exploring the Neural Basis of Avatar Identification in Pathological Internet Gamers and of Self-Reflection in Pathological Social Network Users.

    Science.gov (United States)

    Leménager, Tagrid; Dieter, Julia; Hill, Holger; Hoffmann, Sabine; Reinhard, Iris; Beutel, Martin; Vollstädt-Klein, Sabine; Kiefer, Falk; Mann, Karl

    2016-09-01

    Background and aims Internet gaming addiction appears to be related to self-concept deficits and increased angular gyrus (AG)-related identification with one's avatar. For increased social network use, a few existing studies suggest striatal-related positive social feedback as an underlying factor. However, whether an impaired self-concept and its reward-based compensation through the online presentation of an idealized version of the self are related to pathological social network use has not been investigated yet. We aimed to compare different stages of pathological Internet game and social network use to explore the neural basis of avatar and self-identification in addictive use. Methods About 19 pathological Internet gamers, 19 pathological social network users, and 19 healthy controls underwent functional magnetic resonance imaging while completing a self-retrieval paradigm, asking participants to rate the degree to which various self-concept-related characteristics described their self, ideal, and avatar. Self-concept-related characteristics were also psychometrically assessed. Results Psychometric testing indicated that pathological Internet gamers exhibited higher self-concept deficits generally, whereas pathological social network users exhibit deficits in emotion regulation only. We observed left AG hyperactivations in Internet gamers during avatar reflection and a correlation with symptom severity. Striatal hypoactivations during self-reflection (vs. ideal reflection) were observed in social network users and were correlated with symptom severity. Discussion and conclusion Internet gaming addiction appears to be linked to increased identification with one's avatar, evidenced by high left AG activations in pathological Internet gamers. Addiction to social networks seems to be characterized by emotion regulation deficits, reflected by reduced striatal activation during self-reflection compared to during ideal reflection.

  2. Exploring the Neural Basis of Avatar Identification in Pathological Internet Gamers and of Self-Reflection in Pathological Social Network Users

    Science.gov (United States)

    Leménager, Tagrid; Dieter, Julia; Hill, Holger; Hoffmann, Sabine; Reinhard, Iris; Beutel, Martin; Vollstädt-Klein, Sabine; Kiefer, Falk; Mann, Karl

    2016-01-01

    Background and aims Internet gaming addiction appears to be related to self-concept deficits and increased angular gyrus (AG)-related identification with one’s avatar. For increased social network use, a few existing studies suggest striatal-related positive social feedback as an underlying factor. However, whether an impaired self-concept and its reward-based compensation through the online presentation of an idealized version of the self are related to pathological social network use has not been investigated yet. We aimed to compare different stages of pathological Internet game and social network use to explore the neural basis of avatar and self-identification in addictive use. Methods About 19 pathological Internet gamers, 19 pathological social network users, and 19 healthy controls underwent functional magnetic resonance imaging while completing a self-retrieval paradigm, asking participants to rate the degree to which various self-concept-related characteristics described their self, ideal, and avatar. Self-concept-related characteristics were also psychometrically assessed. Results Psychometric testing indicated that pathological Internet gamers exhibited higher self-concept deficits generally, whereas pathological social network users exhibit deficits in emotion regulation only. We observed left AG hyperactivations in Internet gamers during avatar reflection and a correlation with symptom severity. Striatal hypoactivations during self-reflection (vs. ideal reflection) were observed in social network users and were correlated with symptom severity. Discussion and conclusion Internet gaming addiction appears to be linked to increased identification with one’s avatar, evidenced by high left AG activations in pathological Internet gamers. Addiction to social networks seems to be characterized by emotion regulation deficits, reflected by reduced striatal activation during self-reflection compared to during ideal reflection. PMID:27415603

  3. Variable stator radial turbine

    Science.gov (United States)

    Rogo, C.; Hajek, T.; Chen, A. G.

    1984-01-01

    A radial turbine stage with a variable area nozzle was investigated. A high work capacity turbine design with a known high performance base was modified to accept a fixed vane stagger angle moveable sidewall nozzle. The nozzle area was varied by moving the forward and rearward sidewalls. Diffusing and accelerating rotor inlet ramps were evaluated in combinations with hub and shroud rotor exit rings. Performance of contoured sidewalls and the location of the sidewall split line with respect to the rotor inlet was compared to the baseline. Performance and rotor exit survey data are presented for 31 different geometries. Detail survey data at the nozzle exit are given in contour plot format for five configurations. A data base is provided for a variable geometry concept that is a viable alternative to the more common pivoted vane variable geometry radial turbine.

  4. Estimation of Radial Runout

    OpenAIRE

    Nilsson, Martin

    2007-01-01

    The demands for ride comfort quality in today's long haulage trucks are constantly growing. A part of the ride comfort problems are represented by internal vibrations caused by rotating mechanical parts. This thesis work focus on the vibrations generated from radial runout on the wheels. These long haulage trucks travel long distances on smooth highways, with a constant speed of 90 km/h resulting in a 7 Hz oscillation. This frequency creates vibrations in the cab, which can be found annoying....

  5. Radial Fuzzy Systems

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    2017-01-01

    Roč. 319, 15 July (2017), s. 1-27 ISSN 0165-0114 R&D Projects: GA MŠk(CZ) LD13002 Institutional support: RVO:67985807 Keywords : fuzzy systems * radial functions * coherence Subject RIV: BA - General Mathematics OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 2.718, year: 2016

  6. Radial Field Piezoelectric Diaphragms

    Science.gov (United States)

    Bryant, R. G.; Effinger, R. T., IV; Copeland, B. M., Jr.

    2002-01-01

    A series of active piezoelectric diaphragms were fabricated and patterned with several geometrically defined Inter-Circulating Electrodes "ICE" and Interdigitated Ring Electrodes "ICE". When a voltage potential is applied to the electrodes, the result is a radially distributed electric field that mechanically strains the piezoceramic along the Z-axis (perpendicular to the applied electric field). Unlike other piezoelectric bender actuators, these Radial Field Diaphragms (RFDs) strain concentrically yet afford high displacements (several times that of the equivalent Unimorph) while maintaining a constant circumference. One of the more intriguing aspects is that the radial strain field reverses itself along the radius of the RFD while the tangential strain remains relatively constant. The result is a Z-deflection that has a conical profile. This paper covers the fabrication and characterization of the 5 cm. (2 in.) diaphragms as a function of poling field strength, ceramic thickness, electrode type and line spacing, as well as the surface topography, the resulting strain field and displacement as a function of applied voltage at low frequencies. The unique features of these RFDs include the ability to be clamped about their perimeter with little or no change in displacement, the environmentally insulated packaging, and a highly repeatable fabrication process that uses commodity materials.

  7. MODELING AND STRUCTURING OF ENTERPRISE MANAGEMENT SYSTEM RESORT SPHERE BASED ON ELEMENTS OF NEURAL NETWORK THEORY: THE METHODOLOGICAL BASIS

    Directory of Open Access Journals (Sweden)

    Rena R. Timirualeeva

    2015-01-01

    Full Text Available The article describes the methodology of modeling andstructuring of business networks theory. Accounting ofenvironmental factors mega-, macro- and mesolevels, theinternal state of the managed system and the error management command execution by control system implemented inthis. The proposed methodology can improve the quality of enterprise management of resort complex through a moreflexible response to changes in the parameters of the internaland external environments.

  8. Cognitive Network Modeling as a Basis for Characterizing Human Communication Dynamics and Belief Contagion in Technology Adoption

    Science.gov (United States)

    Hutto, Clayton; Briscoe, Erica; Trewhitt, Ethan

    2012-01-01

    Societal level macro models of social behavior do not sufficiently capture nuances needed to adequately represent the dynamics of person-to-person interactions. Likewise, individual agent level micro models have limited scalability - even minute parameter changes can drastically affect a model's response characteristics. This work presents an approach that uses agent-based modeling to represent detailed intra- and inter-personal interactions, as well as a system dynamics model to integrate societal-level influences via reciprocating functions. A Cognitive Network Model (CNM) is proposed as a method of quantitatively characterizing cognitive mechanisms at the intra-individual level. To capture the rich dynamics of interpersonal communication for the propagation of beliefs and attitudes, a Socio-Cognitive Network Model (SCNM) is presented. The SCNM uses socio-cognitive tie strength to regulate how agents influence--and are influenced by--one another's beliefs during social interactions. We then present experimental results which support the use of this network analytical approach, and we discuss its applicability towards characterizing and understanding human information processing.

  9. Perceived radial translation during centrifugation

    NARCIS (Netherlands)

    Bos, J.E.; Correia Grácio, B.J.

    2015-01-01

    BACKGROUND: Linear acceleration generally gives rise to translation perception. Centripetal acceleration during centrifugation, however, has never been reported giving rise to a radial, inward translation perception. OBJECTIVE: To study whether centrifugation can induce a radial translation

  10. Computer model analysis of the radial artery pressure waveform.

    Science.gov (United States)

    Schwid, H A; Taylor, L A; Smith, N T

    1987-10-01

    Simultaneous measurements of aortic and radial artery pressures are reviewed, and a model of the cardiovascular system is presented. The model is based on resonant networks for the aorta and axillo-brachial-radial arterial system. The model chosen is a simple one, in order to make interpretation of the observed relationships clear. Despite its simplicity, the model produces realistic aortic and radial artery pressure waveforms. It demonstrates that the resonant properties of the arterial wall significantly alter the pressure waveform as it is propagated from the aorta to the radial artery. Although the mean and end-diastolic radial pressures are usually accurate estimates of the corresponding aortic pressures, the systolic pressure at the radial artery is often much higher than that of the aorta due to overshoot caused by the resonant behavior of the radial artery. The radial artery dicrotic notch is predominantly dependent on the axillo-brachial-radial arterial wall properties, rather than on the aortic valve or peripheral resistance. Hence the use of the radial artery dicrotic notch as an estimate of end systole is unreliable. The rate of systolic upstroke, dP/dt, of the radial artery waveform is a function of many factors, making it difficult to interpret. The radial artery waveform usually provides accurate estimates for mean and diastolic aortic pressures; for all other measurements it is an inadequate substitute for the aortic pressure waveform. In the presence of low forearm peripheral resistance the mean radial artery pressure may significantly underestimate the mean aortic pressure, as explained by a voltage divider model.

  11. A Radial Basis Function Approach to Financial Time Series Analysis

    Science.gov (United States)

    1993-12-01

    consequently this approach is at the core of a large fraction of the portfolio management systems today. The Capital Asset Pricing Model ( CAPM ). due...representation used by each method. but of course a critical concern is how to actually estimate the parameters of the models. To sonic extent these...model fitting unseen data nicely depends critically on maintaining a balance between the number of data points used for estimation and the number of

  12. Predicting the occurrence of rainfall using improved radial basis ...

    African Journals Online (AJOL)

    Journal of Computer Science and Its Application. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue · Archives · Journal Home > Vol 22, No 2 (2015) >. Log in or Register to get access to full text downloads.

  13. Radial reflection diffraction tomography

    Science.gov (United States)

    Lehman, Sean K.

    2012-12-18

    A wave-based tomographic imaging method and apparatus based upon one or more rotating radially outward oriented transmitting and receiving elements have been developed for non-destructive evaluation. At successive angular locations at a fixed radius, a predetermined transmitting element can launch a primary field and one or more predetermined receiving elements can collect the backscattered field in a "pitch/catch" operation. A Hilbert space inverse wave (HSIW) algorithm can construct images of the received scattered energy waves using operating modes chosen for a particular application. Applications include, improved intravascular imaging, bore hole tomography, and non-destructive evaluation (NDE) of parts having existing access holes.

  14. Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders.

    Science.gov (United States)

    Zhang, Jie; Cheng, Wei; Liu, Zhaowen; Zhang, Kai; Lei, Xu; Yao, Ye; Becker, Benjamin; Liu, Yicen; Kendrick, Keith M; Lu, Guangming; Feng, Jianfeng

    2016-08-01

    SEE MATTAR ET AL DOI101093/AWW151 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Functional brain networks demonstrate significant temporal variability and dynamic reconfiguration even in the resting state. Currently, most studies investigate temporal variability of brain networks at the scale of single (micro) or whole-brain (macro) connectivity. However, the mechanism underlying time-varying properties remains unclear, as the coupling between brain network variability and neural activity is not readily apparent when analysed at either micro or macroscales. We propose an intermediate (meso) scale analysis and characterize temporal variability of the functional architecture associated with a particular region. This yields a topography of variability that reflects the whole-brain and, most importantly, creates an analytical framework to establish the fundamental relationship between variability of regional functional architecture and its neural activity or structural connectivity. We find that temporal variability reflects the dynamical reconfiguration of a brain region into distinct functional modules at different times and may be indicative of brain flexibility and adaptability. Primary and unimodal sensory-motor cortices demonstrate low temporal variability, while transmodal areas, including heteromodal association areas and limbic system, demonstrate the high variability. In particular, regions with highest variability such as hippocampus/parahippocampus, inferior and middle temporal gyrus, olfactory gyrus and caudate are all related to learning, suggesting that the temporal variability may indicate the level of brain adaptability. With simultaneously recorded electroencephalography/functional magnetic resonance imaging and functional magnetic resonance imaging/diffusion tensor imaging data, we also find that variability of regional functional architecture is modulated by local blood oxygen level-dependent activity and α-band oscillation, and is governed by the

  15. Modeling of mass transfer of Phospholipids in separation process with supercritical CO2 fluid by RBF artificial neural networks

    Science.gov (United States)

    An artificial Radial Basis Function (RBF) neural network model was developed for the prediction of mass transfer of the phospholipids from canola meal in supercritical CO2 fluid. The RBF kind of artificial neural networks (ANN) with orthogonal least squares (OLS) learning algorithm were used for mod...

  16. Compensation for unmatched uncertainty with adaptive RBF network

    African Journals Online (AJOL)

    Robust control for nonlinear uncertain systems has been solved for matched uncertainty but has not been completely solved yet for unmatched uncertainty. This paper developed a new method in which an adaptive radial basis function neural network is used to compensate for the effects of unmatched uncertainty in the ...

  17. Abstract behaviour modelling and prognosis on the basis of spatially distributed sensor networks with Kohonen cards and Markov chains; Abstrakte Verhaltensmodellierung und -prognose auf der Basis raeumlich verteilter Sensornetze mit Kohonen-Karten und Markov-Ketten

    Energy Technology Data Exchange (ETDEWEB)

    Matthes, J.; Keller, H.B.; Mikut, R. [Forschungszentrum Karlsruhe GmbH Technik und Umwelt (Germany). Inst. fuer Angewandte Informatik

    2000-10-01

    Evironmental processes, e.g. local air quality changes in urban agglomerations, buildings and production halls are dynamic processes with regionally distributed physical variables. They can be monitored by networks of distributed measuring probes. Processes of this type form the basis of complex systems with many degrees of freedom and stochastic effects that are difficult to measure. The contribution presents an introduction to Markov chains, proposes a method of generating Markov chains as a prognostic model, and demonstrates the method using the example of an air quality monitoring process. [German] Fuer die Ueberwachung dynamischer Prozesse, deren physikalische Groessen raeumlich verteilt auftreten, werden oft Netze raeumlich verteilter Sensoren eingesetzt. Umweltprozesse, wie z.B. die oertliche Luftqualitaetsaenderung in Ballungsraeumen, Gebaeuden und Produktionsanlagen, aber auch verschiedene verfahrenstechnische Prozesse sind Vertreter dieser Prozessklasse. Solchen Prozessen hinterliegen komplexe Systeme, die durch eine hohe Anzahl an Freiheitsgraden und durch stochastische schwer messbare Einfluesse gekennzeichnet sind. Ziel dieses Vortrages ist es, - eine kurze Einfuehrung zu Markov-Ketten zu gegeben (Abschnitt 2); - ein datengestuetztes Verfahren vorzuschlagen, das nach einer Schaetzung abstrakter Prozesszustaende mit Hilfe von Kohonen-Karten Markov-Ketten als Prognosemodell generiert (Abschnitt 3), und - dieses Verfahren anhand eines Simulationsbeispiels zur Luftqualitaetsueberwachung zu demonstrieren (Abschnitt 4). (orig.)

  18. Genetic Basis for Developmental Homeostasis of Germline Stem Cell Niche Number: A Network of Tramtrack-Group Nuclear BTB Factors

    Science.gov (United States)

    Chalvet, Fabienne; Netter, Sophie; Dos Santos, Nicolas; Poisot, Emilie; Paces-Fessy, Mélanie; Cumenal, Delphine; Peronnet, Frédérique; Pret, Anne-Marie; Théodore, Laurent

    2012-01-01

    The potential to produce new cells during adult life depends on the number of stem cell niches and the capacity of stem cells to divide, and is therefore under the control of programs ensuring developmental homeostasis. However, it remains generally unknown how the number of stem cell niches is controlled. In the insect ovary, each germline stem cell (GSC) niche is embedded in a functional unit called an ovariole. The number of ovarioles, and thus the number of GSC niches, varies widely among species. In Drosophila, morphogenesis of ovarioles starts in larvae with the formation of terminal filaments (TFs), each made of 8–10 cells that pile up and sort in stacks. TFs constitute organizers of individual germline stem cell niches during larval and early pupal development. In the Drosophila melanogaster subgroup, the number of ovarioles varies interspecifically from 8 to 20. Here we show that pipsqueak, Trithorax-like, batman and the bric-à-brac (bab) locus, all encoding nuclear BTB/POZ factors of the Tramtrack Group, are involved in limiting the number of ovarioles in D. melanogaster. At least two different processes are differentially perturbed by reducing the function of these genes. We found that when the bab dose is reduced, sorting of TF cells into TFs was affected such that each TF contains fewer cells and more TFs are formed. In contrast, psq mutants exhibited a greater number of TF cells per ovary, with a normal number of cells per TF, thereby leading to formation of more TFs per ovary than in the wild type. Our results indicate that two parallel genetic pathways under the control of a network of nuclear BTB factors are combined in order to negatively control the number of germline stem cell niches. PMID:23185495

  19. Radial semiconductor drift chambers

    International Nuclear Information System (INIS)

    Rawlings, K.J.

    1987-01-01

    The conditions under which the energy resolution of a radial semiconductor drift chamber based detector system becomes dominated by the step noise from the detector dark current have been investigated. To minimise the drift chamber dark current attention should be paid to carrier generation at Si/SiO 2 interfaces. This consideration conflicts with the desire to reduce the signal risetime: a higher drift field for shorter signal pulses requires a larger area of SiO 2 . Calculations for the single shaping and pseudo Gaussian passive filters indicate that for the same degree of signal risetime sensitivity in a system dominated by the step noise from the detector dark current, the pseudo Gaussian filter gives only a 3% improvement in signal/noise and 12% improvement in rate capability compared with the single shaper performance. (orig.)

  20. ISR Radial Field Magnet

    CERN Multimedia

    1983-01-01

    There were 37 (normal) + 3 (special) Radial Field magnets in the ISR to adjust vertically the closed orbit. Gap heights and strengths were 200 mm and .12 Tm in the normal magnets, 220 mm and .18 Tm in the special ones. The core length was 430 mm in both types. Due to their small length as compared to the gap heights the end fringe field errors were very important and had to be compensated by suitably shaping the poles. In order to save on cables, as these magnets were located very far from their power supplies, the coils of the normal type magnets were formed by many turns of solid cpper conductor with some interleaved layers of hollow conductor directly cooled by circulating water

  1. The ARCS radial collimator

    International Nuclear Information System (INIS)

    Stone, M.B.; Abernathy, D.L.; Niedziela, J.L.; Overbay, M.A.

    2015-01-01

    We have designed, installed, and commissioned a scattered beam radial collimator for use at the ARCS Wide Angular Range Chopper Spectrometer at the Spallation Neutron Source. The collimator has been designed to work effectively for thermal and epithermal neutrons and with a range of sample environments. Other design considerations include the accommodation of working within a high vacuum environment and having the ability to quickly install and remove the collimator from the scattered beam. The collimator is composed of collimating blades (or septa). The septa are 12 micron thick Kapton foils coated on each side with 39 microns of enriched boron carbide ( 10 B 4 C with 10 B > 96%) in an ultra-high vacuum compatible binder. The collimator blades represent an additional 22 m 2 of surface area. In the article we present collimator's design and performance and methodologies for its effective use

  2. Introducing radiality constraints in capacitated location-routing problems

    Directory of Open Access Journals (Sweden)

    Eliana Mirledy Toro Ocampo

    2017-03-01

    Full Text Available In this paper, we introduce a unified mathematical formulation for the Capacitated Vehicle Routing Problem (CVRP and for the Capacitated Location Routing Problem (CLRP, adopting radiality constraints in order to guarantee valid routes and eliminate subtours. This idea is inspired by formulations already employed in electric power distribution networks, which requires a radial topology in its operation. The results show that the proposed formulation greatly improves the convergence of the solver.

  3. Predicting risk for portal vein thrombosis in acute pancreatitis patients: A comparison of radical basis function artificial neural network and logistic regression models.

    Science.gov (United States)

    Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei

    2017-06-01

    To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (Plogistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Antiproton compression and radial measurements

    CERN Document Server

    Andresen, G B; Bowe, P D; Bray, C C; Butler, E; Cesar, C L; Chapman, S; Charlton, M; Fajans, J; Fujiwara, M C; Funakoshi, R; Gill, D R; Hangst, J S; Hardy, W N; Hayano, R S; Hayden, M E; Humphries, A J; Hydomako, R; Jenkins, M J; Jorgensen, L V; Kurchaninov, L; Lambo, R; Madsen, N; Nolan, P; Olchanski, K; Olin, A; Page R D; Povilus, A; Pusa, P; Robicheaux, F; Sarid, E; Seif El Nasr, S; Silveira, D M; Storey, J W; Thompson, R I; Van der Werf, D P; Wurtele, J S; Yamazaki, Y

    2008-01-01

    Control of the radial profile of trapped antiproton clouds is critical to trapping antihydrogen. We report detailed measurements of the radial manipulation of antiproton clouds, including areal density compressions by factors as large as ten, achieved by manipulating spatially overlapped electron plasmas. We show detailed measurements of the near-axis antiproton radial profile, and its relation to that of the electron plasma. We also measure the outer radial profile by ejecting antiprotons to the trap wall using an octupole magnet.

  5. Study on the value of flexibility in the management and design basis of distribution networks in France. Summary - Version dated 7 December 2015

    International Nuclear Information System (INIS)

    2015-01-01

    ;net' value of flexibility is defined as the difference between income and costs. Only the direct economic value of flexibility is analysed in this report: the environmental impact and knock-on effect on employment are not taken into consideration. Furthermore, study of the market design of flexibility (contracting method, division of responsibilities, financial equalization, etc.) is not included in the scope of the study. In conclusion, this study shows that flexibility is of value for electricity distribution networks, at least from a theoretical point of view in some of the 'case studies', and in all likelihood also in practice, in certain situations. However, this study does not provide any results on the overall potential of the value of flexibility at national level. Several other studies must be undertaken to determine this potential, as well as to define the regulatory framework and the market design that would promote its use for the national community. Incorporating failure of the flexibility in terms of its design basis, the sharing of responsibility and penalties resulting from failure will be some of the decisive factors in successfully using the flexibility

  6. Neural networks and statistical learning

    CERN Document Server

    Du, Ke-Lin

    2014-01-01

    Providing a broad but in-depth introduction to neural network and machine learning in a statistical framework, this book provides a single, comprehensive resource for study and further research. All the major popular neural network models and statistical learning approaches are covered with examples and exercises in every chapter to develop a practical working understanding of the content. Each of the twenty-five chapters includes state-of-the-art descriptions and important research results on the respective topics. The broad coverage includes the multilayer perceptron, the Hopfield network, associative memory models, clustering models and algorithms, the radial basis function network, recurrent neural networks, principal component analysis, nonnegative matrix factorization, independent component analysis, discriminant analysis, support vector machines, kernel methods, reinforcement learning, probabilistic and Bayesian networks, data fusion and ensemble learning, fuzzy sets and logic, neurofuzzy models, hardw...

  7. Fault detection for hydraulic pump based on chaotic parallel RBF network

    Directory of Open Access Journals (Sweden)

    Ma Ning

    2011-01-01

    Full Text Available Abstract In this article, a parallel radial basis function network in conjunction with chaos theory (CPRBF network is presented, and applied to practical fault detection for hydraulic pump, which is a critical component in aircraft. The CPRBF network consists of a number of radial basis function (RBF subnets connected in parallel. The number of input nodes for each RBF subnet is determined by different embedding dimension based on chaotic phase-space reconstruction. The output of CPRBF is a weighted sum of all RBF subnets. It was first trained using the dataset from normal state without fault, and then a residual error generator was designed to detect failures based on the trained CPRBF network. Then, failure detection can be achieved by the analysis of the residual error. Finally, two case studies are introduced to compare the proposed CPRBF network with traditional RBF networks, in terms of prediction and detection accuracy.

  8. On the chromospheric network structure around deVeloped groups of sunspots

    International Nuclear Information System (INIS)

    Kartashova, L.G.

    1980-01-01

    The chromospheric network structure around several developed groups of sunspots were studied on the basis of the observations in the Hsub(α) line. The resolution on the filtergrams was of 2. The following was found: 1) in the neighbourhood of the groups of sunspots 70% (from 870) of network cells stretch along fibrils direction (with accuracy 30 deg), and 15% of cells stretch approximately across that (at angles 70-90 deg); 2) out of the boundary of the main radial fibrils structure the groups of sunspots is often rounded by the system of network cells stretched approximately perpendicular to radial direction

  9. Development of Artificial Neural Network Model for Diesel Fuel Properties Prediction using Vibrational Spectroscopy.

    Science.gov (United States)

    Bolanča, Tomislav; Marinović, Slavica; Ukić, Sime; Jukić, Ante; Rukavina, Vinko

    2012-06-01

    This paper describes development of artificial neural network models which can be used to correlate and predict diesel fuel properties from several FTIR-ATR absorbances and Raman intensities as input variables. Multilayer feed forward and radial basis function neural networks have been used to rapid and simultaneous prediction of cetane number, cetane index, density, viscosity, distillation temperatures at 10% (T10), 50% (T50) and 90% (T90) recovery, contents of total aromatics and polycyclic aromatic hydrocarbons of commercial diesel fuels. In this study two-phase training procedures for multilayer feed forward networks were applied. While first phase training algorithm was constantly the back propagation one, two second phase training algorithms were varied and compared, namely: conjugate gradient and quasi Newton. In case of radial basis function network, radial layer was trained using K-means radial assignment algorithm and three different radial spread algorithms: explicit, isotropic and K-nearest neighbour. The number of hidden layer neurons and experimental data points used for the training set have been optimized for both neural networks in order to insure good predictive ability by reducing unnecessary experimental work. This work shows that developed artificial neural network models can determine main properties of diesel fuels simultaneously based on a single and fast IR or Raman measurement.

  10. Radial expansion and multifragmentation

    International Nuclear Information System (INIS)

    Angelique, J.C.; Bizard, G.; Bougault, R.; Brou, R.; Buta, A.; Colin, J.; Cussol, D.; Durand, D.; Kerambrun, A.; Le Brun, C.; Lecolley, J.F.; Lopez, O.; Louvel, M.; Meslin, C.; Nakagawa, T.; Patry, J.P.; Peter, J.; Popescu, R.; Regimbart, R.; Steckmeyer, J.C.; Tamain, B.; Vient, E.; Yuasa-Nakagawa, K.; Wieloch, A.

    1998-01-01

    The light systems 36 Ar + 27 Al and 64 Zn + nat Ti were measured at several bombarding energies between ∼ 35 and 95 MeV/nucleon. It was found that the predominant part of the cross section is due to binary collisions. In this paper the focus is placed on the properties of the quasi-projectile nuclei. In the central collisions the excitation energies of the quasi-projectile reach values exceeding largely 10 MeV/nucleon. The slope of the high energy part of the distribution can give only an upper limit of the apparent temperature (the average temperature along the decay chain). The highly excited quasi-projectile may get rapidly fragmented rather than sequentially. The heavy fragments are excited and can emit light particles (n, p, d, t, 3 He, α,...) what perturbs additionally the spectrum of these particles. Concerning the expansion energy, one can determine the average kinetic energies of the product (in the quasi-projectile-framework) and compare with simulation values. To fit the experimental data an additional radial expansion energy is to be considered. The average expansion energy depends slightly on the impact parameter but it increases with E * / A, ranging from 0.4 to 1,2 MeV/nucleon for an excitation energy increasing from 7 to 10.5 MeV/nucleon. This collective radial energy seems to be independent of the fragment mass, what is possibly valid for the case of larger quasi-projectile masses. The origin of the expansion is to be determined. It may be due to a compression in the interaction zone at the initial stage of the collision, which propagates in the quasi-projectile and quasi-target, or else, may be due, simply, to the increase of thermal energy leading to a rapid fragment emission. The sequential de-excitation calculation overestimates light particle emission and consequently heavy residues, particularly, at higher excitation energies. This disagreement indicates that a sequential process can not account for the di-excitation of very hot nuclei

  11. Nodes and biological processes identified on the basis of network analysis in the brain of the senescence accelerated mice as an Alzheimer’s disease animal model

    Directory of Open Access Journals (Sweden)

    Xiao-Rui eCheng

    2013-10-01

    Full Text Available Harboring the behavioral and histopathological signatures of Alzheimer’s disease (AD, senescence accelerated mouse-prone 8 (SAMP8 mice are currently considered a robust model for studying AD. However, the underlying mechanisms, prioritized pathways and genes in SAMP8 mice linked to AD remain unclear. In this study, we provide a biological interpretation of the molecular underpinnings of SAMP8 mice. Our results were derived from differentially expressed genes in the hippocampus and cerebral cortex of SAMP8 mice compared to age-matched SAMR1 mice at 2, 6, and 12 months of age using cDNA microarray analysis. On the basis of PPI, MetaCore and the co-expression network, we constructed a distinct genetic sub-network in the brains of SAMP8 mice. Next, we determined that the regulation of synaptic transmission and apoptosis were disrupted in the brains of SAMP8 mice. We found abnormal gene expression of RAF1, MAPT, PTGS2, CDKN2A, CAMK2A, NTRK2, AGER, ADRBK1, MCM3AP and STUB1, which may have initiated the dysfunction of biological processes in the brains of SAMP8 mice. Specifically, we found microRNAs, including miR-20a, miR-17, miR-34a, miR-155, miR-18a, miR-22, miR-26a, miR-101, miR-106b and miR-125b, that might regulate the expression of nodes in the sub-network. Taken together, these results provide new insights into the biological and genetic mechanisms of SAMP8 mice and add an important dimension to our understanding of the neuro-pathogenesis in SAMP8 mice from a systems perspective.

  12. A Sliding Mode Control-based on a RBF Neural Network for Deburring Industry Robotic Systems

    OpenAIRE

    Tao, Yong; Zheng, Jiaqi; Lin, Yuanchang

    2016-01-01

    A sliding mode control method based on radial basis function (RBF) neural network is proposed for the deburring of industry robotic systems. First, a dynamic model for deburring the robot system is established. Then, a conventional SMC scheme is introduced for the joint position tracking of robot manipulators. The RBF neural network based sliding mode control (RBFNN-SMC) has the ability to learn uncertain control actions. In the RBFNN-SMC scheme, the adaptive tuning algorithms for network par...

  13. Radial gas turbine design

    Energy Technology Data Exchange (ETDEWEB)

    Krausche, S.; Ohlsson, Johan

    1998-04-01

    The objective of this work was to develop a program dealing with design point calculations of radial turbine machinery, including both compressor and turbine, with as few input data as possible. Some simple stress calculations and turbine metal blade temperatures were also included. This program was then implanted in a German thermodynamics program, Gasturb, a program calculating design and off-design performance of gas turbines. The calculations proceed with a lot of assumptions, necessary to finish the task, concerning pressure losses, velocity distribution, blockage, etc., and have been correlated with empirical data from VAT. Most of these values could have been input data, but to prevent the user of the program from drowning in input values, they are set as default values in the program code. The output data consist of geometry, Mach numbers, predicted component efficiency etc., and a number of graphical plots of geometry and velocity triangles. For the cases examined, the error in predicted efficiency level was within {+-} 1-2% points, and quite satisfactory errors in geometrical and thermodynamic conditions were obtained Examination paper. 18 refs, 36 figs

  14. Radial flow heat exchanger

    Science.gov (United States)

    Valenzuela, Javier

    2001-01-01

    A radial flow heat exchanger (20) having a plurality of first passages (24) for transporting a first fluid (25) and a plurality of second passages (26) for transporting a second fluid (27). The first and second passages are arranged in stacked, alternating relationship, are separated from one another by relatively thin plates (30) and (32), and surround a central axis (22). The thickness of the first and second passages are selected so that the first and second fluids, respectively, are transported with laminar flow through the passages. To enhance thermal energy transfer between first and second passages, the latter are arranged so each first passage is in thermal communication with an associated second passage along substantially its entire length, and vice versa with respect to the second passages. The heat exchangers may be stacked to achieve a modular heat exchange assembly (300). Certain heat exchangers in the assembly may be designed slightly differently than other heat exchangers to address changes in fluid properties during transport through the heat exchanger, so as to enhance overall thermal effectiveness of the assembly.

  15. Neural network post-processing of grayscale optical correlator

    Science.gov (United States)

    Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

    2005-01-01

    In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

  16. Stability of radial swirl flows

    International Nuclear Information System (INIS)

    Dou, H S; Khoo, B C

    2012-01-01

    The energy gradient theory is used to examine the stability of radial swirl flows. It is found that the flow of free vortex is always stable, while the introduction of a radial flow will induce the flow to be unstable. It is also shown that the pure radial flow is stable. Thus, there is a flow angle between the pure circumferential flow and the pure radial flow at which the flow is most unstable. It is demonstrated that the magnitude of this flow angle is related to the Re number based on the radial flow rate, and it is near the pure circumferential flow. The result obtained in this study is useful for the design of vaneless diffusers of centrifugal compressors and pumps as well as other industrial devices.

  17. A comparison of neural network architectures for the prediction of MRR in EDM

    Science.gov (United States)

    Jena, A. R.; Das, Raja

    2017-11-01

    The aim of the research work is to predict the material removal rate of a work-piece in electrical discharge machining (EDM). Here, an effort has been made to predict the material removal rate through back-propagation neural network (BPN) and radial basis function neural network (RBFN) for a work-piece of AISI D2 steel. The input parameters for the architecture are discharge-current (Ip), pulse-duration (Ton), and duty-cycle (τ) taken for consideration to obtained the output for material removal rate of the work-piece. In the architecture, it has been observed that radial basis function neural network is comparatively faster than back-propagation neural network but logically back-propagation neural network results more real value. Therefore BPN may consider as a better process in this architecture for consistent prediction to save time and money for conducting experiments.

  18. Comparing Two Methods of Neural Networks to Evaluate Dead Oil Viscosity

    Directory of Open Access Journals (Sweden)

    Meysam Dabiri-Atashbeyk

    2018-01-01

    Full Text Available Reservoir characterization and asset management require comprehensive information about formation fluids. In fact, it is not possible to find accurate solutions to many petroleum engineering problems without having accurate pressure-volume-temperature (PVT data. Traditionally, fluid information has been obtained by capturing samples and then by measuring the PVT properties in a laboratory. In recent years, neural network has been applied to a large number of petroleum engineering problems. In this paper, a multi-layer perception neural network and radial basis function network (both optimized by a genetic algorithm were used to evaluate the dead oil viscosity of crude oil, and it was found out that the estimated dead oil viscosity by the multi-layer perception neural network was more accurate than the one obtained by radial basis function network.

  19. Radial retinotomy in the macula.

    Science.gov (United States)

    Bovino, J A; Marcus, D F

    1984-01-01

    Radial retinotomy is an operative procedure usually performed in the peripheral or equatorial retina. To facilitate retinal attachment, the authors used intraocular scissors to perform radial retinotomy in the macula of two patients during vitrectomy surgery. In the first patient, a retinal detachment complicated by periretinal proliferation and macula hole formation was successfully reoperated with the aid of three radial cuts in the retina at the edges of the macular hole. In the second patient, an intraoperative retinal tear in the macula during diabetic vitrectomy was also successfully repaired with the aid of radial retinotomy. In both patients, retinotomy in the macula was required because epiretinal membranes, which could not be easily delaminated, were hindering retinal reattachment.

  20. Detonation in supersonic radial outflow

    KAUST Repository

    Kasimov, Aslan R.; Korneev, Svyatoslav

    2014-01-01

    We report on the structure and dynamics of gaseous detonation stabilized in a supersonic flow emanating radially from a central source. The steady-state solutions are computed and their range of existence is investigated. Two-dimensional simulations

  1. Dedicated radial ventriculography pigtail catheter

    Energy Technology Data Exchange (ETDEWEB)

    Vidovich, Mladen I., E-mail: miv@uic.edu

    2013-05-15

    A new dedicated cardiac ventriculography catheter was specifically designed for radial and upper arm arterial access approach. Two catheter configurations have been developed to facilitate retrograde crossing of the aortic valve and to conform to various subclavian, ascending aortic and left ventricular anatomies. The “short” dedicated radial ventriculography catheter is suited for horizontal ascending aortas, obese body habitus, short stature and small ventricular cavities. The “long” dedicated radial ventriculography catheter is suited for vertical ascending aortas, thin body habitus, tall stature and larger ventricular cavities. This new design allows for improved performance, faster and simpler insertion in the left ventricle which can reduce procedure time, radiation exposure and propensity for radial artery spasm due to excessive catheter manipulation. Two different catheter configurations allow for optimal catheter selection in a broad range of patient anatomies. The catheter is exceptionally stable during contrast power injection and provides equivalent cavity opacification to traditional femoral ventriculography catheter designs.

  2. Improvement of the electromagnetic situation in networks of operational current at nuclear power plant for the purpose of ensuring reliability of monitoring systems, control, RPA and communications, realized on the basis of digital equipment

    International Nuclear Information System (INIS)

    Fomenko, O.V.; Moloshnaya, E.S.; Ul'yanova, Yu.E.

    2014-01-01

    The authors propose the technique of designing a portable grounding contour for protection and control systems, relay protection and automation (RPA) systems made on the basis of digital equipment in networks of an operational direct current to increase the reliability of their functioning under the conditions of influence of strong hindrances and improvement of an electromagnetic environment [ru

  3. QSAR modelling using combined simple competitive learning networks and RBF neural networks.

    Science.gov (United States)

    Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

    2018-04-01

    The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

  4. Radial lean direct injection burner

    Science.gov (United States)

    Khan, Abdul Rafey; Kraemer, Gilbert Otto; Stevenson, Christian Xavier

    2012-09-04

    A burner for use in a gas turbine engine includes a burner tube having an inlet end and an outlet end; a plurality of air passages extending axially in the burner tube configured to convey air flows from the inlet end to the outlet end; a plurality of fuel passages extending axially along the burner tube and spaced around the plurality of air passage configured to convey fuel from the inlet end to the outlet end; and a radial air swirler provided at the outlet end configured to direct the air flows radially toward the outlet end and impart swirl to the air flows. The radial air swirler includes a plurality of vanes to direct and swirl the air flows and an end plate. The end plate includes a plurality of fuel injection holes to inject the fuel radially into the swirling air flows. A method of mixing air and fuel in a burner of a gas turbine is also provided. The burner includes a burner tube including an inlet end, an outlet end, a plurality of axial air passages, and a plurality of axial fuel passages. The method includes introducing an air flow into the air passages at the inlet end; introducing a fuel into fuel passages; swirling the air flow at the outlet end; and radially injecting the fuel into the swirling air flow.

  5. Separation prediction in two dimensional boundary layer flows using artificial neural networks

    International Nuclear Information System (INIS)

    Sabetghadam, F.; Ghomi, H.A.

    2003-01-01

    In this article, the ability of artificial neural networks in prediction of separation in steady two dimensional boundary layer flows is studied. Data for network training is extracted from numerical solution of an ODE obtained from Von Karman integral equation with approximate one parameter Pohlhousen velocity profile. As an appropriate neural network, a two layer radial basis generalized regression artificial neural network is used. The results shows good agreements between the overall behavior of the flow fields predicted by the artificial neural network and the actual flow fields for some cases. The method easily can be extended to unsteady separation and turbulent as well as compressible boundary layer flows. (author)

  6. Self-consistent radial sheath

    International Nuclear Information System (INIS)

    Hazeltine, R.D.

    1988-12-01

    The boundary layer arising in the radial vicinity of a tokamak limiter is examined, with special reference to the TEXT tokamak. It is shown that sheath structure depends upon the self-consistent effects of ion guiding-center orbit modification, as well as the radial variation of E /times/ B-induced toroidal rotation. Reasonable agreement with experiment is obtained from an idealized model which, however simplified, preserves such self-consistent effects. It is argued that the radial sheath, which occurs whenever confining magnetic field-lines lie in the plasma boundary surface, is an object of some intrinsic interest. It differs from the more familiar axial sheath because magnetized charges respond very differently to parallel and perpendicular electric fields. 11 refs., 1 fig

  7. Detonation in supersonic radial outflow

    KAUST Repository

    Kasimov, Aslan R.

    2014-11-07

    We report on the structure and dynamics of gaseous detonation stabilized in a supersonic flow emanating radially from a central source. The steady-state solutions are computed and their range of existence is investigated. Two-dimensional simulations are carried out in order to explore the stability of the steady-state solutions. It is found that both collapsing and expanding two-dimensional cellular detonations exist. The latter can be stabilized by putting several rigid obstacles in the flow downstream of the steady-state sonic locus. The problem of initiation of standing detonation stabilized in the radial flow is also investigated numerically. © 2014 Cambridge University Press.

  8. General-Purpose Computation with Neural Networks: A Survey of Complexity Theoretic Results

    Czech Academy of Sciences Publication Activity Database

    Šíma, Jiří; Orponen, P.

    2003-01-01

    Roč. 15, č. 12 (2003), s. 2727-2778 ISSN 0899-7667 R&D Projects: GA AV ČR IAB2030007; GA ČR GA201/02/1456 Institutional research plan: AV0Z1030915 Keywords : computational power * computational complexity * perceptrons * radial basis functions * spiking neurons * feedforward networks * reccurent networks * probabilistic computation * analog computation Subject RIV: BA - General Mathematics Impact factor: 2.747, year: 2003

  9. Training the Recurrent neural network by the Fuzzy Min-Max algorithm for fault prediction

    International Nuclear Information System (INIS)

    Zemouri, Ryad; Racoceanu, Daniel; Zerhouni, Noureddine; Minca, Eugenia; Filip, Florin

    2009-01-01

    In this paper, we present a training technique of a Recurrent Radial Basis Function neural network for fault prediction. We use the Fuzzy Min-Max technique to initialize the k-center of the RRBF neural network. The k-means algorithm is then applied to calculate the centers that minimize the mean square error of the prediction task. The performances of the k-means algorithm are then boosted by the Fuzzy Min-Max technique.

  10. Vortex Whistle in Radial Intake

    National Research Council Canada - National Science Library

    Tse, Man-Chun

    2004-01-01

    In a radial-to-axial intake with inlet guide vanes (IGV) at the entry, a strong flow circulation Gamma can be generated from the tangential flow components created by the IGVs when their setting exceed about halfclosing (approx. 45 deg...

  11. Radial head dislocation during proximal radial shaft osteotomy.

    Science.gov (United States)

    Hazel, Antony; Bindra, Randy R

    2014-03-01

    The following case report describes a 48-year-old female patient with a longstanding both-bone forearm malunion, who underwent osteotomies of both the radius and ulna to improve symptoms of pain and lack of rotation at the wrist. The osteotomies were templated preoperatively. During surgery, after performing the planned radial shaft osteotomy, the authors recognized that the radial head was subluxated. The osteotomy was then revised from an opening wedge to a closing wedge with improvement of alignment and rotation. The case report discusses the details of the operation, as well as ways in which to avoid similar shortcomings in the future. Copyright © 2014 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

  12. Comparison of Deterministic and Probabilistic Radial Distribution Systems Load Flow

    Science.gov (United States)

    Gupta, Atma Ram; Kumar, Ashwani

    2017-12-01

    Distribution system network today is facing the challenge of meeting increased load demands from the industrial, commercial and residential sectors. The pattern of load is highly dependent on consumer behavior and temporal factors such as season of the year, day of the week or time of the day. For deterministic radial distribution load flow studies load is taken as constant. But, load varies continually with a high degree of uncertainty. So, there is a need to model probable realistic load. Monte-Carlo Simulation is used to model the probable realistic load by generating random values of active and reactive power load from the mean and standard deviation of the load and for solving a Deterministic Radial Load Flow with these values. The probabilistic solution is reconstructed from deterministic data obtained for each simulation. The main contribution of the work is: Finding impact of probable realistic ZIP load modeling on balanced radial distribution load flow. Finding impact of probable realistic ZIP load modeling on unbalanced radial distribution load flow. Compare the voltage profile and losses with probable realistic ZIP load modeling for balanced and unbalanced radial distribution load flow.

  13. Centralized Networks to Generate Human Body Motions.

    Science.gov (United States)

    Vakulenko, Sergei; Radulescu, Ovidiu; Morozov, Ivan; Weber, Andres

    2017-12-14

    We consider continuous-time recurrent neural networks as dynamical models for the simulation of human body motions. These networks consist of a few centers and many satellites connected to them. The centers evolve in time as periodical oscillators with different frequencies. The center states define the satellite neurons' states by a radial basis function (RBF) network. To simulate different motions, we adjust the parameters of the RBF networks. Our network includes a switching module that allows for turning from one motion to another. Simulations show that this model allows us to simulate complicated motions consisting of many different dynamical primitives. We also use the model for learning human body motion from markers' trajectories. We find that center frequencies can be learned from a small number of markers and can be transferred to other markers, such that our technique seems to be capable of correcting for missing information resulting from sparse control marker settings.

  14. RADIAL STABILITY IN STRATIFIED STARS

    International Nuclear Information System (INIS)

    Pereira, Jonas P.; Rueda, Jorge A.

    2015-01-01

    We formulate within a generalized distributional approach the treatment of the stability against radial perturbations for both neutral and charged stratified stars in Newtonian and Einstein's gravity. We obtain from this approach the boundary conditions connecting any two phases within a star and underline its relevance for realistic models of compact stars with phase transitions, owing to the modification of the star's set of eigenmodes with respect to the continuous case

  15. Velocidades radiales en Collinder 121

    Science.gov (United States)

    Arnal, M.; Morrell, N.

    Se han llevado a cabo observaciones espectroscópicas de unas treinta estrellas que son posibles miembros del cúmulo abierto Collinder 121. Las mismas fueron realizadas con el telescopio de 2.15m del Complejo Astronómico El Leoncito (CASLEO). El análisis de las velocidades radiales derivadas del material obtenido, confirma la realidad de Collinder 121, al menos desde el punto de vista cinemático. La velocidad radial baricentral (LSR) del cúmulo es de +17 ± 3 km.s-1. Esta velocidad coincide, dentro de los errores, con la velocidad radial (LSR) de la nebulosa anillo S308, la cual es de ~20 ± 10 km.s-1. Como S308 se encuentra físicamente asociada a la estrella Wolf-Rayet HD~50896, es muy probable que esta última sea un miembro de Collinder 121. Desde un punto de vista cinemático, la supergigante roja HD~50877 (K3Iab) también pertenecería a Collinder 121. Basándonos en la pertenencia de HD~50896 a Collinder 121, y en la interacción encontrada entre el viento de esta estrella y el medio interestelar circundante a la misma, se estima para este cúmulo una distancia del orden de 1 kpc.

  16. A Concept of Operations for the Use of Emergent Open Internet Technologies as the Basis for a Network-Centric Environment

    National Research Council Canada - National Science Library

    O'Sullivan, Joshua D

    2006-01-01

    .... With the dawn of the Information Age a similar revolution has begun, with the realization of the science of networks and their effects on complex systems, such as command and control and sharing...

  17. Study of co-authorship in the nets and the interdisciplinarity in the scientific production on the basis of social network analysis methods: evaluation of the posgraduation program in information science - PPGCI / UFMG

    Directory of Open Access Journals (Sweden)

    Antonio Braz de Oliveira e Silva

    2006-07-01

    Full Text Available This paper discusses the Social Network Analysis (SNA as a method to be broadly applied in researches in the Information Scienc (IS field. This science is, normally, presented as an interdisciplinary filed, but the reseaches lines conducted in Brazil have differents relationship with other disciplines, and doing so, dis-similars interdisciplinaries characteristics. The analysis of the co-authorship network of the professors of the PPGCI/UFMG emphasizes both, the strenght of the methodology and the characteristics of the colaboration in the IS. The article gives an overview of the theoretical basis of the SNA, and presents studies about subjects related to the Information Science field that are done applying SNA, mainly the coauthorship network analysis. Finally, the methodological approach of this research and the main results are presented.

  18. Neural network approach for the calculation of potential coefficients in quantum mechanics

    Science.gov (United States)

    Ossandón, Sebastián; Reyes, Camilo; Cumsille, Patricio; Reyes, Carlos M.

    2017-05-01

    A numerical method based on artificial neural networks is used to solve the inverse Schrödinger equation for a multi-parameter class of potentials. First, the finite element method was used to solve repeatedly the direct problem for different parametrizations of the chosen potential function. Then, using the attainable eigenvalues as a training set of the direct radial basis neural network a map of new eigenvalues was obtained. This relationship was later inverted and refined by training an inverse radial basis neural network, allowing the calculation of the unknown parameters and therefore estimating the potential function. Three numerical examples are presented in order to prove the effectiveness of the method. The results show that the method proposed has the advantage to use less computational resources without a significant accuracy loss.

  19. Exceptional circles of radial potentials

    International Nuclear Information System (INIS)

    Music, M; Perry, P; Siltanen, S

    2013-01-01

    A nonlinear scattering transform is studied for the two-dimensional Schrödinger equation at zero energy with a radial potential. Explicit examples are presented, both theoretically and computationally, of potentials with nontrivial singularities in the scattering transform. The singularities arise from non-uniqueness of the complex geometric optics solutions that define the scattering transform. The values of the complex spectral parameter at which the singularities appear are called exceptional points. The singularity formation is closely related to the fact that potentials of conductivity type are ‘critical’ in the sense of Murata. (paper)

  20. The Neural Basis of Recollection Rejection: Increases in Hippocampal-Prefrontal Connectivity in the Absence of a Shared Recall-to-Reject and Target Recollection Network.

    Science.gov (United States)

    Bowman, Caitlin R; Dennis, Nancy A

    2016-08-01

    Recollection rejection or "recall-to-reject" is a mechanism that has been posited to help maintain accurate memory by preventing the occurrence of false memories. Recollection rejection occurs when the presentation of a new item during recognition triggers recall of an associated target, a mismatch in features between the new and old items is registered, and the lure is correctly rejected. Critically, this characterization of recollection rejection involves a recall signal that is conceptually similar to recollection as elicited by a target. However, previous neuroimaging studies have not evaluated the extent to which recollection rejection and target recollection rely on a common neural signal but have instead focused on recollection rejection as a postretrieval monitoring process. This study utilized a false memory paradigm in conjunction with an adapted remember-know-new response paradigm that separated "new" responses based on recollection rejection from those that were based on a lack of familiarity with the item. This procedure allowed for parallel recollection rejection and target recollection contrasts to be computed. Results revealed that, contrary to predictions from theoretical and behavioral literature, there was virtually no evidence of a common retrieval mechanism supporting recollection rejection and target recollection. Instead of the typical target recollection network, recollection rejection recruited a network of lateral prefrontal and bilateral parietal regions that is consistent with the retrieval monitoring network identified in previous neuroimaging studies of recollection rejection. However, a functional connectivity analysis revealed a component of the frontoparietal rejection network that showed increased coupling with the right hippocampus during recollection rejection responses. As such, we demonstrate a possible link between PFC monitoring network and basic retrieval mechanisms within the hippocampus that was not revealed with

  1. Moment methods with effective nuclear Hamiltonians; calculations of radial moments

    International Nuclear Information System (INIS)

    Belehrad, R.H.

    1981-02-01

    A truncated orthogonal polynomial expansion is used to evaluate the expectation value of the radial moments of the one-body density of nuclei. The expansion contains the configuration moments, , , and 2 >, where R/sup (k)/ is the operator for the k-th power of the radial coordinate r, and H is the effective nuclear Hamiltonian which is the sum of the relative kinetic energy operator and the Bruckner G matrix. Configuration moments are calculated using trace reduction formulae where the proton and neutron orbitals are treated separately in order to find expectation values of good total isospin. The operator averages are taken over many-body shell model states in the harmonic oscillator basis where all particles are active and single-particle orbitals through six major shells are included. The radial moment expectation values are calculated for the nuclei 16 O, 40 Ca, and 58 Ni and find that is usually the largest term in the expansion giving a large model space dependence to the results. For each of the 3 nuclei, a model space is found which gives the desired rms radius and then we find that the other 5 lowest moments compare favorably with other theoretical predictions. Finally, we use a method of Gordon (5) to employ the lowest 6 radial moment expectation values in the calculation of elastic electron scattering from these nuclei. For low to moderate momentum transfer, the results compare favorably with the experimental data

  2. Regional modeling approach for analyzing harmonic stability in radial power electronics based power system

    DEFF Research Database (Denmark)

    Yoon, Changwoo; Bai, Haofeng; Wang, Xiongfei

    2015-01-01

    Stability analysis of distributed power generation system becomes complex when there are many numbers of grid inverters in the system. In order to analyze system stability, the overall network impedance will be lumped and needs to be analyzed one by one. However, using a unified bulky transfer-fu...... and then it is expanded for generalizing its concept to an overall radial structured network....

  3. Modelling and prediction for chaotic fir laser attractor using rational function neural network.

    Science.gov (United States)

    Cho, S

    2001-02-01

    Many real-world systems such as irregular ECG signal, volatility of currency exchange rate and heated fluid reaction exhibit highly complex nonlinear characteristic known as chaos. These chaotic systems cannot be retreated satisfactorily using linear system theory due to its high dimensionality and irregularity. This research focuses on prediction and modelling of chaotic FIR (Far InfraRed) laser system for which the underlying equations are not given. This paper proposed a method for prediction and modelling a chaotic FIR laser time series using rational function neural network. Three network architectures, TDNN (Time Delayed Neural Network), RBF (radial basis function) network and the RF (rational function) network, are also presented. Comparisons between these networks performance show the improvements introduced by the RF network in terms of a decrement in network complexity and better ability of predictability.

  4. Radial smoothing and closed orbit

    International Nuclear Information System (INIS)

    Burnod, L.; Cornacchia, M.; Wilson, E.

    1983-11-01

    A complete simulation leading to a description of one of the error curves must involve four phases: (1) random drawing of the six set-up points within a normal population having a standard deviation of 1.3 mm; (b) random drawing of the six vertices of the curve in the sextant mode within a normal population having a standard deviation of 1.2 mm. These vertices are to be set with respect to the axis of the error lunes, while this axis has as its origins the positions defined by the preceding drawing; (c) mathematical definition of six parabolic curves and their junctions. These latter may be curves with very slight curvatures, or segments of a straight line passing through the set-up point and having lengths no longer than one LSS. Thus one gets a mean curve for the absolute errors; (d) plotting of the actually observed radial positions with respect to the mean curve (results of smoothing)

  5. Waves on radial film flows

    Science.gov (United States)

    Cholemari, Murali R.; Arakeri, Jaywant H.

    2005-08-01

    We study the stability of surface waves on the radial film flow created by a vertical cylindrical water jet striking a horizontal plate. In such flows, surface waves have been found to be unstable and can cause transition to turbulence. This surface-wave-induced transition is different from the well-known Tollmien-Schlichting wave-induced transition. The present study aims at understanding the instability and the transition process. We do a temporal stability analysis by assuming the flow to be locally two-dimensional but including spatial variations to first order in the basic flow. The waves are found to be dispersive, mostly unstable, and faster than the mean flow. Spatial variation is the major destabilizing factor. Experiments are done to test the results of the linear stability analysis and to document the wave breakup and transition. Comparison between theory and experiments is fairly good and indicates the adequacy of the model.

  6. Radial flow gas dynamic laser

    International Nuclear Information System (INIS)

    Damm, F.C.

    1975-01-01

    The unique gas dynamic laser provides outward radial supersonic flow from a toroidal shaped stacked array of a plurality of nozzles, through a diffuser having ring shaped and/or linear shaped vanes, and through a cavity which is cylindrical and concentric with the stacked array, with the resultant laser beam passing through the housing parallel to the central axis of the diffuser which is coincident with the axis of the gas dynamic laser. Therefore, greater beam extraction flexibility is attainable, because of fewer flow shock disturbances, as compared to the conventional unidirectional flow gas dynamic laser in which unidirectional supersonic flow sweeps through a rectangular cavity and is exhausted through a two-dimensional diffuser. (auth)

  7. Ulnar nerve entrapment complicating radial head excision

    Directory of Open Access Journals (Sweden)

    Kevin Parfait Bienvenu Bouhelo-Pam

    Full Text Available Introduction: Several mechanisms are involved in ischemia or mechanical compression of ulnar nerve at the elbow. Presentation of case: We hereby present the case of a road accident victim, who received a radial head excision for an isolated fracture of the radial head and complicated by onset of cubital tunnel syndrome. This outcome could be the consequence of an iatrogenic valgus of the elbow due to excision of the radial head. Hitherto the surgical treatment of choice it is gradually been abandoned due to development of radial head implant arthroplasty. However, this management option is still being performed in some rural centers with low resources. Discussion: The radial head plays an important role in the stability of the elbow and his iatrogenic deformity can be complicated by cubital tunnel syndrome. Conclusion: An ulnar nerve release was performed with favorable outcome. Keywords: Cubital tunnel syndrome, Peripheral nerve palsy, Radial head excision, Elbow valgus

  8. Stirling Engine With Radial Flow Heat Exchangers

    Science.gov (United States)

    Vitale, N.; Yarr, George

    1993-01-01

    Conflict between thermodynamical and structural requirements resolved. In Stirling engine of new cylindrical configuration, regenerator and acceptor and rejector heat exchangers channel flow of working gas in radial direction. Isotherms in regenerator ideally concentric cylinders, and gradient of temperature across regenerator radial rather than axial. Acceptor and rejector heat exchangers located radially inward and outward of regenerator, respectively. Enables substantial increase in power of engine without corresponding increase in diameter of pressure vessel.

  9. Mixtures of truncated basis functions

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre; Rumí, Rafael

    2012-01-01

    In this paper we propose a framework, called mixtures of truncated basis functions (MoTBFs), for representing general hybrid Bayesian networks. The proposed framework generalizes both the mixture of truncated exponentials (MTEs) framework and the mixture of polynomials (MoPs) framework. Similar t...

  10. A novel structure of permanent-magnet-biased radial hybrid magnetic bearing

    International Nuclear Information System (INIS)

    Sun Jinji; Fang Jiancheng

    2011-01-01

    The paper proposes a novel structure for a permanent-magnet-biased radial hybrid magnetic bearing. Based on the air gap between the rotor and stator of traditional radial hybrid magnetic bearings, a subsidiary air gap is first constructed between the permanent magnets and the inner magnetic parts. Radial magnetic bearing makes X and Y magnetic fields independent of each other with separate stator poles, and the subsidiary air gap makes control flux to a close loop. As a result, magnetic field coupling of the X and Y channels is decreased significantly by the radial hybrid magnetic bearing and makes it easier to design control systems. Then an external rotor structure is designed into the radial hybrid magnetic bearing. The working principle of the radial hybrid magnetic bearing and its mathematical model is discussed. Finally, a non-linear magnetic network method is proposed to analyze the radial hybrid magnetic bearing. Simulation results indicate that magnetic fields in the two channels of the proposed radial hybrid magnetic bearing decouple well from each other.

  11. A novel structure of permanent-magnet-biased radial hybrid magnetic bearing

    Energy Technology Data Exchange (ETDEWEB)

    Sun Jinji, E-mail: sunjinji@aspe.buaa.edu.c [Key Laboratory of Fundamental Science for National Defense, Novel Inertial Instrument and Navigation System Technology, School of Instrument Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, 100191 (China); Fang Jiancheng [Key Laboratory of Fundamental Science for National Defense, Novel Inertial Instrument and Navigation System Technology, School of Instrument Science and Opto-electronics Engineering, Beijing University of Aeronautics and Astronautics, 100191 (China)

    2011-01-15

    The paper proposes a novel structure for a permanent-magnet-biased radial hybrid magnetic bearing. Based on the air gap between the rotor and stator of traditional radial hybrid magnetic bearings, a subsidiary air gap is first constructed between the permanent magnets and the inner magnetic parts. Radial magnetic bearing makes X and Y magnetic fields independent of each other with separate stator poles, and the subsidiary air gap makes control flux to a close loop. As a result, magnetic field coupling of the X and Y channels is decreased significantly by the radial hybrid magnetic bearing and makes it easier to design control systems. Then an external rotor structure is designed into the radial hybrid magnetic bearing. The working principle of the radial hybrid magnetic bearing and its mathematical model is discussed. Finally, a non-linear magnetic network method is proposed to analyze the radial hybrid magnetic bearing. Simulation results indicate that magnetic fields in the two channels of the proposed radial hybrid magnetic bearing decouple well from each other.

  12. Molecular basis of human Usher syndrome: deciphering the meshes of the Usher protein network provides insights into the pathomechanisms of the Usher disease.

    Science.gov (United States)

    Reiners, Jan; Nagel-Wolfrum, Kerstin; Jürgens, Karin; Märker, Tina; Wolfrum, Uwe

    2006-07-01

    Usher syndrome (USH) is the most frequent cause of combined deaf-blindness in man. It is clinically and genetically heterogeneous and at least 12 chromosomal loci are assigned to three clinical USH types, namely USH1A-G, USH2A-C, USH3A (Davenport, S.L.H., Omenn, G.S., 1977. The heterogeneity of Usher syndrome. Vth Int. Conf. Birth Defects, Montreal; Petit, C., 2001. Usher syndrome: from genetics to pathogenesis. Annu. Rev. Genomics Hum. Genet. 2, 271-297). Mutations in USH type 1 genes cause the most severe form of USH. In USH1 patients, congenital deafness is combined with a pre-pubertal onset of retinitis pigmentosa (RP) and severe vestibular dysfunctions. Those with USH2 have moderate to severe congenital hearing loss, non-vestibular dysfunction and a later onset of RP. USH3 is characterized by variable RP and vestibular dysfunction combined with progressive hearing loss. The gene products of eight identified USH genes belong to different protein classes and families. There are five known USH1 molecules: the molecular motor myosin VIIa (USH1B); the two cell-cell adhesion cadherin proteins, cadherin 23 (USH1D) and protocadherin 15, (USH1F) and the scaffold proteins, harmonin (USH1C) and SANS (USH1G). In addition, two USH2 genes and one USH3A gene have been identified. The two USH2 genes code for the transmembrane protein USH2A, also termed USH2A ("usherin") and the G-protein-coupled 7-transmembrane receptor VLGR1b (USH2C), respectively, whereas the USH3A gene encodes clarin-1, a member of the clarin family which exhibits 4-transmembrane domains. Molecular analysis of USH1 protein function revealed that all five USH1 proteins are integrated into a protein network via binding to PDZ domains in the USH1C protein harmonin. Furthermore, this scaffold function of harmonin is supported by the USH1G protein SANS. Recently, we have shown that the USH2 proteins USH2A and VLGR1b as well as the candidate for USH2B, the sodium bicarbonate co-transporter NBC3, are also

  13. Design and development of self-powered sensors on wireless sensor network for standalone plant critical data management during SBO and beyond design basis events

    International Nuclear Information System (INIS)

    Aparna, J.; Dulera, I.V.; Rama Rao, A.; Vijayan, P.K.

    2015-01-01

    Advanced reactors are designed with an aim of maximum safety, optimized fuel utilization and effective system design. Safety aspects in reactor designs are being viewed for all possible vulnerabilities, and as a result, robust self-regulating passive safety features have been favored in Gen IV and advanced reactor designs. In addition to passive systems, the accidents scenarios at Fukushima indicate the dire need of reliable and stand-alone self-powered sensors, for monitoring plant critical parameters for effective damage control actions. There is a strong need for plant critical data management and situation awareness during the unavailability of all conventional power sources in a nuclear power plant, during extended station blackout (SBO) conditions. These self-powered sensors would assist the operators in managing events like SBO and help in containing any Beyond Design Basis Events (BDBE) conditions, well away from the public domain

  14. Day-Ahead Natural Gas Demand Forecasting Using Optimized ABC-Based Neural Network with Sliding Window Technique: The Case Study of Regional Basis in Turkey

    Directory of Open Access Journals (Sweden)

    Mustafa Akpinar

    2017-06-01

    Full Text Available The increase of energy consumption in the world is reflected in the consumption of natural gas. However, this increment requires additional investment. This effect leads imbalances in terms of demand forecasting, such as applying penalties in the case of error rates occurring beyond the acceptable limits. As the forecasting errors increase, penalties increase exponentially. Therefore, the optimal use of natural gas as a scarce resource is important. There are various demand forecast ranges for natural gas and the most difficult range among these demands is the day-ahead forecasting, since it is hard to implement and makes predictions with low error rates. The objective of this study is stabilizing gas tractions on day-ahead demand forecasting using low-consuming subscriber data for minimizing error using univariate artificial bee colony-based artificial neural networks (ANN-ABC. For this purpose, households and low-consuming commercial users’ four-year consumption data between the years of 2011–2014 are gathered in daily periods. Previous consumption values are used to forecast day-ahead consumption values with sliding window technique and other independent variables are not taken into account. Dataset is divided into two parts. First, three-year daily consumption values are used with a seven day window for training the networks, while the last year is used for the day-ahead demand forecasting. Results show that ANN-ABC is a strong, stable, and effective method with a low error rate of 14.9 mean absolute percentage error (MAPE for training utilizing MAPE with a univariate sliding window technique.

  15. Radial head button holing: a cause of irreducible anterior radial head dislocation

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Su-Mi; Chai, Jee Won; You, Ja Yeon; Park, Jina [Seoul National University Seoul Metropolitan Government Boramae Medical Center, Department of Radiology, Seoul (Korea, Republic of); Bae, Kee Jeong [Seoul National University Seoul Metropolitan Government Boramae Medical Center, Department of Orthopedic Surgery, Seoul (Korea, Republic of)

    2016-10-15

    ''Buttonholing'' of the radial head through the anterior joint capsule is a known cause of irreducible anterior radial head dislocation associated with Monteggia injuries in pediatric patients. To the best of our knowledge, no report has described an injury consisting of buttonholing of the radial head through the annular ligament and a simultaneous radial head fracture in an adolescent. In the present case, the radiographic findings were a radial head fracture with anterior dislocation and lack of the anterior fat pad sign. Magnetic resonance imaging (MRI) clearly demonstrated anterior dislocation of the fractured radial head through the torn annular ligament. The anterior joint capsule and proximal portion of the annular ligament were interposed between the radial head and capitellum, preventing closed reduction of the radial head. Familiarity with this condition and imaging findings will aid clinicians to make a proper diagnosis and fast decision to perform an open reduction. (orig.)

  16. Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

    Science.gov (United States)

    Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.

    2007-01-01

    To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

  17. Fundamentals of computational intelligence neural networks, fuzzy systems, and evolutionary computation

    CERN Document Server

    Keller, James M; Fogel, David B

    2016-01-01

    This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basi function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzz...

  18. Photoelectric Radial Velocities, Paper XIX Additional Spectroscopic ...

    Indian Academy of Sciences (India)

    ian velocity curve that does justice to the measurements, but it cannot be expected to have much predictive power. Key words. Stars: late-type—stars: radial velocities—spectroscopic binaries—orbits. 0. Preamble. The 'Redman K stars' are a lot of seventh-magnitude K stars whose radial velocities were first observed by ...

  19. Radial velocities of RR Lyrae stars

    International Nuclear Information System (INIS)

    Hawley, S.L.; Barnes, T.G. III

    1985-01-01

    283 spectra of 57 RR Lyrae stars have been obtained using the 2.1-m telescope at McDonald Observatory. Radial velocities were determined using a software cross-correlation technique. New mean radial velocities were determined for 46 of the stars. 11 references

  20. Concepts of radial and angular kinetic energies

    DEFF Research Database (Denmark)

    Dahl, Jens Peder; Schleich, W.P.

    2002-01-01

    We consider a general central-field system in D dimensions and show that the division of the kinetic energy into radial and angular parts proceeds differently in the wave-function picture and the Weyl-Wigner phase-space picture, Thus, the radial and angular kinetic energies are different quantities...

  1. Effect of changing of the parameters of the cable network of monitoring systems of high-rise buildings on the basis of string converters on their operability

    Science.gov (United States)

    Gusev, Nikolay; Svatovskaya, Larisa; Kucherenko, Alexandr

    2018-03-01

    The article is devoted to the problem of improving the reliability of monitoring systems for the technical conditions of high-rise buildings. The improvement is based on string sensors with an impulsed excitation method ensuring the maximum signal-to-noise ratio at their output. The influence of the parameters of the monitoring system on the shape of the excitation impulses of the string, and, consequently, on the amplitude of the string vibration of the string converter is also considered in the article. It has been experimentally proved that the parameters of the excitation impulses of the string converters. The article presents the results of the experiments showing the effect of the fronts duration of the excitation impulses on the amplitude of the oscillations of the strings. The influence of the fronts duration of the excitation impulse with the frontal lengths up to 0.5 ms is studied at the excitation impulse duration not exceeding 0.5 times the duration of natural oscillation periods of the string. The experimental data are compared with the theoretical ones and hypotheses explaining their difference are advanced. The article suggests some methods of reducing the influence of the cable-switching equipment system parameters on the amplitude of string oscillations. The possibilities of improving the reliability of the systems developed on the basis of string sensors with an impulsed excitation method and used for monitoring the technical conditions of the high-rise buildings are proposed.

  2. Science Forum of the renewables 2004: Networked knowledge for renewable energies - Research, development and education - Basis for wide-spread deployment of renewable energies. Proceedings

    Energy Technology Data Exchange (ETDEWEB)

    Wienges, S.; Stadermann, G.; Szczepanski, P. (eds.)

    2004-09-01

    Energy was one of five foci of the World Summit on Sustainable Development (WSSD) in Johannesburg in 2002. While the access to modern energy is crucial for poverty reduction in particular and development in general, the way of producing and providing that energy is as crucial for environmental and social sustainability. Hence, the renewables 2004 - the International Conference for Renewable Energies was the logical consequence and next step on the way forward. It was held from 1st June to 4th June 2004 in Bonn, Germany, and turned out to be a forum for stakeholders from all sectors: Governments as well as parliamentarians, the private sector, NGOs, International Organisations, and International Financial Institutions. On 1st June this multisectoral approach to the dissemination of renewables was completed by the Science Forum - Education, Research, and Training: Basis for Wide-spread Deployment of Renewable Energies. This one-day side-event brought together scientists and practitioners from allover the world, discussing the future requirements of research and development as well as needs and potentials of education and training for renewables in developing and industrialized countries. (orig.)

  3. Radial lip seals, thermal aspects

    NARCIS (Netherlands)

    Stakenborg, M.J.L.; van Ostaijen, R.A.J.; Dowson, D.

    1989-01-01

    In this paper the influence of temperature on tne seal-snarc contact is studied, using coupled temperature-stress FEH analysis. A thermal network model is used to calculate the seal-shaft contact temperature for steady-state and transient conditions. Contact temperatures were measured under the seal

  4. PERFORMANCE COMPARISON FOR INTRUSION DETECTION SYSTEM USING NEURAL NETWORK WITH KDD DATASET

    Directory of Open Access Journals (Sweden)

    S. Devaraju

    2014-04-01

    Full Text Available Intrusion Detection Systems are challenging task for finding the user as normal user or attack user in any organizational information systems or IT Industry. The Intrusion Detection System is an effective method to deal with the kinds of problem in networks. Different classifiers are used to detect the different kinds of attacks in networks. In this paper, the performance of intrusion detection is compared with various neural network classifiers. In the proposed research the four types of classifiers used are Feed Forward Neural Network (FFNN, Generalized Regression Neural Network (GRNN, Probabilistic Neural Network (PNN and Radial Basis Neural Network (RBNN. The performance of the full featured KDD Cup 1999 dataset is compared with that of the reduced featured KDD Cup 1999 dataset. The MATLAB software is used to train and test the dataset and the efficiency and False Alarm Rate is measured. It is proved that the reduced dataset is performing better than the full featured dataset.

  5. Ultraviolet and visible radiation at Barrow, Alaska: Climatology and influencing factors on the basis of version 2 National Science Foundation network data

    Science.gov (United States)

    Bernhard, Germar; Booth, Charles R.; Ehramjian, James C.; Stone, Robert; Dutton, Ellsworth G.

    2007-05-01

    Spectral ultraviolet (UV) and visible irradiance has been measured near Barrow, Alaska (71°N, 157°W), between 1991 and 2005 with a SUV-100 spectroradiometer. The instrument is part of the U.S. National Science Foundation's UV Monitoring Network. Here we present results based on the recently produced "version 2" data release, which supersedes published "version 0" data. Cosine error and wavelength-shift corrections applied to the new version increased biologically effective UV dose rates by 0-10%. Corrected clear-sky measurements of different years are typically consistent to within ±3%. Measurements were complemented with radiative transfer model calculations to retrieve total ozone and surface albedo from measured spectra and for the separation of the different factors influencing UV and visible radiation. A climatology of UV and visible radiation was established, focusing on annual cycles, trends, and the effect of clouds. During several episodes in spring of abnormally low total ozone, the daily UV dose at 305 nm exceeded the climatological mean by up to a factor of 2.6. Typical noontime UV Indices during summer vary between 2 and 4; the highest UV Index measured was 5.0 and occurred when surface albedo was unusually high. Radiation levels in the UV-A and visible exhibit a strong spring-autumn asymmetry. Irradiance at 345 nm peaks on approximately 20 May, 1 month before the solstice. This asymmetry is caused by increased cloudiness in autumn and high albedo in spring, when the snow covered surface enhances downwelling UV irradiance by up to 57%. Clouds reduce UV radiation at 345 nm on average by 4% in March and by more than 40% in August. Aerosols reduce UV by typically 5%, but larger reductions were observed during Arctic haze events. Stratospheric aerosols from the Pinatubo eruption in 1991 enhanced spectral irradiance at 305 nm for large solar zenith angles. The year-to-year variations of spectral irradiance at 305 nm and of the UV Index are mostly caused

  6. Application of RBF neural network improved by peak density function in intelligent color matching of wood dyeing

    International Nuclear Information System (INIS)

    Guan, Xuemei; Zhu, Yuren; Song, Wenlong

    2016-01-01

    According to the characteristics of wood dyeing, we propose a predictive model of pigment formula for wood dyeing based on Radial Basis Function (RBF) neural network. In practical application, however, it is found that the number of neurons in the hidden layer of RBF neural network is difficult to determine. In general, we need to test several times according to experience and prior knowledge, which is lack of a strict design procedure on theoretical basis. And we also don’t know whether the RBF neural network is convergent. This paper proposes a peak density function to determine the number of neurons in the hidden layer. In contrast to existing approaches, the centers and the widths of the radial basis function are initialized by extracting the features of samples. So the uncertainty caused by random number when initializing the training parameters and the topology of RBF neural network is eliminated. The average relative error of the original RBF neural network is 1.55% in 158 epochs. However, the average relative error of the RBF neural network which is improved by peak density function is only 0.62% in 50 epochs. Therefore, the convergence rate and approximation precision of the RBF neural network are improved significantly.

  7. Radial electric fields for improved tokamak performance

    International Nuclear Information System (INIS)

    Downum, W.B.

    1981-01-01

    The influence of externally-imposed radial electric fields on the fusion energy output, energy multiplication, and alpha-particle ash build-up in a TFTR-sized, fusing tokamak plasma is explored. In an idealized tokamak plasma, an externally-imposed radial electric field leads to plasma rotation, but no charge current flows across the magnetic fields. However, a realistically-low neutral density profile generates a non-zero cross-field conductivity and the species dependence of this conductivity allows the electric field to selectively alter radial particle transport

  8. Radial MR images of the knee

    International Nuclear Information System (INIS)

    Hewes, R.C.; Miller, T.R.

    1988-01-01

    To profile optimally each portion of the meniscus, the authors use the multiangle, multisection feature of a General Electric SIGNA 1.5-T imager to produce radial images centered on each meniscus. A total of 12-15 sections are imaged at 10 0 -15 0 intervals of each meniscus, yielding perpendicular images of the entire meniscus, comparable with the arthrographic tangential views. The authors review their technique and demonstrate correlation cases between the radial gradient recalled acquisition in a steady state sequences, sagittal and coronal MR images, and arthrograms. Radial images should be a routine part of knee MR imaging

  9. Radial pattern of nuclear decay processes

    International Nuclear Information System (INIS)

    Iskra, W.; Mueller, M.; Rotter, I.; Technische Univ. Dresden

    1994-05-01

    At high level density of nuclear states, a separation of different time scales is observed (trapping effect). We calculate the radial profile of partial widths in the framework of the continuum shell model for some 1 - resonances with 2p-2h nuclear structure in 16 O as a function of the coupling strength to the continuum. A correlation between the lifetime of a nuclear state and the radial profile of the corresponding decay process is observed. We conclude from our numerical results that the trapping effect creates structures in space and time characterized by a small radial extension and a short lifetime. (orig.)

  10. Impeller radial force evolution in a large double-suction centrifugal pump during startup at the shut-off condition

    Energy Technology Data Exchange (ETDEWEB)

    Zou, Zhichao [College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083 (China); Wang, Fujun, E-mail: wangfj@cau.edu.cn [College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083 (China); Beijing Engineering Research Center of Safety and Energy Saving Technology for Water Supply Network System, China Agricultural University, Beijing 100083 (China); Yao, Zhifeng [College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083 (China); Beijing Engineering Research Center of Safety and Energy Saving Technology for Water Supply Network System, China Agricultural University, Beijing 100083 (China); Tao, Ran [College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083 (China); Xiao, Ruofu [College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083 (China); Beijing Engineering Research Center of Safety and Energy Saving Technology for Water Supply Network System, China Agricultural University, Beijing 100083 (China); Li, Huaicheng [Shanghai Liancheng (Group) Co., Ltd., Shanghai 201812 (China)

    2016-12-15

    Highlights: • Conclude the characteristics of transient radial force in the startup process for a large double-suction centrifugal pump. • The overall direction of the radial force during startup process is also confirmed. • A formula used to calculate the transient radial force during startup process is proposed. • A relationship between radial force variation and axial vortex development in blade channel during the startup process is established. The mechanism of the radial force evolution is revealed. - Abstract: Double-suction centrifugal pumps play an important role in the main feedwater systems of nuclear power plant. The impeller radial force in a centrifugal pump varies dramatically during startup at the shut-off condition. In this study, the startup process of a large double-suction centrifugal pump is investigated using CFD. During testing, the impeller speed is accelerated from zero to its rated speed in 1.0 s (marked as t{sub 0}) and is then maintained at the rated speed. The results show that the radial force increase lags behind the impeller speed increase. At 0–0.4t{sub 0}, the radial force is small (approaching zero). At 0.4–1.4t{sub 0}, the radial force increases rapidly. After 1.4t{sub 0}, the average radial force stabilizes and reaches its maximum value of 55,619 N. The observed maximum radial force value during startup is approximately nine times as high as the radial force under rated condition. During startup, the overall radial force direction is proximate to the radial line located 25° from the volute tongue along circumferential direction. A transient radial force formula is proposed to evaluate the changes in radial force during startup. The streamline distribution in impeller passages and the impeller outlet pressure profile varying over time are produced. The relationship between radial force evolution and the varying axial-to-spiral vortex structure is analyzed. The radial force change mechanism is revealed. This research

  11. Impeller radial force evolution in a large double-suction centrifugal pump during startup at the shut-off condition

    International Nuclear Information System (INIS)

    Zou, Zhichao; Wang, Fujun; Yao, Zhifeng; Tao, Ran; Xiao, Ruofu; Li, Huaicheng

    2016-01-01

    Highlights: • Conclude the characteristics of transient radial force in the startup process for a large double-suction centrifugal pump. • The overall direction of the radial force during startup process is also confirmed. • A formula used to calculate the transient radial force during startup process is proposed. • A relationship between radial force variation and axial vortex development in blade channel during the startup process is established. The mechanism of the radial force evolution is revealed. - Abstract: Double-suction centrifugal pumps play an important role in the main feedwater systems of nuclear power plant. The impeller radial force in a centrifugal pump varies dramatically during startup at the shut-off condition. In this study, the startup process of a large double-suction centrifugal pump is investigated using CFD. During testing, the impeller speed is accelerated from zero to its rated speed in 1.0 s (marked as t_0) and is then maintained at the rated speed. The results show that the radial force increase lags behind the impeller speed increase. At 0–0.4t_0, the radial force is small (approaching zero). At 0.4–1.4t_0, the radial force increases rapidly. After 1.4t_0, the average radial force stabilizes and reaches its maximum value of 55,619 N. The observed maximum radial force value during startup is approximately nine times as high as the radial force under rated condition. During startup, the overall radial force direction is proximate to the radial line located 25° from the volute tongue along circumferential direction. A transient radial force formula is proposed to evaluate the changes in radial force during startup. The streamline distribution in impeller passages and the impeller outlet pressure profile varying over time are produced. The relationship between radial force evolution and the varying axial-to-spiral vortex structure is analyzed. The radial force change mechanism is revealed. This research provides a scientific

  12. Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China

    Directory of Open Access Journals (Sweden)

    C. W. Dawson

    2002-01-01

    Full Text Available While engineers have been quantifying rainfall-runoff processes since the mid-19th century, it is only in the last decade that artificial neural network models have been applied to the same task. This paper evaluates two neural networks in this context: the popular multilayer perceptron (MLP, and the radial basis function network (RBF. Using six-hourly rainfall-runoff data for the River Yangtze at Yichang (upstream of the Three Gorges Dam for the period 1991 to 1993, it is shown that both neural network types can simulate river flows beyond the range of the training set. In addition, an evaluation of alternative RBF transfer functions demonstrates that the popular Gaussian function, often used in RBF networks, is not necessarily the ‘best’ function to use for river flow forecasting. Comparisons are also made between these neural networks and conventional statistical techniques; stepwise multiple linear regression, auto regressive moving average models and a zero order forecasting approach. Keywords: Artificial neural network, multilayer perception, radial basis function, flood forecasting

  13. Reliability analysis of C-130 turboprop engine components using artificial neural network

    Science.gov (United States)

    Qattan, Nizar A.

    In this study, we predict the failure rate of Lockheed C-130 Engine Turbine. More than thirty years of local operational field data were used for failure rate prediction and validation. The Weibull regression model and the Artificial Neural Network model including (feed-forward back-propagation, radial basis neural network, and multilayer perceptron neural network model); will be utilized to perform this study. For this purpose, the thesis will be divided into five major parts. First part deals with Weibull regression model to predict the turbine general failure rate, and the rate of failures that require overhaul maintenance. The second part will cover the Artificial Neural Network (ANN) model utilizing the feed-forward back-propagation algorithm as a learning rule. The MATLAB package will be used in order to build and design a code to simulate the given data, the inputs to the neural network are the independent variables, the output is the general failure rate of the turbine, and the failures which required overhaul maintenance. In the third part we predict the general failure rate of the turbine and the failures which require overhaul maintenance, using radial basis neural network model on MATLAB tool box. In the fourth part we compare the predictions of the feed-forward back-propagation model, with that of Weibull regression model, and radial basis neural network model. The results show that the failure rate predicted by the feed-forward back-propagation artificial neural network model is closer in agreement with radial basis neural network model compared with the actual field-data, than the failure rate predicted by the Weibull model. By the end of the study, we forecast the general failure rate of the Lockheed C-130 Engine Turbine, the failures which required overhaul maintenance and six categorical failures using multilayer perceptron neural network (MLP) model on DTREG commercial software. The results also give an insight into the reliability of the engine

  14. Radial pseudoaneurysm following diagnostic coronary angiography

    Directory of Open Access Journals (Sweden)

    Shankar Laudari

    2015-06-01

    Full Text Available The radial artery access has gained popularity as a method of diagnostic coronary catheterization compared to femoral artery puncture in terms of vascular complications and early ambulation. However, very rare complication like radial artery pseudoaneurysm may occur following cardiac catheterization which may give rise to serious consequences. Here, we report a patient with radial pseudoaneurysm following diagnostic coronary angiography. Adequate and correct methodology of compression of radial artery following puncture for maintaining hemostasis is the key to prevention.DOI: http://dx.doi.org/10.3126/jcmsn.v10i3.12776 Journal of College of Medical Sciences-Nepal, 2014, Vol-10, No-3, 48-50

  15. Radial transport with perturbed magnetic field

    Energy Technology Data Exchange (ETDEWEB)

    Hazeltine, R. D. [Institute for Fusion Studies, University of Texas at Austin, Austin, Texas 78712 (United States)

    2015-05-15

    It is pointed out that the viscosity coefficient describing radial transport of toroidal angular momentum is proportional to the second power of the gyro-radius—like the corresponding coefficients for particle and heat transport—regardless of any geometrical symmetry. The observation is widely appreciated, but worth emphasizing because some literature gives the misleading impression that asymmetry can allow radial moment transport in first-order.

  16. Radial transport with perturbed magnetic field

    International Nuclear Information System (INIS)

    Hazeltine, R. D.

    2015-01-01

    It is pointed out that the viscosity coefficient describing radial transport of toroidal angular momentum is proportional to the second power of the gyro-radius—like the corresponding coefficients for particle and heat transport—regardless of any geometrical symmetry. The observation is widely appreciated, but worth emphasizing because some literature gives the misleading impression that asymmetry can allow radial moment transport in first-order

  17. Modelling and Forecasting Cruise Tourism Demand to İzmir by Different Artificial Neural Network Architectures

    Directory of Open Access Journals (Sweden)

    Murat Cuhadar

    2014-03-01

    Full Text Available Abstract Cruise ports emerged as an important sector for the economy of Turkey bordered on three sides by water. Forecasting cruise tourism demand ensures better planning, efficient preparation at the destination and it is the basis for elaboration of future plans. In the recent years, new techniques such as; artificial neural networks were employed for developing of the predictive models to estimate tourism demand. In this study, it is aimed to determine the forecasting method that provides the best performance when compared the forecast accuracy of Multi-layer Perceptron (MLP, Radial Basis Function (RBF and Generalized Regression neural network (GRNN to estimate the monthly inbound cruise tourism demand to İzmir via the method giving best results. We used the total number of foreign cruise tourist arrivals as a measure of inbound cruise tourism demand and monthly cruise tourist arrivals to İzmir Cruise Port in the period of January 2005 ‐December 2013 were utilized to appropriate model. Experimental results showed that radial basis function (RBF neural network outperforms multi-layer perceptron (MLP and the generalised regression neural networks (GRNN in terms of forecasting accuracy. By the means of the obtained RBF neural network model, it has been forecasted the monthly inbound cruise tourism demand to İzmir for the year 2014.

  18. Stability of radial and non-radial pulsation modes of massive ZAMS models

    International Nuclear Information System (INIS)

    Odell, A.P.; Pausenwein, A.; Weiss, W.W.; Hajek, A.

    1987-01-01

    The authors have computed non-adiabatic eigenvalues for radial and non-radial pulsation modes of star models between 80 and 120 M solar with composition of chi=0.70 and Z=0.02. The radial fundamental mode is unstable in models with mass greater than 95 M solar , but the first overtone mode is always stable. The non-radial modes are all stable for all models, but the iota=2 f-mode is the closest to being driven. The non-radial modes are progressively more stable with higher iota and with higher n (for both rho- and g-modes). Thus, their results indicate that radial pulsation limits the upper mass of a star

  19. 21 CFR 866.4800 - Radial immunodiffusion plate.

    Science.gov (United States)

    2010-04-01

    ...) MEDICAL DEVICES IMMUNOLOGY AND MICROBIOLOGY DEVICES Immunology Laboratory Equipment and Reagents § 866.4800 Radial immunodiffusion plate. (a) Identification. A radial immunodiffusion plate for clinical use...

  20. Neural Network Predictive Control for Vanadium Redox Flow Battery

    Directory of Open Access Journals (Sweden)

    Hai-Feng Shen

    2013-01-01

    Full Text Available The vanadium redox flow battery (VRB is a nonlinear system with unknown dynamics and disturbances. The flowrate of the electrolyte is an important control mechanism in the operation of a VRB system. Too low or too high flowrate is unfavorable for the safety and performance of VRB. This paper presents a neural network predictive control scheme to enhance the overall performance of the battery. A radial basis function (RBF network is employed to approximate the dynamics of the VRB system. The genetic algorithm (GA is used to obtain the optimum initial values of the RBF network parameters. The gradient descent algorithm is used to optimize the objective function of the predictive controller. Compared with the constant flowrate, the simulation results show that the flowrate optimized by neural network predictive controller can increase the power delivered by the battery during the discharge and decrease the power consumed during the charge.

  1. Advances in Artificial Neural Networks – Methodological Development and Application

    Directory of Open Access Journals (Sweden)

    Yanbo Huang

    2009-08-01

    Full Text Available 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 backpropagation training algorithm, have gained recognition in research and applications in various scientific and engineering areas. In order to accelerate the training process and overcome data over-fitting, research has been conducted to improve the backpropagation algorithm. Further, artificial neural networks have been integrated with other advanced methods such as fuzzy logic and wavelet analysis, to enhance the ability of data interpretation and modeling and to avoid subjectivity in the operation of the training algorithm. In recent years, support vector machines have emerged as a set of high-performance supervised generalized linear classifiers in parallel with artificial neural networks. A review on development history of artificial neural networks is presented and the standard architectures and algorithms of artificial neural networks are described. Furthermore, advanced artificial neural networks will be introduced with support vector machines, and limitations of ANNs will be identified. The future of artificial neural network development in tandem with support vector machines will be discussed in conjunction with further applications to food science and engineering, soil and water relationship for crop management, and decision support for precision agriculture. Along with the network structures and training algorithms, the applications of artificial neural networks will be reviewed as well, especially in the fields of agricultural and biological

  2. Structure, Kinematics and Origin of Radial Faults: 3D Seismic Observations from the Santos Basin, offshore Brazil

    Science.gov (United States)

    Coleman, Alexander; Jackson, Christopher A.-L.

    2017-04-01

    Salt stock growth is typically accompanied by the development of geometrically and kinematically complex fault networks in the surrounding country rock. The most common networks comprise radial faults; these are characterised by low displacement (stock into flanking strata. Radial faults are commonly observed in an arched, unpierced roof developed above a rising salt stock; in these cases, the faults are typically well-imaged seismically and likely form due to outer-arc extension during overburden stretching. Radial faults are also found at deeper structural levels, in strata flanking the diapir stem; in these cases, they are typically less well-imaged, thus their structure, kinematics and origin are less well understood. Furthermore, understanding the growth of radial faults may provide insights into hydrocarbon reservoir compartmentalisation and the evolution of neighbouring salt stocks. Here, we use high-quality 3D seismic reflection data from the Santos Basin, offshore Brazil to determine the structure and kinematics, and infer the likely origin of exceptionally well-imaged radial faults overlying and flanking a mature salt stock. Furthermore, we compare the geometric (e.g. throw, geometry, spacing, distribution etc.) and kinematic (e.g. timing of formation and duration of activity) characteristics of radial faults at both structural levels, allowing us to infer their temporal relationship and likely origins. We show that radial faults regardless of their structural level typically have aspect ratios of c. 1.8 - 2, are laterally-restricted in the vicinity of the salt, and have lengths of indices of c. 1, with low throw gradients of 0.05 - 0.1 at the upper tip indicate that radial faults were likely blind. Throws range from 5 - 80 ms, with throw-maxima within 1 - 2 radii of the salt diapir. However, we note that the position of the throw maxima is not at the same level for all radial faults. We propose that radial faults nucleate and initially grow as blind

  3. Prediction of dissolved oxygen in the Mediterranean Sea along Gaza, Palestine - an artificial neural network approach.

    Science.gov (United States)

    Zaqoot, Hossam Adel; Ansari, Abdul Khalique; Unar, Mukhtiar Ali; Khan, Shaukat Hyat

    2009-01-01

    Artificial Neural Networks (ANNs) are flexible tools which are being used increasingly to predict and forecast water resources variables. The human activities in areas surrounding enclosed and semi-enclosed seas such as the Mediterranean Sea always produce in the long term a strong environmental impact in the form of coastal and marine degradation. The presence of dissolved oxygen is essential for the survival of most organisms in the water bodies. This paper is concerned with the use of ANNs - Multilayer Perceptron (MLP) and Radial Basis Function neural networks for predicting the next fortnight's dissolved oxygen concentrations in the Mediterranean Sea water along Gaza. MLP and Radial Basis Function (RBF) neural networks are trained and developed with reference to five important oceanographic variables including water temperature, wind velocity, turbidity, pH and conductivity. These variables are considered as inputs of the network. The data sets used in this study consist of four years and collected from nine locations along Gaza coast. The network performance has been tested with different data sets and the results show satisfactory performance. Prediction results prove that neural network approach has good adaptability and extensive applicability for modelling the dissolved oxygen in the Mediterranean Sea along Gaza. We hope that the established model will help in assisting the local authorities in developing plans and policies to reduce the pollution along Gaza coastal waters to acceptable levels.

  4. Anomalies of radial and ulnar arteries

    Directory of Open Access Journals (Sweden)

    Rajani Singh

    Full Text Available Abstract During dissection conducted in an anatomy department of the right upper limb of the cadaver of a 70-year-old male, both origin and course of the radial and ulnar arteries were found to be anomalous. After descending 5.5 cm from the lower border of the teres major, the brachial artery anomalously bifurcated into a radial artery medially and an ulnar artery laterally. In the arm, the ulnar artery lay lateral to the median nerve. It followed a normal course in the forearm. The radial artery was medial to the median nerve in the arm and then, at the level of the medial epicondyle, it crossed from the medial to the lateral side of the forearm, superficial to the flexor muscles. The course of the radial artery was superficial and tortuous throughout the arm and forearm. The variations of radial and ulnar arteries described above were associated with anomalous formation and course of the median nerve in the arm. Knowledge of neurovascular anomalies are important for vascular surgeons and radiologists.

  5. Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Ruchi D. Chande

    2017-01-01

    Full Text Available Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

  6. Predictive Behavior of a Computational Foot/Ankle Model through Artificial Neural Networks.

    Science.gov (United States)

    Chande, Ruchi D; Hargraves, Rosalyn Hobson; Ortiz-Robinson, Norma; Wayne, Jennifer S

    2017-01-01

    Computational models are useful tools to study the biomechanics of human joints. Their predictive performance is heavily dependent on bony anatomy and soft tissue properties. Imaging data provides anatomical requirements while approximate tissue properties are implemented from literature data, when available. We sought to improve the predictive capability of a computational foot/ankle model by optimizing its ligament stiffness inputs using feedforward and radial basis function neural networks. While the former demonstrated better performance than the latter per mean square error, both networks provided reasonable stiffness predictions for implementation into the computational model.

  7. On-line identification of hybrid systems using an adaptive growing and pruning RBF neural network

    DEFF Research Database (Denmark)

    Alizadeh, Tohid

    2008-01-01

    This paper introduces an adaptive growing and pruning radial basis function (GAP-RBF) neural network for on-line identification of hybrid systems. The main idea is to identify a global nonlinear model that can predict the continuous outputs of hybrid systems. In the proposed approach, GAP......-RBF neural network uses a modified unscented kalman filter (UKF) with forgetting factor scheme as the required on-line learning algorithm. The effectiveness of the resulting identification approach is tested and evaluated on a simulated benchmark hybrid system....

  8. Robust stabilization of burn conditions in subignited fusion reactors using artificial neural networks

    International Nuclear Information System (INIS)

    Vitela, E. Javier; Martinell, J. Julio

    2000-01-01

    In this work it is shown that robust burn control in long pulse operations of thermonuclear reactors can be successfully achieved with artificial neural networks. The results reported here correspond to a volume averaged zero-dimensional nonlinear model of a subignited fusion device using the design parameters of the tokamak EDA-ITER group. A Radial Basis Neural Network (RBNN) was trained to provide feedback stabilization at a fixed operating point independently of any particular scaling law that the reactor confinement time may follow. A numerically simulated transient is used to illustrate the stabilization capabilities of the resulting RBNN when the reactor follows an ELMy scaling law corrupted with Gaussian noise. (author)

  9. Physical mechanism determining the radial electric field and its radial structure in a toroidal plasma

    International Nuclear Information System (INIS)

    Ida, Katsumi; Miura, Yukitoshi; Itoh, Sanae

    1994-10-01

    Radial structures of plasma rotation and radial electric field are experimentally studied in tokamak, heliotron/torsatron and stellarator devices. The perpendicular and parallel viscosities are measured. The parallel viscosity, which is dominant in determining the toroidal velocity in heliotron/torsatron and stellarator devices, is found to be neoclassical. On the other hand, the perpendicular viscosity, which is dominant in dictating the toroidal rotation in tokamaks, is anomalous. Even without external momentum input, both a plasma rotation and a radial electric field exist in tokamaks and heliotrons/torsatrons. The observed profiles of the radial electric field do not agree with the theoretical prediction based on neoclassical transport. This is mainly due to the existence of anomalous perpendicular viscosity. The shear of the radial electric field improves particle and heat transport both in bulk and edge plasma regimes of tokamaks. (author) 95 refs

  10. Manufacturing of Precision Forgings by Radial Forging

    International Nuclear Information System (INIS)

    Wallner, S.; Harrer, O.; Buchmayr, B.; Hofer, F.

    2011-01-01

    Radial forging is a multi purpose incremental forging process using four tools on the same plane. It is widely used for the forming of tool steels, super alloys as well as titanium- and refractory metals. The range of application goes from reducing the diameters of shafts, tubes, stepped shafts and axels, as well as for creating internal profiles for tubes in Near-Net-Shape and Net-Shape quality. Based on actual development of a weight optimized transmission input shaft, the specific features of radial forging technology is demonstrated. Also a Finite Element Model for the simulation of the process is shown which leads to reduced pre-processing effort and reduced computing time compared to other published simulation methods for radial forging. The finite element model can be applied to quantify the effects of different forging strategies.

  11. Radial velocity observations of VB10

    Science.gov (United States)

    Deshpande, R.; Martin, E.; Zapatero Osorio, M. R.; Del Burgo, C.; Rodler, F.; Montgomery, M. M.

    2011-07-01

    VB 10 is the smallest star known to harbor a planet according to the recent astrometric study of Pravdo & Shaklan [1]. Here we present near-infrared (J-band) radial velocity of VB 10 performed from high resolution (R~20,000) spectroscopy (NIRSPEC/KECK II). Our results [2] suggest radial velocity variability with amplitude of ~1 km/s, a result that is consistent with the presence of a massive planet companion around VB10 as found via long-term astrometric monitoring of the star by Pravdo & Shaklan. Employing an entirely different technique we verify the results of Pravdo & Shaklan.

  12. Plasma Signatures of Radial Field Power Dropouts

    International Nuclear Information System (INIS)

    Lucek, E.A.; Horbury, T.S.; Balogh, A.; McComas, D.J.

    1998-01-01

    A class of small scale structures, with a near-radial magnetic field and a drop in magnetic field fluctuation power, have recently been identified in the polar solar wind. An earlier study of 24 events, each lasting for 6 hours or more, identified no clear plasma signature. In an extension of that work, radial intervals lasting for 4 hours or more (89 in total), have been used to search for a statistically significant plasma signature. It was found that, despite considerable variations between intervals, there was a small but significant drop, on average, in plasma temperature, density and β during these events

  13. Reble, a radially converging electron beam accelerator

    International Nuclear Information System (INIS)

    Ramirez, J.J.; Prestwich, K.R.

    1976-01-01

    The Reble accelerator at Sandia Laboratories is described. This accelerator was developed to provide an experimental source for studying the relevant diode physics, beam propagation, beam energy deposition in a gas using a radially converging e-beam. The nominal parameters for Reble are 1 MV, 200 kA, 20 ns e-beam pulse. The anode and cathode are concentric cylinders with the anode as the inner cylinder. The radial beam can be propagated through the thin foil anode into the laser gas volume. The design and performance of the various components of the accelerator are presented

  14. A Regularizer Approach for RBF Networks Under the Concurrent Weight Failure Situation.

    Science.gov (United States)

    Leung, Chi-Sing; Wan, Wai Yan; Feng, Ruibin

    2017-06-01

    Many existing results on fault-tolerant algorithms focus on the single fault source situation, where a trained network is affected by one kind of weight failure. In fact, a trained network may be affected by multiple kinds of weight failure. This paper first studies how the open weight fault and the multiplicative weight noise degrade the performance of radial basis function (RBF) networks. Afterward, we define the objective function for training fault-tolerant RBF networks. Based on the objective function, we then develop two learning algorithms, one batch mode and one online mode. Besides, the convergent conditions of our online algorithm are investigated. Finally, we develop a formula to estimate the test set error of faulty networks trained from our approach. This formula helps us to optimize some tuning parameters, such as RBF width.

  15. Prediction of friction factor of pure water flowing inside vertical smooth and microfin tubes by using artificial neural networks

    Science.gov (United States)

    Çebi, A.; Akdoğan, E.; Celen, A.; Dalkilic, A. S.

    2017-02-01

    An artificial neural network (ANN) model of friction factor in smooth and microfin tubes under heating, cooling and isothermal conditions was developed in this study. Data used in ANN was taken from a vertically positioned heat exchanger experimental setup. Multi-layered feed-forward neural network with backpropagation algorithm, radial basis function networks and hybrid PSO-neural network algorithm were applied to the database. Inputs were the ratio of cross sectional flow area to hydraulic diameter, experimental condition number depending on isothermal, heating, or cooling conditions and mass flow rate while the friction factor was the output of the constructed system. It was observed that such neural network based system could effectively predict the friction factor values of the flows regardless of their tube types. A dependency analysis to determine the strongest parameter that affected the network and database was also performed and tube geometry was found to be the strongest parameter of all as a result of analysis.

  16. Solution of the chemical master equation by radial basis functions approximation with interface tracking

    NARCIS (Netherlands)

    Kryven, I.; Röblitz, S; Schütte, C.

    2015-01-01

    Background: The chemical master equation is the fundamental equation of stochastic chemical kinetics. This differential-difference equation describes temporal evolution of the probability density function for states of a chemical system. A state of the system, usually encoded as a vector, represents

  17. Hybrid model decomposition of speech and noise in a radial basis function neural model framework

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Hartmann, Uwe

    1994-01-01

    The aim of the paper is to focus on a new approach to automatic speech recognition in noisy environments where the noise has either stationary or non-stationary statistical characteristics. The aim is to perform automatic recognition of speech in the presence of additive car noise. The technique...

  18. A meshless local radial basis function method for two-dimensional incompressible Navier-Stokes equations

    KAUST Repository

    Wang, Zhiheng; Huang, Zhu; Zhang, Wei; Xi, Guang

    2014-01-01

    main advantages of the method. One is that the unstructured nodes generation in the computational domain is quite simple, without much concern about the mesh quality; the other is that the localization of the obtained collocations for the discretization

  19. A Sequential Optimization Sampling Method for Metamodels with Radial Basis Functions

    Science.gov (United States)

    Pan, Guang; Ye, Pengcheng; Yang, Zhidong

    2014-01-01

    Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is strongly affected by the sampling methods. In this paper, a new sequential optimization sampling method is proposed. Based on the new sampling method, metamodels can be constructed repeatedly through the addition of sampling points, namely, extrema points of metamodels and minimum points of density function. Afterwards, the more accurate metamodels would be constructed by the procedure above. The validity and effectiveness of proposed sampling method are examined by studying typical numerical examples. PMID:25133206

  20. Warping a Neuro-Anatomy Atlas on 3D MRI Data with Radial Basis Functions

    NARCIS (Netherlands)

    Bennink, H.E.; Korbeeck, J.M.; Janssen, B.J.; Haar Romenij, ter B.M.

    2006-01-01

    Navigation for neurosurgical procedures must be highly accurate. Often small structures are hardly seen on pre-operative scans. Fitting a 3D electronic neuro-anatomical atlas on the data assists with the localization of small structures and dim outlines. During surgery also brainshifts occurs. With

  1. Numerical simulations of flapping foil and wing aerodynamics : Mesh deformation using radial basis functions

    NARCIS (Netherlands)

    Bos, F.M.

    2010-01-01

    Both biological and engineering scientist have always been intrigued by the flight of insects and birds. For a long time, the aerodynamic mechanism behind flapping insect flight was a complete mystery. Recently, several experimental and numerical flow visualisations were performed to investigate the

  2. An efficient approach for electric load forecasting using distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network) neural network

    International Nuclear Information System (INIS)

    Cai, Yuan; Wang, Jian-zhou; Tang, Yun; Yang, Yu-chen

    2011-01-01

    This paper presents a neural network based on adaptive resonance theory, named distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network), applied to the electric load forecasting problem. The distributed ART combines the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multi-layer perceptions. The HS-ARTMAP, a hybrid of an RBF (Radial Basis Function)-network-like module which uses hyper-sphere basis function substitute the Gaussian basis function and an ART-like module, performs incremental learning capabilities in function approximation problem. The HS-ARTMAP only receives the compressed distributed coding processed by distributed ART to deal with the proliferation problem which ARTMAP (adaptive resonance theory map) architecture often encounters and still performs well in electric load forecasting. To demonstrate the performance of the methodology, data from New South Wales and Victoria in Australia are illustrated. Results show that the developed method is much better than the traditional BP and single HS-ARTMAP neural network. -- Research highlights: → The processing of the presented network is based on compressed distributed data. It's an innovation among the adaptive resonance theory architecture. → The presented network decreases the proliferation the Fuzzy ARTMAP architectures usually encounter. → The network on-line forecasts electrical load accurately, stably. → Both one-period and multi-period load forecasting are executed using data of different cities.

  3. On helicon wave induced radial plasma transport

    International Nuclear Information System (INIS)

    Petrzilka, V.

    1993-04-01

    Estimates of helicon wave induced radial plasma transport are presented. The wave induced transport grows or decreases in dependence on the sign of the azimuthal wave number; these changes in transport may play an important role in helicon wave plasma sources. (author) 5 figs., 18 refs

  4. Revealing the radial modes in vortex beams

    CSIR Research Space (South Africa)

    Sephton, Bereneice C

    2016-10-01

    Full Text Available Light beams that carry orbital angular momentum are often approximated by modulating an initial beam, usually Gaussian, with an azimuthal phase variation to create a vortex beam. Such vortex beams are well defined azimuthally, but the radial profile...

  5. Measurement of Wear in Radial Journal Bearings

    NARCIS (Netherlands)

    Ligterink, D.J.; Ligterink, D.J.; de Gee, A.W.J.

    1996-01-01

    this article, the measurement of wear in radial journal bearings is discussed, where a distinction is made between stationary and non-stationary contact conditions. Starting with Holm/Archard's wear law, equations are derived for the calculation of the specific wear rate k of the bearing material as

  6. Radial interchange motions of plasma filaments

    DEFF Research Database (Denmark)

    Garcia, O.E.; Bian, N.H.; Fundamenski, W.

    2006-01-01

    on a biperiodic domain perpendicular to the magnetic field. It is demonstrated that a blob-like plasma structure develops dipolar vorticity and electrostatic potential fields, resulting in rapid radial acceleration and formation of a steep front and a trailing wake. While the dynamical evolution strongly depends...

  7. Radial transfer effects for poloidal rotation

    Science.gov (United States)

    Hallatschek, Klaus

    2010-11-01

    Radial transfer of energy or momentum is the principal agent responsible for radial structures of Geodesic Acoustic Modes (GAMs) or stationary Zonal Flows (ZF) generated by the turbulence. For the GAM, following a physical approach, it is possible to find useful expressions for the individual components of the Poynting flux or radial group velocity allowing predictions where a mathematical full analysis is unfeasible. Striking differences between up-down symmetric flux surfaces and asymmetric ones have been found. For divertor geometries, e.g., the direction of the propagation depends on the sign of the ion grad-B drift with respect to the X-point, reminiscent of a sensitive determinant of the H-mode threshold. In nonlocal turbulence computations it becomes obvious that the linear energy transfer terms can be completely overwhelmed by the action of the turbulence. In contrast, stationary ZFs are governed by the turbulent radial transfer of momentum. For sufficiently large systems, the Reynolds stress becomes a deterministic functional of the flows, which can be empirically determined from the stress response in computational turbulence studies. The functional allows predictions even on flow/turbulence states not readily obtainable from small amplitude noise, such as certain transport bifurcations or meta-stable states.

  8. Computing modal dispersion characteristics of radially Asymmetric ...

    African Journals Online (AJOL)

    We developed a matrix theory that applies to with non-circular/circular but concentric layers fibers. And we compute the dispersion characteristics of radially unconventional fiber, known as Asymmetric Bragg fiber. An attempt has been made to determine how the modal characteristics change as circular Bragg fiber is ...

  9. Zernike Basis to Cartesian Transformations

    Science.gov (United States)

    Mathar, R. J.

    2009-12-01

    The radial polynomials of the 2D (circular) and 3D (spherical) Zernike functions are tabulated as powers of the radial distance. The reciprocal tabulation of powers of the radial distance in series of radial polynomials is also given, based on projections that take advantage of the orthogonality of the polynomials over the unit interval. They play a role in the expansion of products of the polynomials into sums, which is demonstrated by some examples. Multiplication of the polynomials by the angular bases (azimuth, polar angle) defines the Zernike functions, for which we derive transformations to and from the Cartesian coordinate system centered at the middle of the circle or sphere.

  10. On the stability of a homogeneous barrier discharge in nitrogen relative to radial perturbations

    CERN Document Server

    Golubovskii, Y B; Behnke, J; Behnke, J F

    2003-01-01

    The influence of small radial perturbations of the cathode current on the characteristics of a homogeneous barrier discharge in nitrogen is investigated on the basis of a two-dimensional fluid model. In a Townsend discharge, radial fluctuations are substantially suppressed, which is the evidence of its stability. The oscillative mode of the Townsend discharge is also stable with regard to radial perturbations. As the discharge turns into a form controlled by spatial charge (a streamer is developed), disturbances of all radii grow in time. Such a behaviour testifies the instability of a streamer front and may cause the discharge filamentation. Since only the Townsend discharge is stable, it is possible to use a one-dimensional model to determine the domain of existence for a homogeneous discharge. The study of homogeneity domains by means of the one-dimensional model shows that at relatively large values of the voltage growth rate, discharge gap width, or capacitance of dielectric barriers the discharge tends ...

  11. Variations in the usage and composition of a radial cocktail during radial access coronary angiography procedures.

    LENUS (Irish Health Repository)

    Pate, G

    2011-10-01

    A survey was conducted of medication administered during radial artery cannulation for coronary angiography in 2009 in Ireland; responses were obtained for 15 of 20 centres, in 5 of which no radial access procedures were undertaken. All 10 (100%) centres which provided data used heparin and one or more anti-spasmodics; verapamil in 9 (90%), nitrate in 1 (10%), both in 2 (20%). There were significant variations in the doses used. Further work needs to be done to determine the optimum cocktail to prevent radial artery injury following coronary angiography.

  12. Radial wave crystals: radially periodic structures from anisotropic metamaterials for engineering acoustic or electromagnetic waves.

    Science.gov (United States)

    Torrent, Daniel; Sánchez-Dehesa, José

    2009-08-07

    We demonstrate that metamaterials with anisotropic properties can be used to develop a new class of periodic structures that has been named radial wave crystals. They can be sonic or photonic, and wave propagation along the radial directions is obtained through Bloch states like in usual sonic or photonic crystals. The band structure of the proposed structures can be tailored in a large amount to get exciting novel wave phenomena. For example, it is shown that acoustical cavities based on radial sonic crystals can be employed as passive devices for beam forming or dynamically orientated antennas for sound localization.

  13. Improved WKB radial wave functions in several bases

    International Nuclear Information System (INIS)

    Durand, B.; Durand, L.; Department of Physics, University of Wisconsin, Madison, Wisconsin 53706)

    1986-01-01

    We develop approximate WKB-like solutions to the radial Schroedinger equation for problems with an angular momentum barrier using Riccati-Bessel, Coulomb, and harmonic-oscillator functions as basis functions. The solutions treat the angular momentum singularity near the origin more accurately in leading approximation than the standard WKB solutions based on sine waves. The solutions based on Riccati-Bessel and free Coulomb wave functions continue smoothly through the inner turning point and are appropriate for scattering problems. The solutions based on oscillator and bound Coulomb wave functions incorporate both turning points smoothly and are particularly appropriate for bound-state problems; no matching of piecewise solutions using Airy functions is necessary

  14. Microinstabilities in a radially contracting inhomogeneous cylindrical plasma slab

    International Nuclear Information System (INIS)

    Deutsch, R.; Kaeppeler, H.J.

    1980-07-01

    In order to study the development of microinstabilities in a collapsing cylindrical plasma sheath, corresponding to the situations in a z-pinch or a plasma focus, the dispersion relation for electromagnetic perturbations is derived with the aid of a newly established slab-model for an inhomogeneous, radially contracting plasma. In contrast to previously used slab-models, the orientation of the electric field is in direction of the cylinder axis and the azimuthal magnetic field is induced by the current flowing through the cylindrical plasma slab. The Vlasov equation is used together with the Krook collision term in order to include the influence of collisions. The results of this theory presented in this report will be used to calculate the growth of drift instabilities in the compression phase of a plasma focus, and shall serve as a basis for further development of a more general dispersion relation including runaway-effects. (orig.)

  15. Logarithmic learning for generalized classifier neural network.

    Science.gov (United States)

    Ozyildirim, Buse Melis; Avci, Mutlu

    2014-12-01

    Generalized classifier neural network is introduced as an efficient classifier among the others. Unless the initial smoothing parameter value is close to the optimal one, generalized classifier neural network suffers from convergence problem and requires quite a long time to converge. In this work, to overcome this problem, a logarithmic learning approach is proposed. The proposed method uses logarithmic cost function instead of squared error. Minimization of this cost function reduces the number of iterations used for reaching the minima. The proposed method is tested on 15 different data sets and performance of logarithmic learning generalized classifier neural network is compared with that of standard one. Thanks to operation range of radial basis function included by generalized classifier neural network, proposed logarithmic approach and its derivative has continuous values. This makes it possible to adopt the advantage of logarithmic fast convergence by the proposed learning method. Due to fast convergence ability of logarithmic cost function, training time is maximally decreased to 99.2%. In addition to decrease in training time, classification performance may also be improved till 60%. According to the test results, while the proposed method provides a solution for time requirement problem of generalized classifier neural network, it may also improve the classification accuracy. The proposed method can be considered as an efficient way for reducing the time requirement problem of generalized classifier neural network. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Sustainability analysis. Development of various indicators of sustainability for technical environmental analysis and evaluation of local heat supply networks on the basis of regenerative energies in comparison to fossil energy sources; Nachhaltigkeitsanalyse. Entwicklung verschiedener Nachhaltigkeitsindikatoren zur umwelttechnischen Analyse und Bewertung von Nahwaermeversorgungsnetzen auf Basis regenerativer Energien im Vergleich zu fossilen Energietraegern

    Energy Technology Data Exchange (ETDEWEB)

    Hehenberger-Risse, Diana

    2013-06-15

    The aim of this thesis is to define indicators to evaluate local heat supply systems based on renewable energy compared to fossil energy reference scenarios. With these indicators a assessment matrix was developed as a planning instrument for the realization of sustainable and energy-efficient local heat supply systems. Further inferences from single projects on regions can be done. In these thesis a method was developed to assess the sustainability of local heat supply systems with the focus on ecology under consideration of economically and social aspects. This method uses a set of indicators composed of Input-, Output-, Efficiency- and Balance indicators. To realize advancement in comparison to present situations, an environmental quality target to advance the environmental impacts of minimum 75% was defined. For the developing and application of the indicators different examples from projects and scenarios of combined heat production from Biomass, Biogas, Solar heat combined with near-surface geothermal storage; geothermal energy and fossil peakload supply were calculated. These scenarios were related to a basis fossil energy scenario. Overall, the two district heating projects Speichersdorf and Mitterteich were compared. In this case, the project Speichersdorf with different coverage areas and decrease heat densities was investigated. The lengths of electrical grid of two areas are 10,828 m and 6,027 m. Those were opposed to the biomass district-heating project Mitterteich with a grid length of 360 m and a higher heat density decrease. Furthermore, a scenario for heat supply was designed and calculated using geothermal plant operating in duplicate to provide heat to the large coverage area for the storage project village. The calculation of the various processes and scenarios was performed with the program GEMIS 4.8 based on the total heat generated (final energy) by the respective supply type. The study examined the main system components; boilers, solar heat

  17. Radial restricted solid-on-solid and etching interface-growth models

    Science.gov (United States)

    Alves, Sidiney G.

    2018-03-01

    An approach to generate radial interfaces is presented. A radial network recursively obtained is used to implement discrete model rules designed originally for the investigation in flat substrates. I used the restricted solid-on-solid and etching models as to test the proposed scheme. The results indicate the Kardar, Parisi, and Zhang conjecture is completely verified leading to a good agreement between the interface radius fluctuation distribution and the Gaussian unitary ensemble. The evolution of the radius agrees well with the generalized conjecture, and the two-point correlation function exhibits also a good agreement with the covariance of the Airy2 process. The approach can be used to investigate radial interfaces evolution for many other classes of universality.

  18. Radial velocity asymmetries from jets with variable velocity profiles

    International Nuclear Information System (INIS)

    Cerqueira, A. H.; Vasconcelos, M. J.; Velazquez, P. F.; Raga, A. C.; De Colle, F.

    2006-01-01

    We have computed a set of 3-D numerical simulations of radiatively cooling jets including variabilities in both the ejection direction (precession) and the jet velocity (intermittence), using the Yguazu-a code. In order to investigate the effects of jet rotation on the shape of the line profiles, we also introduce an initial toroidal rotation velocity profile. Since the Yguazu-a code includes an atomic/ionic network, we are able to compute the emission coefficients for several emission lines, and we generate line profiles for the Hα, [O I]λ6300, [S II]λ6716 and [N II]λ6548 lines. Using initial parameters that are suitable for the DG Tau microjet, we show that the computed radial velocity shift for the medium-velocity component of the line profile as a function of distance from the jet axis is strikingly similar for rotating and non-rotating jet models

  19. Sustainability analysis. Development of various indicators of sustainability for technical environmental analysis and evaluation of local heat supply networks on the basis of regenerative energies in comparison to fossil energy sources

    International Nuclear Information System (INIS)

    Hehenberger-Risse, Diana

    2013-06-01

    The aim of this thesis is to define indicators to evaluate local heat supply systems based on renewable energy compared to fossil energy reference scenarios. With these indicators a assessment matrix was developed as a planning instrument for the realization of sustainable and energy-efficient local heat supply systems. Further inferences from single projects on regions can be done. In these thesis a method was developed to assess the sustainability of local heat supply systems with the focus on ecology under consideration of economically and social aspects. This method uses a set of indicators composed of Input-, Output-, Efficiency- and Balance indicators. To realize advancement in comparison to present situations, an environmental quality target to advance the environmental impacts of minimum 75% was defined. For the developing and application of the indicators different examples from projects and scenarios of combined heat production from Biomass, Biogas, Solar heat combined with near-surface geothermal storage; geothermal energy and fossil peakload supply were calculated. These scenarios were related to a basis fossil energy scenario. Overall, the two district heating projects Speichersdorf and Mitterteich were compared. In this case, the project Speichersdorf with different coverage areas and decrease heat densities was investigated. The lengths of electrical grid of two areas are 10,828 m and 6,027 m. Those were opposed to the biomass district-heating project Mitterteich with a grid length of 360 m and a higher heat density decrease. Furthermore, a scenario for heat supply was designed and calculated using geothermal plant operating in duplicate to provide heat to the large coverage area for the storage project village. The calculation of the various processes and scenarios was performed with the program GEMIS 4.8 based on the total heat generated (final energy) by the respective supply type. The study examined the main system components; boilers, solar heat

  20. Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

    Science.gov (United States)

    Lo, Ching F.

    1999-01-01

    The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.

  1. Safety Basis Report

    International Nuclear Information System (INIS)

    R.J. Garrett

    2002-01-01

    As part of the internal Integrated Safety Management Assessment verification process, it was determined that there was a lack of documentation that summarizes the safety basis of the current Yucca Mountain Project (YMP) site characterization activities. It was noted that a safety basis would make it possible to establish a technically justifiable graded approach to the implementation of the requirements identified in the Standards/Requirements Identification Document. The Standards/Requirements Identification Documents commit a facility to compliance with specific requirements and, together with the hazard baseline documentation, provide a technical basis for ensuring that the public and workers are protected. This Safety Basis Report has been developed to establish and document the safety basis of the current site characterization activities, establish and document the hazard baseline, and provide the technical basis for identifying structures, systems, and components (SSCs) that perform functions necessary to protect the public, the worker, and the environment from hazards unique to the YMP site characterization activities. This technical basis for identifying SSCs serves as a grading process for the implementation of programs such as Conduct of Operations (DOE Order 5480.19) and the Suspect/Counterfeit Items Program. In addition, this report provides a consolidated summary of the hazards analyses processes developed to support the design, construction, and operation of the YMP site characterization facilities and, therefore, provides a tool for evaluating the safety impacts of changes to the design and operation of the YMP site characterization activities

  2. Safety Basis Report

    Energy Technology Data Exchange (ETDEWEB)

    R.J. Garrett

    2002-01-14

    As part of the internal Integrated Safety Management Assessment verification process, it was determined that there was a lack of documentation that summarizes the safety basis of the current Yucca Mountain Project (YMP) site characterization activities. It was noted that a safety basis would make it possible to establish a technically justifiable graded approach to the implementation of the requirements identified in the Standards/Requirements Identification Document. The Standards/Requirements Identification Documents commit a facility to compliance with specific requirements and, together with the hazard baseline documentation, provide a technical basis for ensuring that the public and workers are protected. This Safety Basis Report has been developed to establish and document the safety basis of the current site characterization activities, establish and document the hazard baseline, and provide the technical basis for identifying structures, systems, and components (SSCs) that perform functions necessary to protect the public, the worker, and the environment from hazards unique to the YMP site characterization activities. This technical basis for identifying SSCs serves as a grading process for the implementation of programs such as Conduct of Operations (DOE Order 5480.19) and the Suspect/Counterfeit Items Program. In addition, this report provides a consolidated summary of the hazards analyses processes developed to support the design, construction, and operation of the YMP site characterization facilities and, therefore, provides a tool for evaluating the safety impacts of changes to the design and operation of the YMP site characterization activities.

  3. WWER radial reflector modeling by diffusion codes

    International Nuclear Information System (INIS)

    Petkov, P. T.; Mittag, S.

    2005-01-01

    The two commonly used approaches to describe the WWER radial reflectors in diffusion codes, by albedo on the core-reflector boundary and by a ring of diffusive assembly size nodes, are discussed. The advantages and disadvantages of the first approach are presented first, then the Koebke's equivalence theory is outlined and its implementation for the WWER radial reflectors is discussed. Results for the WWER-1000 reactor are presented. Then the boundary conditions on the outer reflector boundary are discussed. The possibility to divide the library into fuel assembly and reflector parts and to generate each library by a separate code package is discussed. Finally, the homogenization errors for rodded assemblies are presented and discussed (Author)

  4. Oculoauriculovertebral spectrum with radial anomaly in child.

    Science.gov (United States)

    Taksande, Amar; Vilhekar, Krishna

    2013-01-01

    Oculoauriculovertebral spectrum (OAVS) or Goldenhar syndrome is a wide spectrum of congenital anomalies that involves structures arising from the first and second branchial arches. It is characterized by a wide spectrum of symptoms and physical features. These abnormalities mainly involve the cheekbones, jaws, mouth, ears, eyes, or vertebrae. Other conditions with ear and/or radial involvement, such as, the Nager syndrome, Holt-Oram syndrome, Radial-renal syndrome, facioauriculoradial dysplasia, Fanconi anemia, and Vertebral, Anal atresia, Cardiac, Trachea, Esophageal, Renal, and Limb (VACTERL) association should be considered for differential diagnosis. Here we report a child who had facial asymmetry, microsomia, microtia, congenital facial nerve palsy, conductive hearing loss, skin tags, iris coloboma, and preaxial polydactyly.

  5. Oculoauriculovertebral spectrum with radial anomaly in child

    Directory of Open Access Journals (Sweden)

    Amar Taksande

    2013-01-01

    Full Text Available Oculoauriculovertebral spectrum (OAVS or Goldenhar syndrome is a wide spectrum of congenital anomalies that involves structures arising from the first and second branchial arches. It is characterized by a wide spectrum of symptoms and physical features. These abnormalities mainly involve the cheekbones, jaws, mouth, ears, eyes, or vertebrae. Other conditions with ear and/or radial involvement, such as, the Nager syndrome, Holt-Oram syndrome, Radial-renal syndrome, facioauriculoradial dysplasia, Fanconi anemia, and Vertebral, Anal atresia, Cardiac, Trachea, Esophageal, Renal, and Limb (VACTERL association should be considered for differential diagnosis. Here we report a child who had facial asymmetry, microsomia, microtia, congenital facial nerve palsy, conductive hearing loss, skin tags, iris coloboma, and preaxial polydactyly.

  6. Linear radial pulsation theory. Lecture 5

    International Nuclear Information System (INIS)

    Cox, A.N.

    1983-01-01

    We describe a method for getting an equilibrium stellar envelope model using as input the total mass, the envelope mass, the surface effective temperature, the total surface luminosity, and the composition of the envelope. Then wih the structure of the envelope model known, we present a method for obtaining the raidal pulsation periods and growth rates for low order modes. The large amplitude pulsations observed for the yellow and red giants and supergiants are always these radial models, but for the stars nearer the main sequence, as for all of our stars and for the white dwarfs, there frequently are nonradial modes occuring also. Application of linear theory radial pulsation theory is made to the giant star sigma Scuti variables, while the linear nonradial theory will be used for the B stars in later lectures

  7. SpicyNodes Radial Map Engine

    Science.gov (United States)

    Douma, M.; Ligierko, G.; Angelov, I.

    2008-10-01

    The need for information has increased exponentially over the past decades. The current systems for constructing, exploring, classifying, organizing, and searching information face the growing challenge of enabling their users to operate efficiently and intuitively in knowledge-heavy environments. This paper presents SpicyNodes, an advanced user interface for difficult interaction contexts. It is based on an underlying structure known as a radial map, which allows users to manipulate and interact in a natural manner with entities called nodes. This technology overcomes certain limitations of existing solutions and solves the problem of browsing complex sets of linked information. SpicyNodes is also an organic system that projects users into a living space, stimulating exploratory behavior and fostering creative thought. Our interactive radial layout is used for educational purposes and has the potential for numerous other applications.

  8. Stability of a radial immiscible drive

    Energy Technology Data Exchange (ETDEWEB)

    Bataille, J

    1968-11-01

    The stability of the displacement front between 2 immiscible fluids of radial flow between 2 parallel plates (Hele-Shaw model) is studied mathematically by superposing onto the circular displacement front a sinusoidal perturbation. The equations are reduced to dimensionless variables, and it is shown that the stable and unstable domains in a plot: dimensionless viscosity vs. dimensionless time are separated by a polygonal contour, each side of the contour being characterized by the (integer) number of perturbations along the circumference. There is a critical reduced time below which the perturbations are amortized but beyond which they are amplified. Experimental results have been in fair general agreement with theoretical results, the divergence between them being attributable to neglecting capillary phenomena, which may become very important at large radial distances. One test with miscible fluids has shown that even in this case, there is a critical time or an equivalent critical radius.

  9. Radial oxygen gradients over rat cortex arterioles

    OpenAIRE

    Galler, Michael

    2011-01-01

    Purpose: We present the results of the visualisation of radial oxygen gradients in rats’ cortices and their use in neurocritical management. Methods: PO2 maps of the cortex of 10 wistar rats were obtained with a camera (SensiMOD, PCO, Kehlheim, Germany). Those pictures were analyzed and edited by a custom-made software. We chose a vessel for examination. A matrix, designed to evaluate the cortical O2 partial pressure, was placed vertically to the artery and afterwards multiple regio...

  10. Variational method for integrating radial gradient field

    Science.gov (United States)

    Legarda-Saenz, Ricardo; Brito-Loeza, Carlos; Rivera, Mariano; Espinosa-Romero, Arturo

    2014-12-01

    We propose a variational method for integrating information obtained from circular fringe pattern. The proposed method is a suitable choice for objects with radial symmetry. First, we analyze the information contained in the fringe pattern captured by the experimental setup and then move to formulate the problem of recovering the wavefront using techniques from calculus of variations. The performance of the method is demonstrated by numerical experiments with both synthetic and real data.

  11. Moment approach to tandem mirror radial transport

    International Nuclear Information System (INIS)

    Siebert, K.D.; Callen, J.D.

    1986-02-01

    A moment approach is proposed for the study of tandem mirror radial transport in the resonant plateau regime. The salient features of the method are described with reference to axisymmetric tokamak transport theory. In particular, the importance of momentum conservation to the establishment of the azimuthal variations in the electrostatic potential is demonstrated. Also, an ad hoc drift kinetic equation is solved to determine parallel viscosity coefficients which are required to close the moment system

  12. Numerical simulation of radial compressor stage

    Science.gov (United States)

    Syka, T.; Luňáček, O.

    2013-04-01

    Article describes numerical simulations of air flow in radial compressor stage in NUMECA CFD software. In simulations geometry variants with and without seals are used. During tasks evaluating was observed seals influence on flow field and performance parameters of compressor stage. Also is described CFDresults comparison with results from design software based on experimental measurements and monitoring of influence of seals construction on compressor stage efficiency.

  13. Numerical simulation of radial compressor stage

    OpenAIRE

    Luňáček O.; Syka T.

    2013-01-01

    Article describes numerical simulations of air flow in radial compressor stage in NUMECA CFD software. In simulations geometry variants with and without seals are used. During tasks evaluating was observed seals influence on flow field and performance parameters of compressor stage. Also is described CFDresults comparison with results from design software based on experimental measurements and monitoring of influence of seals construction on compressor stage efficiency.

  14. Numerical simulation of radial compressor stage

    Directory of Open Access Journals (Sweden)

    Luňáček O.

    2013-04-01

    Full Text Available Article describes numerical simulations of air flow in radial compressor stage in NUMECA CFD software. In simulations geometry variants with and without seals are used. During tasks evaluating was observed seals influence on flow field and performance parameters of compressor stage. Also is described CFDresults comparison with results from design software based on experimental measurements and monitoring of influence of seals construction on compressor stage efficiency.

  15. Radial excitations in nucleon-nucleon scattering

    International Nuclear Information System (INIS)

    Silvestre-Brac, B.; Carbonell, J.; Gignoux, C.

    1986-01-01

    In the non-relativistic constituent quark model, the role of the radial excitations of the nucleon is studied within a resonating group approach of the nucleon-nucleon scattering. It is shown that, rather than the inclusion of new channels, it is important to include mixed-symmetry spin-isospin components in the nucleon wave function. It is also found that during the collision there is no significant deformation of the nucleon. (orig.)

  16. Fuel radial design using Path Relinking

    International Nuclear Information System (INIS)

    Campos S, Y.

    2007-01-01

    The present work shows the obtained results when implementing the combinatory optimization technique well-known as Path Re linking (Re-linkage of Trajectories), to the problem of the radial design of nuclear fuel assemblies, for boiling water reactors (BWR Boiling Water Reactor by its initials in English), this type of reactors is those that are used in the Laguna Verde Nucleo electric Central, Veracruz. As in any other electric power generation plant of that make use of some fuel to produce heat and that it needs each certain time (from 12 to 14 months) to make a supply of the same one, because this it wears away or it burns, in the nucleolectric plants to this activity is denominated fuel reload. In this reload different activities intervene, among those which its highlight the radial and axial designs of fuel assemblies, the patterns of control rods and the multi cycles study, each one of these stages with their own complexity. This work was limited to study in independent form the radial design, without considering the other activities. These phases are basic for the fuel reload design and of reactor operation strategies. (Author)

  17. Development of a Radial Deconsolidation Method

    Energy Technology Data Exchange (ETDEWEB)

    Helmreich, Grant W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Montgomery, Fred C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Hunn, John D. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-12-01

    A series of experiments have been initiated to determine the retention or mobility of fission products* in AGR fuel compacts [Petti, et al. 2010]. This information is needed to refine fission product transport models. The AGR-3/4 irradiation test involved half-inch-long compacts that each contained twenty designed-to-fail (DTF) particles, with 20-μm thick carbon-coated kernels whose coatings were deliberately fabricated such that they would crack under irradiation, providing a known source of post-irradiation isotopes. The DTF particles in these compacts were axially distributed along the compact centerline so that the diffusion of fission products released from the DTF kernels would be radially symmetric [Hunn, et al. 2012; Hunn et al. 2011; Kercher, et al. 2011; Hunn, et al. 2007]. Compacts containing DTF particles were irradiated at Idaho National Laboratory (INL) at the Advanced Test Reactor (ATR) [Collin, 2015]. Analysis of the diffusion of these various post-irradiation isotopes through the compact requires a method to radially deconsolidate the compacts so that nested-annular volumes may be analyzed for post-irradiation isotope inventory in the compact matrix, TRISO outer pyrolytic carbon (OPyC), and DTF kernels. An effective radial deconsolidation method and apparatus appropriate to this application has been developed and parametrically characterized.

  18. Temperature and boron dependencies of buckling and radial reflector saving for VVER lattices

    International Nuclear Information System (INIS)

    Alvarez, C.

    1990-01-01

    The temperature and boron dependencies of buckling and radial reflectors savings are analyzed in this paper on the basis of the results from the calculations ZR-6M critical assembly. These dependencies are related to the physical behavior of temperature and boron reactivity coefficients for the cores of VVER-type critical facilities. As a byproduct, the parameter was also investigated and its dependence on water density was determined

  19. Temperature and boron dependencies of buckling and radial reflector savings for VVER lattices

    International Nuclear Information System (INIS)

    Alvarez, C.

    1990-01-01

    The temperature and boron dependencies of buckling and radial reflector savings are analyzed in this paper on the basis of the results from the calculations for the ZR-6M critical assembly. These dependencies are related to he physical behaviour of temperature and boron reactivity coefficients for the cores of VVER-type critical facilities. As a byproduct, the dp/dBg 2 parameter was also investigated and its dependence on water density was determined

  20. Linear theory radial and nonradial pulsations of DA dwarf stars

    International Nuclear Information System (INIS)

    Starrfield, S.; Cox, A.N.; Hodson, S.; Pesnell, W.D.

    1982-01-01

    The Los Alamos stellar envelope and radial linear non-adiabatic computer code, along with a new Los Alamos non-radial code are used to investigate the total hydrogen mass necessary to produce the non-radial instability of DA dwarfs

  1. Radial distribution of ions in pores with a surface charge

    NARCIS (Netherlands)

    Stegen, J.H.G. van der; Görtzen, J.; Kuipers, J.A.M.; Hogendoorn, J.A.; Versteeg, G.F.

    2001-01-01

    A sorption model applicable to calculate the radial equilibrium concentrations of ions in the pores of ion-selective membranes with a pore structure is developed. The model is called the radial uptake model. Because the model is applied to a Nafion sulfonic layer with very small pores and the radial

  2. Experimental feasibility study of radial injection cooling of three-pad radial air foil bearings

    Science.gov (United States)

    Shrestha, Suman K.

    Air foil bearings use ambient air as a lubricant allowing environment-friendly operation. When they are designed, installed, and operated properly, air foil bearings are very cost effective and reliable solution to oil-free turbomachinery. Because air is used as a lubricant, there are no mechanical contacts between the rotor and bearings and when the rotor is lifted off the bearing, near frictionless quiet operation is possible. However, due to the high speed operation, thermal management is one of the very important design factors to consider. Most widely accepted practice of the cooling method is axial cooling, which uses cooling air passing through heat exchange channels formed underneath the bearing pad. Advantage is no hardware modification to implement the axial cooling because elastic foundation structure of foil bearing serves as a heat exchange channels. Disadvantage is axial temperature gradient on the journal shaft and bearing. This work presents the experimental feasibility study of alternative cooling method using radial injection of cooling air directly on the rotor shaft. The injection speeds, number of nozzles, location of nozzles, total air flow rate are important factors determining the effectiveness of the radial injection cooling method. Effectiveness of the radial injection cooling was compared with traditional axial cooling method. A previously constructed test rig was modified to accommodate a new motor with higher torque and radial injection cooling. The radial injection cooling utilizes the direct air injection to the inlet region of air film from three locations at 120° from one another with each location having three axially separated holes. In axial cooling, a certain axial pressure gradient is applied across the bearing to induce axial cooling air through bump foil channels. For the comparison of the two methods, the same amount of cooling air flow rate was used for both axial cooling and radial injection. Cooling air flow rate was

  3. Neural feedback linearization adaptive control for affine nonlinear systems based on neural network estimator

    Directory of Open Access Journals (Sweden)

    Bahita Mohamed

    2011-01-01

    Full Text Available In this work, we introduce an adaptive neural network controller for a class of nonlinear systems. The approach uses two Radial Basis Functions, RBF networks. The first RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are unknown. The second RBF network is used for on-line estimating the control gain which is a nonlinear and unknown function of the states. The updating laws for the combined estimator and controller are derived through Lyapunov analysis. Asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, the proposed method is applied to control and stabilize the inverted pendulum system.

  4. Application of CMAC Neural Network to Solar Energy Heliostat Field Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Neng-Sheng Pai

    2013-01-01

    Full Text Available Solar energy heliostat fields comprise numerous sun tracking platforms. As a result, fault detection is a highly challenging problem. Accordingly, the present study proposes a cerebellar model arithmetic computer (CMAC neutral network for automatically diagnosing faults within the heliostat field in accordance with the rotational speed, vibration, and temperature characteristics of the individual heliostat transmission systems. As compared with radial basis function (RBF neural network and back propagation (BP neural network in the heliostat field fault diagnosis, the experimental results show that the proposed neural network has a low training time, good robustness, and a reliable diagnostic performance. As a result, it provides an ideal solution for fault diagnosis in modern, large-scale heliostat fields.

  5. A Sliding Mode Control-Based on a RBF Neural Network for Deburring Industry Robotic Systems

    Directory of Open Access Journals (Sweden)

    Yong Tao

    2016-01-01

    Full Text Available A sliding mode control method based on radial basis function (RBF neural network is proposed for the deburring of industry robotic systems. First, a dynamic model for deburring the robot system is established. Then, a conventional SMC scheme is introduced for the joint position tracking of robot manipulators. The RBF neural network based sliding mode control (RBFNN-SMC has the ability to learn uncertain control actions. In the RBFNN-SMC scheme, the adaptive tuning algorithms for network parameters are derived by a Koski function algorithm to ensure the network convergences and enacts stable control. The simulations and experimental results of the deburring robot system are provided to illustrate the effectiveness of the proposed RBFNN-SMC control method. The advantages of the proposed RBFNN-SMC method are also evaluated by comparing it to existing control schemes.

  6. Incorporation of distributed generation and shunt capacitor in radial distribution system for techno-economic benefits

    Directory of Open Access Journals (Sweden)

    Mukul Dixit

    2017-04-01

    The various costs such as purchase active power from grid, DG installation, capacitor installation, DG Operation and Maintenance (O&M are evaluated at two different load scenarios. In addition to that, technical and economical analyses are examined for various combinations of DGs and shunt capacitors. The proposed methodology is successfully demonstrated on 33-bus and 85-bus radial networks and the obtained numerical outcomes validate the suitability, importance and effectiveness to identify locations as well as sizes of DGs and shunt capacitors.

  7. MARVELS Radial Velocity Solutions to Seven Kepler Eclipsing Binaries

    Science.gov (United States)

    Heslar, Michael Francis; Thomas, Neil B.; Ge, Jian; Ma, Bo; Herczeg, Alec; Reyes, Alan; SDSS-III MARVELS Team

    2016-01-01

    Eclipsing binaries serve momentous purposes to improve the basis of understanding aspects of stellar astrophysics, such as the accurate calculation of the physical parameters of stars and the enigmatic mass-radius relationship of M and K dwarfs. We report the investigation results of 7 eclipsing binary candidates, initially identified by the Kepler mission, overlapped with the radial velocity observations from the SDSS-III Multi-Object APO Radial-Velocity Exoplanet Large-Area Survey (MARVELS). The RV extractions and spectroscopic solutions of these eclipsing binaries were generated by the University of Florida's 1D data pipeline with a median RV precision of ~60-100 m/s, which was utilized for the DR12 data release. We performed the cross-reference fitting of the MARVELS RV data and the Kepler photometric fluxes obtained from the Kepler Eclipsing Binary Catalog (V2) and modelled the 7 eclipsing binaries in the BinaryMaker3 and PHOEBE programs. This analysis accurately determined the absolute physical and orbital parameters of each binary. Most of the companion stars were determined to have masses of K and M dwarf stars (0.3-0.8 M⊙), and allowed for an investigation into the mass-radius relationship of M and K dwarfs. Among the cases are KIC 9163796, a 122.2 day period "heartbeat star", a recently-discovered class of eccentric binaries known for tidal distortions and pulsations, with a high eccentricity (e~0.75) and KIC 11244501, a 0.29 day period, contact binary with a double-lined spectrum and mass ratio (q~0.45). We also report on the possible reclassification of 2 Kepler eclipsing binary candidates as background eclipsing binaries based on the analysis of the flux measurements, flux ratios of the spectroscopic and photometric solutions, the differences in the FOVs, the image processing of Kepler, and RV and spectral analysis of MARVELS.

  8. Radial rescaling approach for the eigenvalue problem of a particle in an arbitrarily shaped box.

    Science.gov (United States)

    Lijnen, Erwin; Chibotaru, Liviu F; Ceulemans, Arnout

    2008-01-01

    In the present work we introduce a methodology for solving a quantum billiard with Dirichlet boundary conditions. The procedure starts from the exactly known solutions for the particle in a circular disk, which are subsequently radially rescaled in such a way that they obey the new boundary conditions. In this way one constructs a complete basis set which can be used to obtain the eigenstates and eigenenergies of the corresponding quantum billiard to a high level of precision. Test calculations for several regular polygons show the efficiency of the method which often requires one or two basis functions to describe the lowest eigenstates with high accuracy.

  9. Methods and apparatus for radially compliant component mounting

    Science.gov (United States)

    Bulman, David Edward [Cincinnati, OH; Darkins, Jr., Toby George; Stumpf, James Anthony [Columbus, IN; Schroder, Mark S [Greenville, SC; Lipinski, John Joseph [Simpsonville, SC

    2012-03-27

    Methods and apparatus for a mounting assembly for a liner of a gas turbine engine combustor are provided. The combustor includes a combustor liner and a radially outer annular flow sleeve. The mounting assembly includes an inner ring surrounding a radially outer surface of the liner and including a plurality of axially extending fingers. The mounting assembly also includes a radially outer ring coupled to the inner ring through a plurality of spacers that extend radially from a radially outer surface of the inner ring to the outer ring.

  10. RADIALLY MAGNETIZED PROTOPLANETARY DISK: VERTICAL PROFILE

    International Nuclear Information System (INIS)

    Russo, Matthew; Thompson, Christopher

    2015-01-01

    This paper studies the response of a thin accretion disk to an external radial magnetic field. Our focus is on protoplanetary disks (PPDs), which are exposed during their later evolution to an intense, magnetized wind from the central star. A radial magnetic field is mixed into a thin surface layer, wound up by the disk shear, and pushed downward by a combination of turbulent mixing and ambipolar and ohmic drift. The toroidal field reaches much greater strengths than the seed vertical field that is usually invoked in PPD models, even becoming superthermal. Linear stability analysis indicates that the disk experiences the magnetorotational instability (MRI) at a higher magnetization than a vertically magnetized disk when both the effects of ambipolar and Hall drift are taken into account. Steady vertical profiles of density and magnetic field are obtained at several radii between 0.06 and 1 AU in response to a wind magnetic field B r ∼ (10 −4 –10 −2 )(r/ AU) −2 G. Careful attention is given to the radial and vertical ionization structure resulting from irradiation by stellar X-rays. The disk is more strongly magnetized closer to the star, where it can support a higher rate of mass transfer. As a result, the inner ∼1 AU of a PPD is found to evolve toward lower surface density. Mass transfer rates around 10 −8 M ⊙ yr −1 are obtained under conservative assumptions about the MRI-generated stress. The evolution of the disk and the implications for planet migration are investigated in the accompanying paper

  11. RADIALLY MAGNETIZED PROTOPLANETARY DISK: VERTICAL PROFILE

    Energy Technology Data Exchange (ETDEWEB)

    Russo, Matthew [Department of Physics, University of Toronto, 60 St. George St., Toronto, ON M5S 1A7 (Canada); Thompson, Christopher [Canadian Institute for Theoretical Astrophysics, 60 St. George St., Toronto, ON M5S 3H8 (Canada)

    2015-11-10

    This paper studies the response of a thin accretion disk to an external radial magnetic field. Our focus is on protoplanetary disks (PPDs), which are exposed during their later evolution to an intense, magnetized wind from the central star. A radial magnetic field is mixed into a thin surface layer, wound up by the disk shear, and pushed downward by a combination of turbulent mixing and ambipolar and ohmic drift. The toroidal field reaches much greater strengths than the seed vertical field that is usually invoked in PPD models, even becoming superthermal. Linear stability analysis indicates that the disk experiences the magnetorotational instability (MRI) at a higher magnetization than a vertically magnetized disk when both the effects of ambipolar and Hall drift are taken into account. Steady vertical profiles of density and magnetic field are obtained at several radii between 0.06 and 1 AU in response to a wind magnetic field B{sub r} ∼ (10{sup −4}–10{sup −2})(r/ AU){sup −2} G. Careful attention is given to the radial and vertical ionization structure resulting from irradiation by stellar X-rays. The disk is more strongly magnetized closer to the star, where it can support a higher rate of mass transfer. As a result, the inner ∼1 AU of a PPD is found to evolve toward lower surface density. Mass transfer rates around 10{sup −8} M{sub ⊙} yr{sup −1} are obtained under conservative assumptions about the MRI-generated stress. The evolution of the disk and the implications for planet migration are investigated in the accompanying paper.

  12. Theoretical basis for dosimetry

    International Nuclear Information System (INIS)

    Carlsson, G.A.

    1985-01-01

    Radiation dosimetry is fundamental to all fields of science dealing with radiation effects and is concerned with problems which are often intricate as hinted above. A firm scientific basis is needed to face increasing demands on accurate dosimetry. This chapter is an attempt to review and to elucidate the elements for such a basis. Quantities suitable for radiation dosimetry have been defined in the unique work to coordinate radiation terminology and usage by the International Commission on Radiation Units and Measurements, ICRU. Basic definitions and terminology used in this chapter conform with the recent ''Radiation Quantities and Units, Report 33'' of the ICRU

  13. Radial fractional Laplace operators and Hessian inequalities

    Science.gov (United States)

    Ferrari, Fausto; Verbitsky, Igor E.

    In this paper we deduce a formula for the fractional Laplace operator ( on radially symmetric functions useful for some applications. We give a criterion of subharmonicity associated with (, and apply it to a problem related to the Hessian inequality of Sobolev type: ∫Rn |(u| dx⩽C∫Rn -uFk[u] dx, where Fk is the k-Hessian operator on Rn, 1⩽kFerrari et al. [5] contains the extremal functions for the Hessian Sobolev inequality of X.-J. Wang (1994) [15]. This is proved using logarithmic convexity of the Gaussian ratio of hypergeometric functions which might be of independent interest.

  14. Convex and Radially Concave Contoured Distributions

    Directory of Open Access Journals (Sweden)

    Wolf-Dieter Richter

    2015-01-01

    Full Text Available Integral representations of the locally defined star-generalized surface content measures on star spheres are derived for boundary spheres of balls being convex or radially concave with respect to a fan in Rn. As a result, the general geometric measure representation of star-shaped probability distributions and the general stochastic representation of the corresponding random vectors allow additional specific interpretations in the two mentioned cases. Applications to estimating and testing hypotheses on scaling parameters are presented, and two-dimensional sample clouds are simulated.

  15. On radial flow between parallel disks

    International Nuclear Information System (INIS)

    Wee, A Y L; Gorin, A

    2015-01-01

    Approximate analytical solutions are presented for converging flow in between two parallel non rotating disks. The static pressure distribution and radial component of the velocity are developed by averaging the inertial term across the gap in between parallel disks. The predicted results from the first approximation are favourable to experimental results as well as results presented by other authors. The second approximation shows that as the fluid approaches the center, the velocity at the mid channel slows down which is due to the struggle between the inertial term and the flowrate. (paper)

  16. Zernike Basis to Cartesian Transformations

    Directory of Open Access Journals (Sweden)

    Mathar, R. J.

    2009-12-01

    Full Text Available The radial polynomials of the 2D (circular and 3D (spherical Zernike functions are tabulated as powers of the radial distance. The reciprocal tabulation of powers of the radial distance in series of radial polynomials is also given, based on projections that take advantage of the orthogonality of the polynomials over the unit interval. They play a role in the expansion of products of the polynomials into sums, which is demonstrated by some examples. Multiplication of the polynomials by the angular bases (azimuth, polar angle defines the Zernike functions, for which we derive transformations to and from the Cartesian coordinate system centered at the middle of the circle or sphere.

  17. Zernike basis to cartesian transformations

    Directory of Open Access Journals (Sweden)

    Mathar R.J.

    2009-01-01

    Full Text Available The radial polynomials of the 2D (circular and 3D (spherical Zernike functions are tabulated as powers of the radial distance. The reciprocal tabulation of powers of the radial distance in series of radial polynomials is also given, based on projections that take advantage of the orthogonality of the polynomials over the unit interval. They play a role in the expansion of products of the polynomials into sums, which is demonstrated by some examples. Multiplication of the polynomials by the angular bases (azimuth, polar angle defines the Zernike functions, for which we derive transformations to and from the Cartesian coordinate system centered at the middle of the circle or sphere.

  18. Radial-Velocity Signatures of Magnetic Features on the Sun Observed as a Star

    Science.gov (United States)

    Palumbo, M. L., III; Haywood, R. D.; Saar, S. H.; Dupree, A. K.; Milbourne, T. W.

    2017-12-01

    In recent years, the search for Earth-mass planets using radial-velocity measurements has become increasingly limited by signals arising from stellar activity. Individual magnetic features induce localized changes in intensity and velocity, which combine to change the apparent radial velocity of the star. Therefore it is critical to identify an indicator of activity-driven radial-velocity variations on the timescale of stellar rotation periods. We use 617.3 nm photospheric filtergrams, magnetograms, and dopplergrams from SDO/HMI and 170.0 nm chromospheric filtergrams from AIA to identify magnetically-driven solar features and reconstruct the integrated solar radial velocity with six samples per day over the course of 2014. Breaking the solar image up into regions of umbrae, penumbrae, quiet Sun, network, and plages, we find a distinct variation in the center-to-limb intensity-weighted velocity for each region. In agreement with past studies, we find that the suppression of convective blueshift is dominated by plages and network, rather than dark photospheric features. In the future, this work will be highly useful for identifying indicators which correlate with rotationally modulated radial-velocity variations. This will allow us to break the activity barrier that currently precludes the precise characterization of exoplanet properties at the lowest masses. This work was supported by the NSF-REU solar physics program at SAO, grant number AGS-1560313. This work was performed in part under contract with the California Institute of Technology (Caltech)/Jet Propulsion Laboratory (JPL) funded by NASA through the Sagan Fellowship Program executed by the NASA Exoplanet Science Institute.

  19. Intraluminal milrinone for dilation of the radial artery graft.

    Science.gov (United States)

    García-Rinaldi, R; Soltero, E R; Carballido, J; Mojica, J

    1999-01-01

    There is renewed interest in the use of the radial artery as a conduit for coronary artery bypass surgery. The radial artery is, however, a very muscular artery, prone to vasospasm. Milrinone, a potent vasodilator, has demonstrated vasodilatory properties superior to those of papaverine. In this report, we describe our technique of radial artery harvesting and the adjunctive use of intraluminal milrinone as a vasodilator in the preparation of this conduit for coronary artery bypass grafting. We have used these techniques in 25 patients who have undergone coronary artery bypass grafting using the radial artery. No hand ischemic complications have been observed in this group. Intraluminal milrinone appears to dilate and relax the radial artery, rendering this large conduit spasm free and very easy to use. We recommend the skeletonization technique for radial artery harvesting and the use of intraluminal milrinone as a radial artery vasodilator in routine myocardial revascularization. PMID:10524740

  20. Neural network-based model reference adaptive control system.

    Science.gov (United States)

    Patino, H D; Liu, D

    2000-01-01

    In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

  1. Robust Forecasting for Energy Efficiency of Wireless Multimedia Sensor Networks.

    Science.gov (United States)

    Wang, Xue; Ma, Jun-Jie; Ding, Liang; Bi, Dao-Wei

    2007-11-15

    An important criterion of wireless sensor network is the energy efficiency inspecified applications. In this wireless multimedia sensor network, the observations arederived from acoustic sensors. Focused on the energy problem of target tracking, this paperproposes a robust forecasting method to enhance the energy efficiency of wirelessmultimedia sensor networks. Target motion information is acquired by acoustic sensornodes while a distributed network with honeycomb configuration is constructed. Thereby,target localization is performed by multiple sensor nodes collaboratively through acousticsignal processing. A novel method, combining autoregressive moving average (ARMA)model and radial basis function networks (RBFNs), is exploited to perform robust targetposition forecasting during target tracking. Then sensor nodes around the target areawakened according to the forecasted target position. With committee decision of sensornodes, target localization is performed in a distributed manner and the uncertainty ofdetection is reduced. Moreover, a sensor-to-observer routing approach of the honeycombmesh network is investigated to solve the data reporting considering the residual energy ofsensor nodes. Target localization and forecasting are implemented in experiments.Meanwhile, sensor node awakening and dynamic routing are evaluated. Experimentalresults verify that energy efficiency of wireless multimedia sensor network is enhanced bythe proposed target tracking method.

  2. From BASIS to MIRACLES

    DEFF Research Database (Denmark)

    Tsapatsaris, Nikolaos; Willendrup, Peter Kjær; E. Lechner, Ruep

    2015-01-01

    Results based on virtual instrument models for the first high-flux, high-resolution, spallation based, backscattering spectrometer, BASIS are presented in this paper. These were verified using the Monte Carlo instrument simulation packages McStas and VITESS. Excellent agreement of the neutron count...... are pivotal to the conceptual design of the next generation backscattering spectrometer, MIRACLES at the European Spallation Source....

  3. A new model of Earth's radial conductivity structure derived from over 10 yr of satellite and observatory magnetic data

    DEFF Research Database (Denmark)

    Püthe, Christoph; Kuvshinov, Alexey; Khan, Amir

    2015-01-01

    We present a newmodel of the radial (1-D) conductivity structure of Earth's mantle. This model is derived frommore than 10 yr of magnetic measurements from the satellites ørsted, CHAMP, SAC-C and the Swarm trio as well as the global network of geomagnetic observatories. After removal of core...

  4. Asymptotic Solutions of Serial Radial Fuel Shuffling

    Directory of Open Access Journals (Sweden)

    Xue-Nong Chen

    2015-12-01

    Full Text Available In this paper, the mechanism of traveling wave reactors (TWRs is investigated from the mathematical physics point of view, in which a stationary fission wave is formed by radial fuel drifting. A two dimensional cylindrically symmetric core is considered and the fuel is assumed to drift radially according to a continuous fuel shuffling scheme. A one-group diffusion equation with burn-up dependent macroscopic coefficients is set up. The burn-up dependent macroscopic coefficients were assumed to be known as functions of neutron fluence. By introducing the effective multiplication factor keff, a nonlinear eigenvalue problem is formulated. The 1-D stationary cylindrical coordinate problem can be solved successively by analytical and numerical integrations for associated eigenvalues keff. Two representative 1-D examples are shown for inward and outward fuel drifting motions, respectively. The inward fuel drifting has a higher keff than the outward one. The 2-D eigenvalue problem has to be solved by a more complicated method, namely a pseudo time stepping iteration scheme. Its 2-D asymptotic solutions are obtained together with certain eigenvalues keff for several fuel inward drifting speeds. Distributions of the neutron flux, the neutron fluence, the infinity multiplication factor kinf and the normalized power are presented for two different drifting speeds.

  5. [Comparison of chemical quality characteristics between radial striations and non-radial striations in tuberous root of Rehmannia glutinosa].

    Science.gov (United States)

    Xie, Cai-Xia; Zhang, Miao; Li, Ya-Jing; Geng, Xiao-Tong; Wang, Feng-Qing; Zhang, Zhong-Yi

    2017-11-01

    An HPLC method was established to determine the contents of catalpol, acteoside, rehmaionoside A, rehmaionoside D, leonuride in three part of Rehmanni glutinosa in Beijing No.1 variety R. glutinosa during the growth period, This method, in combination with its HPLC fingerprint was used to evaluate its overall quality characteristics.The results showed that:① the content of main components of R. glutinosa varied in different growth stages ;② there was a great difference of the content of main components between theradial striations and the non-radial striations; ③ the two sections almost have the same content distribution of catalpol, acteoside and rehmaionoside D; ④the content of rehmaionoside A in non-radial striations was higher than that in radial striations,while the content of leonuride in radial striations was higher than that in non-radial striations.; ⑤the HPLC fingerprint of radial striations, non-radial striations and whole root tuber were basically identical, except for the big difference in the content of chemical components. The result of clustering displayed that the radial striations, non-radial striations, and whole root were divided into two groups. In conclusion, there was a significant difference in the quality characteristics of radial striations and non-radial striations of R. glutinosa. This research provides a reference for quality evaluation and geoherbalism of R. glutinosa. Copyright© by the Chinese Pharmaceutical Association.

  6. Radial electromagnetic force calculation of induction motor based on multi-loop theory

    Directory of Open Access Journals (Sweden)

    HE Haibo

    2017-12-01

    Full Text Available [Objectives] In order to study the vibration and noise of induction motors, a method of radial electromagnetic force calculation is established on the basis of the multi-loop model.[Methods] Based on the method of calculating air-gap magneto motive force according to stator and rotor fundamental wave current, the analytic formulas are deduced for calculating the air-gap magneto motive force and radial electromagnetic force generated in accordance with any stator winding and rotor conducting bar current. The multi-loop theory and calculation method for the electromagnetic parameters of a motor are introduced, and a dynamic simulation model of an induction motor built to achieve the current of the stator winding and rotor conducting bars, and obtain the calculation formula of radial electromagnetic force. The radial electromagnetic force and vibration are then estimated.[Results] The experimental results indicate that the vibration acceleration frequency and amplitude of the motor are consistent with the experimental results.[Conclusions] The results and calculation method can support the low noise design of converters.

  7. Effects of various factors on Doppler ultrasonographic measurements of radial and coccygeal arterial blood pressure in privately owned, conscious cats.

    Science.gov (United States)

    Whittemore, Jacqueline C; Nystrom, Michael R; Mawby, Dianne I

    2017-04-01

    OBJECTIVE To assess the effects of age, body condition score (BCS), and muscle condition score (MCS) on radial and coccygeal systolic arterial blood pressure (SAP) in cats. DESIGN Prospective randomized trial. ANIMALS 66 privately owned cats enrolled between May and December 2010. PROCEDURES BCS and MCS of cats were assessed by 2 investigators; SAP was measured via Doppler ultrasonic flow detector, with cats positioned in right lateral or sternal recumbency for measurements at the radial or coccygeal artery, respectively, with order of site randomized. Associations among variables were assessed through correlation coefficients, partial correlation coefficients, and ANCOVA. RESULTS Interrater reliability for BCS and MCS assessment was high (correlation coefficients, 0.95 and 0.83, respectively). No significant effect was identified for order of SAP measurement sites. Coccygeal and radial SAP were positively correlated (ρ = 0.45). The median difference in coccygeal versus radial SAP was 19 mm Hg, but differences were not consistently positive or negative. Radial SAP was positively correlated with age (ρ = 0.48) and negatively correlated with MCS (ρ = -0.30). On the basis of the correlation analysis, the association between radial SAP and MCS reflected the confounding influence of age. Coccygeal SAP was not significantly correlated with age, BCS, or MCS. CONCLUSIONS AND CLINICAL RELEVANCE Use of the coccygeal artery is recommended to reduce the confounding effects of age and sarcopenia on Doppler ultrasonographic SAP measurements in cats. Additionally, monitoring for changes in MCS is recommended for cats undergoing serial SAP measurement.

  8. Computed tomography arthrography using a radial plane view for the detection of triangular fibrocartilage complex foveal tears.

    Science.gov (United States)

    Moritomo, Hisao; Arimitsu, Sayuri; Kubo, Nobuyuki; Masatomi, Takashi; Yukioka, Masao

    2015-02-01

    To classify triangular fibrocartilage complex (TFCC) foveal lesions on the basis of computed tomography (CT) arthrography using a radial plane view and to correlate the CT arthrography results with surgical findings. We also tested the interobserver and intra-observer reliability of the radial plane view. A total of 33 patients with a suspected TFCC foveal tear who had undergone wrist CT arthrography and subsequent surgical exploration were enrolled. We classified the configurations of TFCC foveal lesions into 5 types on the basis of CT arthrography with the radial plane view in which the image slices rotate clockwise centered on the ulnar styloid process. Sensitivity, specificity, and positive predictive values were calculated for each type of foveal lesion in CT arthrography to detect foveal tears. We determined interobserver and intra-observer agreements using kappa statistics. We also compared accuracies with the radial plane views with those with the coronal plane views. Among the tear types on CT arthrography, type 3, a roundish defect at the fovea, and type 4, a large defect at the overall ulnar insertion, had high specificity and positive predictive value for the detection of foveal tears. Specificity and positive predictive values were 90% and 89% for type 3 and 100% and 100% for type 4, respectively, whereas sensitivity was 35% for type 3 and 22% for type 4. Interobserver and intra-observer agreement was substantial and almost perfect, respectively. The radial plane view identified foveal lesion of each palmar and dorsal radioulnar ligament separately, but accuracy results with the radial plane views were not statistically different from those with the coronal plane views. Computed tomography arthrography with a radial plane view exhibited enhanced specificity and positive predictive value when a type 3 or 4 lesion was identified in the detection of a TFCC foveal tear compared with historical controls. Diagnostic II. Copyright © 2015 American Society for

  9. Dynamical basis set

    International Nuclear Information System (INIS)

    Blanco, M.; Heller, E.J.

    1985-01-01

    A new Cartesian basis set is defined that is suitable for the representation of molecular vibration-rotation bound states. The Cartesian basis functions are superpositions of semiclassical states generated through the use of classical trajectories that conform to the intrinsic dynamics of the molecule. Although semiclassical input is employed, the method becomes ab initio through the standard matrix diagonalization variational method. Special attention is given to classical-quantum correspondences for angular momentum. In particular, it is shown that the use of semiclassical information preferentially leads to angular momentum eigenstates with magnetic quantum number Vertical BarMVertical Bar equal to the total angular momentum J. The present method offers a reliable technique for representing highly excited vibrational-rotational states where perturbation techniques are no longer applicable

  10. Design basis 2

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, G.; Soerensen, P. [Risoe National Lab., Roskilde (Denmark)

    1996-09-01

    Design Basis Program 2 (DBP2) is comprehensive fully coupled code which has the capability to operate in the time domain as well as in the frequency domain. The code was developed during the period 1991-93 and succeed Design Basis 1, which is a one-blade model presuming stiff tower, transmission system and hub. The package is designed for use on a personal computer and offers a user-friendly environment based on menu-driven editing and control facilities, and with graphics used extensively for the data presentation. Moreover in-data as well as results are dumped on files in Ascii-format. The input data is organized in a in-data base with a structure that easily allows for arbitrary combinations of defined structural components and load cases. (au)

  11. Employing a secure Virtual Private Network (VPN) infrastructure as a global command and control gateway to dynamically connect and disconnect diverse forces on a task-force-by-task-force basis

    OpenAIRE

    Kilcrease, Patrick N.

    2009-01-01

    Approved for public release, distribution unlimited GHOSTNet is a secure and anonymous Virtual Private Network (VPN) service. Coupling Ethernet tunneling and proxy services to provide users safe and anonymous Internet access, GHOSTNet utilizes TLS (SSL) protocol with AES-256 encryption to secure the network along with PKI certificates and HMAC protection from replay attacks and UDP flooding. This thesis will be a system level test and evaluation of the GHOSTNet infrastructure. The primary...

  12. Prediction of vibration characteristics of a planar mechanism having imperfect joints using neural network

    International Nuclear Information System (INIS)

    Erkaya, Selcuk

    2012-01-01

    Clearance is inevitable in the joints of mechanisms due primarily to the design, manufacturing and assembly processes or a wear effect. Excessive value of joint clearance plays a crucial role and has a significant effect on the kinematic and dynamic performances of the mechanism. In this study, effects of joint clearances on bearing vibrations of mechanism are investigated. An experimental test rig is set up, and a planar slider-crank mechanism having two imperfect joints with radial clearance is used as a model mechanism. Three accelerometers are positioned at different points to measure the bearing vibrations during the mechanism motion. For the different running speeds and clearance sizes, this work provides a neural model to predict and estimate the bearing vibrations of the mechanical systems having imperfect joints. The results show that radial basis function (RBF) neural network has a superior performance for predicting and estimating the vibration characteristics of the mechanical system

  13. Reconstruction of an engine combustion process with a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, P J; Gu, F; Ball, A D [School of Engineering, University of Manchester, Manchester (United Kingdom)

    1998-12-31

    The cylinder pressure waveform in an internal combustion engine is one of the most important parameters in describing the engine combustion process. It is used for a range of diagnostic tasks such as identification of ignition faults or mechanical wear in the cylinders. However, it is very difficult to measure this parameter directly. Never-the-less, the cylinder pressure may be inferred from other more readily obtainable parameters. In this presentation it is shown how a Radial Basis Function network, which may be regarded as a form of neural network, may be used to model the cylinder pressure as a function of the instantaneous crankshaft velocity, recorded with a simple magnetic sensor. The application of the model is demonstrated on a four cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the model once trained are validated against measured data. (orig.) 4 refs.

  14. Reconstruction of an engine combustion process with a neural network

    Energy Technology Data Exchange (ETDEWEB)

    Jacob, P.J.; Gu, F.; Ball, A.D. [School of Engineering, University of Manchester, Manchester (United Kingdom)

    1997-12-31

    The cylinder pressure waveform in an internal combustion engine is one of the most important parameters in describing the engine combustion process. It is used for a range of diagnostic tasks such as identification of ignition faults or mechanical wear in the cylinders. However, it is very difficult to measure this parameter directly. Never-the-less, the cylinder pressure may be inferred from other more readily obtainable parameters. In this presentation it is shown how a Radial Basis Function network, which may be regarded as a form of neural network, may be used to model the cylinder pressure as a function of the instantaneous crankshaft velocity, recorded with a simple magnetic sensor. The application of the model is demonstrated on a four cylinder DI diesel engine with data from a wide range of speed and load settings. The prediction capabilities of the model once trained are validated against measured data. (orig.) 4 refs.

  15. Accelerated optimizations of an electromagnetic acoustic transducer with artificial neural networks as metamodels

    Directory of Open Access Journals (Sweden)

    S. Wang

    2017-08-01

    Full Text Available Electromagnetic acoustic transducers (EMATs are noncontact transducers generating ultrasonic waves directly in the conductive sample. Despite the advantages, their transduction efficiencies are relatively low, so it is imperative to build accurate multiphysics models of EMATs and optimize the structural parameters accordingly, using a suitable optimization algorithm. The optimizing process often involves a large number of runs of the computationally expensive numerical models, so metamodels as substitutes for the real numerical models are helpful for the optimizations. In this work the focus is on the artificial neural networks as the metamodels of an omnidirectional EMAT, including the multilayer feedforward networks trained with the basic and improved back propagation algorithms and the radial basis function networks with exact and nonexact interpolations. The developed neural-network programs are tested on an example problem. Then the model of an omnidirectional EMAT generating Lamb waves in a linearized steel plate is introduced, and various approaches to calculate the amplitudes of the displacement component waveforms are discussed. The neural-network metamodels are then built for the EMAT model and compared to the displacement component amplitude (or ratio of amplitudes surface data on a discrete grid of the design variables as the reference, applying a multifrequency model with FFT (fast Fourier transform/IFFT (inverse FFT processing. Finally the two-objective optimization problem is formulated with one objective function minimizing the ratio of the amplitude of the S0-mode Lamb wave to that of the A0 mode, and the other objective function minimizing as the negative amplitude of the A0 mode. Pareto fronts in the criterion space are solved with the neural-network models and the total time consumption is greatly decreased. From the study it could be observed that the radial basis function network with exact interpolation has the best

  16. MR accuracy and arthroscopic incidence of meniscal radial tears

    Energy Technology Data Exchange (ETDEWEB)

    Magee, Thomas; Shapiro, Marc; Williams, David [Department of Radiology, Neuroimaging Institute, 27 East Hibiscus Blvd., Melbourne, FL 32901 (United States)

    2002-12-01

    A meniscal radial tear is a vertical tear that involves the inner meniscal margin. The tear is most frequent in the middle third of the lateral meniscus and may extend outward in any direction. We report (1) the arthroscopic incidence of radial tears, (2) MR signs that aid in the detection of radial tears and (3) our prospective accuracy in detection of radial tears. Design and patients. Three musculoskeletal radiologists prospectively read 200 consecutive MR examinations of the knee that went on to arthroscopy by one orthopedic surgeon. MR images were assessed for location and MR characteristics of radial tears. MR criteria used for diagnosis of a radial tear were those outlined by Tuckman et al.: truncation, abnormal morphology and/or lack of continuity or absence of the meniscus on one or more MR images. An additional criterion used was abnormal increased signal in that area on fat-saturated proton density or T2-weighted coronal and sagittal images. Prospective MR readings were correlated with the arthroscopic findings.Results. Of the 200 consecutive knee arthroscopies, 28 patients had radial tears reported arthroscopically (14% incidence). MR readings prospectively demonstrated 19 of the 28 radial tears (68% sensitivity) when the criteria for diagnosis of a radial tear were truncation or abnormal morphology of the meniscus. With the use of the additional criterion of increased signal in the area of abnormal morphology on fat-saturated T2-weighted or proton density weighted sequences, the prospective sensitivity was 25 of 28 radial tears (89% sensitivity). There were no radial tears described in MR reports that were not demonstrated on arthroscopy (i.e., there were no false positive MR readings of radial tears in these 200 patients). Radial tears are commonly seen at arthroscopy. There was a 14% incidence in this series of 200 patients who underwent arthroscopy. Prospective detection of radial tears was 68% as compared with arthroscopy when the criteria as

  17. MR accuracy and arthroscopic incidence of meniscal radial tears

    International Nuclear Information System (INIS)

    Magee, Thomas; Shapiro, Marc; Williams, David

    2002-01-01

    A meniscal radial tear is a vertical tear that involves the inner meniscal margin. The tear is most frequent in the middle third of the lateral meniscus and may extend outward in any direction. We report (1) the arthroscopic incidence of radial tears, (2) MR signs that aid in the detection of radial tears and (3) our prospective accuracy in detection of radial tears. Design and patients. Three musculoskeletal radiologists prospectively read 200 consecutive MR examinations of the knee that went on to arthroscopy by one orthopedic surgeon. MR images were assessed for location and MR characteristics of radial tears. MR criteria used for diagnosis of a radial tear were those outlined by Tuckman et al.: truncation, abnormal morphology and/or lack of continuity or absence of the meniscus on one or more MR images. An additional criterion used was abnormal increased signal in that area on fat-saturated proton density or T2-weighted coronal and sagittal images. Prospective MR readings were correlated with the arthroscopic findings.Results. Of the 200 consecutive knee arthroscopies, 28 patients had radial tears reported arthroscopically (14% incidence). MR readings prospectively demonstrated 19 of the 28 radial tears (68% sensitivity) when the criteria for diagnosis of a radial tear were truncation or abnormal morphology of the meniscus. With the use of the additional criterion of increased signal in the area of abnormal morphology on fat-saturated T2-weighted or proton density weighted sequences, the prospective sensitivity was 25 of 28 radial tears (89% sensitivity). There were no radial tears described in MR reports that were not demonstrated on arthroscopy (i.e., there were no false positive MR readings of radial tears in these 200 patients). Radial tears are commonly seen at arthroscopy. There was a 14% incidence in this series of 200 patients who underwent arthroscopy. Prospective detection of radial tears was 68% as compared with arthroscopy when the criteria as

  18. Sliding Mode Control for NSVs with Input Constraint Using Neural Network and Disturbance Observer

    Directory of Open Access Journals (Sweden)

    Yan-long Zhou

    2013-01-01

    Full Text Available The sliding mode control (SMC scheme is proposed for near space vehicles (NSVs with strong nonlinearity, high coupling, parameter uncertainty, and unknown time-varying disturbance based on radial basis function neural networks (RBFNNs and the nonlinear disturbance observer (NDO. Considering saturation characteristic of rudders, RBFNNs are constructed as a compensator to overcome the saturation nonlinearity. The stability of the closed-loop system is proved, and the tracking error as well as the disturbance observer error can converge to the origin through the Lyapunov analysis. Simulation results are presented to demonstrate the effectiveness of the proposed flight control scheme.

  19. Automated Stellar Classification for Large Surveys with EKF and RBF Neural Networks

    Institute of Scientific and Technical Information of China (English)

    Ling Bai; Ping Guo; Zhan-Yi Hu

    2005-01-01

    An automated classification technique for large size stellar surveys is proposed. It uses the extended Kalman filter as a feature selector and pre-classifier of the data, and the radial basis function neural networks for the classification.Experiments with real data have shown that the correct classification rate can reach as high as 93%, which is quite satisfactory. When different system models are selected for the extended Kalman filter, the classification results are relatively stable. It is shown that for this particular case the result using extended Kalman filter is better than using principal component analysis.

  20. Numerical analysis for multi-group neutron-diffusion equation using Radial Point Interpolation Method (RPIM)

    International Nuclear Information System (INIS)

    Kim, Kyung-O; Jeong, Hae Sun; Jo, Daeseong

    2017-01-01

    Highlights: • Employing the Radial Point Interpolation Method (RPIM) in numerical analysis of multi-group neutron-diffusion equation. • Establishing mathematical formation of modified multi-group neutron-diffusion equation by RPIM. • Performing the numerical analysis for 2D critical problem. - Abstract: A mesh-free method is introduced to overcome the drawbacks (e.g., mesh generation and connectivity definition between the meshes) of mesh-based (nodal) methods such as the finite-element method and finite-difference method. In particular, the Point Interpolation Method (PIM) using a radial basis function is employed in the numerical analysis for the multi-group neutron-diffusion equation. The benchmark calculations are performed for the 2D homogeneous and heterogeneous problems, and the Multiquadrics (MQ) and Gaussian (EXP) functions are employed to analyze the effect of the radial basis function on the numerical solution. Additionally, the effect of the dimensionless shape parameter in those functions on the calculation accuracy is evaluated. According to the results, the radial PIM (RPIM) can provide a highly accurate solution for the multiplication eigenvalue and the neutron flux distribution, and the numerical solution with the MQ radial basis function exhibits the stable accuracy with respect to the reference solutions compared with the other solution. The dimensionless shape parameter directly affects the calculation accuracy and computing time. Values between 1.87 and 3.0 for the benchmark problems considered in this study lead to the most accurate solution. The difference between the analytical and numerical results for the neutron flux is significantly increased in the edge of the problem geometry, even though the maximum difference is lower than 4%. This phenomenon seems to arise from the derivative boundary condition at (x,0) and (0,y) positions, and it may be necessary to introduce additional strategy (e.g., the method using fictitious points and

  1. Radial propagation of microturbulence in tokamaks

    International Nuclear Information System (INIS)

    Garbet, X.; Laurent, L.; Roubin, J.P.; Samain, A.

    1992-01-01

    Energy confinement time in tokamaks exhibits a clear dependence on global plasma parameters. This is not the case for transport coefficients; their dependence on local plasma parameters cannot be precisely established. The aim of the present paper is to give a possible explanation of this behaviour; turbulence propagates radially because of departure from cylindrical geometry. This implies that the turbulence level at a given point and hence transport coefficients are not only functions of local plasma parameters. A quantitative estimate of the propagation velocity is derived from a Lagrangian formalism. Two cases are considered: the effect of toroidicity and the effect of non linear mode-mode coupling. The consequences of this model are discussed. This process does not depend on the type of instability. For the sake of simplicity only electrostatic perturbations are considered

  2. Radial particle distributions in PARMILA simulation beams

    International Nuclear Information System (INIS)

    Boicourt, G.P.

    1984-03-01

    The estimation of beam spill in particle accelerators is becoming of greater importance as higher current designs are being funded. To the present, no numerical method for predicting beam-spill has been available. In this paper, we present an approach to the loss-estimation problem that uses probability distributions fitted to particle-simulation beams. The properties of the PARMILA code's radial particle distribution are discussed, and a broad class of probability distributions are examined to check their ability to fit it. The possibility that the PARMILA distribution is a mixture is discussed, and a fitting distribution consisting of a mixture of two generalized gamma distributions is found. An efficient algorithm to accomplish the fit is presented. Examples of the relative prediction of beam spill are given. 26 references, 18 figures, 1 table

  3. Radial expansion for spinning conformal blocks

    CERN Document Server

    Costa, Miguel S.; Penedones, João; Trevisani, Emilio

    2016-07-12

    This paper develops a method to compute any bosonic conformal block as a series expansion in the optimal radial coordinate introduced by Hogervorst and Rychkov. The method reduces to the known result when the external operators are all the same scalar operator, but it allows to compute conformal blocks for external operators with spin. Moreover, we explain how to write closed form recursion relations for the coefficients of the expansions. We study three examples of four point functions in detail: one vector and three scalars; two vectors and two scalars; two spin 2 tensors and two scalars. Finally, for the case of two external vectors, we also provide a more efficient way to generate the series expansion using the analytic structure of the blocks as a function of the scaling dimension of the exchanged operator.

  4. Hydrostatic radial bearing of centrifugal pump

    International Nuclear Information System (INIS)

    Skalicky, A.

    1976-01-01

    A hydrostatic radial pump is described characterized by the fact that part of the medium off-taken from delivery is used as a lubricating medium. Two additional bodies are placed alongside a hydrostatic bearing with coils in between them and the pump shaft; the coils have an opposite pitch. The feed channel for the hydrostatic bearing pocket is linked to delivery. The coil outlets are connected to the pump suction unit. Two rotating coils placed alongside the hydrostatic bearing will considerably simplify the communication channel design and reduce the dependence on the pump shaft deflections. The addition of another rotating coil in the close vicinity of the pump shaft or directly on the shaft further increases the efficiency. The bearing can be used in designing vertical circulating pumps for the cooling circuits of nuclear reactors. (J.B.)

  5. The radial velocity variations in IC 418

    International Nuclear Information System (INIS)

    Mendez, R.H.; Verga, A.D.

    1981-01-01

    The observations presented are part of a search for spectral and radial velocity variations among central stars of planetary nebulae and include the following new data: 1) Weak, previously undetected C III emissions are visible at 4056, 4186, 4516, 5270 and 5826 A. The famous unidentified emissions at 4485 and 4503 A were also found. 2) The He I absorptions at 4471 and 5875 A are blue-shifted relative to the nebular emissions. The same happens with Hsub(delta) and Hsub(γ), although in this case the shift can be at least partly attributed to blends with the strong He II absorptions, which are estimated to contribute about one half of the equivalent width at Hsub(delta) and Hsub(γ). 3) O III 5592 and C IV 5801, 5811 are also found in absorption. (Auth.)

  6. Anomalous Medial Branch of Radial Artery: A Rare Variant

    Directory of Open Access Journals (Sweden)

    Surbhi Wadhwa

    2016-10-01

    Full Text Available Radial artery is an important consistent vessel of the upper limb. It is a useful vascular access site for coronary procedures and its reliable anatomy has resulted in an elevation of radial forearm flaps for reconstructive surgeries of head and neck. Technical failures, in both the procedures, are mainly due to anatomical variations, such as radial loops, ectopic radial arteries or tortuosity in the vessel. We present a rare and a unique anomalous medial branch of the radial artery spiraling around the flexor carpi radialis muscle in the forearm with a high rising superficial palmar branch of radial artery. Developmentally it probably is a remanent of the normal pattern of capillary vessel maintenance and regression. Such a case is of importance for reconstructive surgeons and coronary interventionists, especially in view of its unique medial and deep course.

  7. Radial extension of drift waves in presence of velocity profiles

    International Nuclear Information System (INIS)

    Sen, S.; Weiland, J.

    1994-01-01

    The effect of a radially varying poloidal velocity field on the recently found radially extended toroidal drift waves is investigated analytically. The role of velocity curvature (υ φ '') is found to have robust effects on the radial model structure of the mode. For a positive value of the curvature (Usually found in the H-mode edges) the radial model envelope, similar to the sheared slab case, becomes fully outgoing. The mode is therefore stable. On the other hand, for a negative value of the curvature (usually observed in the L-mode edges) all the characteristics of conventional drift waves return back. The radial mode envelope reduces to a localized Gaussian shape and the mode is therefore unstable again for typical (magnetic) shear values in tokamaks. Velocity shear (υ φ ??) on the other hand is found to have rather insignificant role both in determining the radial model structure and stability

  8. Radial-Electric-Field Piezoelectric Diaphragm Pumps

    Science.gov (United States)

    Bryant, Robert G.; Working, Dennis C.; Mossi, Karla; Castro, Nicholas D.; Mane, Pooma

    2009-01-01

    In a recently invented class of piezoelectric diaphragm pumps, the electrode patterns on the piezoelectric diaphragms are configured so that the electric fields in the diaphragms have symmetrical radial (along-the-surface) components in addition to through-the-thickness components. Previously, it was accepted in the piezoelectric-transducer art that in order to produce the out-of-plane bending displacement of a diaphragm needed for pumping, one must make the electric field asymmetrical through the thickness, typically by means of electrodes placed on only one side of the piezoelectric material. In the present invention, electrodes are placed on both sides and patterned so as to produce substantial radial as well as through-the-thickness components. Moreover, unlike in the prior art, the electric field can be symmetrical through the thickness. Tests have shown in a given diaphragm that an electrode configuration according to this invention produces more displacement than does a conventional one-sided electrode pattern. The invention admits of numerous variations characterized by various degrees of complexity. Figure 1 is a simplified depiction of a basic version. As in other piezoelectric diaphragm pumps of similar basic design, the prime mover is a piezoelectric diaphragm. Application of a suitable voltage to the electrodes on the diaphragm causes it to undergo out-of-plane bending. The bending displacement pushes a fluid out of, or pulls the fluid into, a chamber bounded partly by the diaphragm. Also as in other diaphragm pumps in general, check valves ensure that the fluid flows only in through one port and only out through another port.

  9. Radial stability of anisotropic strange quark stars

    Energy Technology Data Exchange (ETDEWEB)

    Arbañil, José D.V.; Malheiro, M., E-mail: jose.arbanil@upn.pe, E-mail: malheiro@ita.br [ITA—Instituto Tecnológico de Aeronáutica—Departamento de Física, 12228-900, São José dos Campos, São Paulo (Brazil)

    2016-11-01

    The influence of the anisotropy in the equilibrium and stability of strange stars is investigated through the numerical solution of the hydrostatic equilibrium equation and the radial oscillation equation, both modified from their original version to include this effect. The strange matter inside the quark stars is described by the MIT bag model equation of state. For the anisotropy two different kinds of local anisotropic σ = p {sub t} − p {sub r} are considered, where p {sub t} and p {sub r} are respectively the tangential and the radial pressure: one that is null at the star's surface defined by p {sub r} ( R ) = 0, and one that is nonnull at the surface, namely, σ {sub s} = 0 and σ {sub s} {sub ≠} {sub 0}. In the case σ {sub s} = 0, the maximum mass value and the zero frequency of oscillation are found at the same central energy density, indicating that the maximum mass marks the onset of the instability. For the case σ {sub s} {sub ≠} {sub 0}, we show that the maximum mass point and the zero frequency of oscillation coincide in the same central energy density value only in a sequence of equilibrium configurations with the same value of σ {sub s} . Thus, the stability star regions are determined always by the condition dM / d ρ {sub c} {sub >} {sub 0} only when the tangential pressure is maintained fixed at the star surface's p {sub t} ( R ). These results are also quite important to analyze the stability of other anisotropic compact objects such as neutron stars, boson stars and gravastars.

  10. Planning Training Loads for the 400 M Hurdles in Three-Month Mesocycles using Artificial Neural Networks.

    Science.gov (United States)

    Przednowek, Krzysztof; Iskra, Janusz; Wiktorowicz, Krzysztof; Krzeszowski, Tomasz; Maszczyk, Adam

    2017-12-01

    This paper presents a novel approach to planning training loads in hurdling using artificial neural networks. The neural models performed the task of generating loads for athletes' training for the 400 meters hurdles. All the models were calculated based on the training data of 21 Polish National Team hurdlers, aged 22.25 ± 1.96, competing between 1989 and 2012. The analysis included 144 training plans that represented different stages in the annual training cycle. The main contribution of this paper is to develop neural models for planning training loads for the entire career of a typical hurdler. In the models, 29 variables were used, where four characterized the runner and 25 described the training process. Two artificial neural networks were used: a multi-layer perceptron and a network with radial basis functions. To assess the quality of the models, the leave-one-out cross-validation method was used in which the Normalized Root Mean Squared Error was calculated. The analysis shows that the method generating the smallest error was the radial basis function network with nine neurons in the hidden layer. Most of the calculated training loads demonstrated a non-linear relationship across the entire competitive period. The resulting model can be used as a tool to assist a coach in planning training loads during a selected training period.

  11. Planning Training Loads for The 400 M Hurdles in Three-Month Mesocycles Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Przednowek Krzysztof

    2017-12-01

    Full Text Available This paper presents a novel approach to planning training loads in hurdling using artificial neural networks. The neural models performed the task of generating loads for athletes’ training for the 400 meters hurdles. All the models were calculated based on the training data of 21 Polish National Team hurdlers, aged 22.25 ± 1.96, competing between 1989 and 2012. The analysis included 144 training plans that represented different stages in the annual training cycle. The main contribution of this paper is to develop neural models for planning training loads for the entire career of a typical hurdler. In the models, 29 variables were used, where four characterized the runner and 25 described the training process. Two artificial neural networks were used: a multi-layer perceptron and a network with radial basis functions. To assess the quality of the models, the leave-one-out cross-validation method was used in which the Normalized Root Mean Squared Error was calculated. The analysis shows that the method generating the smallest error was the radial basis function network with nine neurons in the hidden layer. Most of the calculated training loads demonstrated a non-linear relationship across the entire competitive period. The resulting model can be used as a tool to assist a coach in planning training loads during a selected training period.

  12. EEG signal classification using PSO trained RBF neural network for epilepsy identification

    Directory of Open Access Journals (Sweden)

    Sandeep Kumar Satapathy

    Full Text Available The electroencephalogram (EEG is a low amplitude signal generated in the brain, as a result of information flow during the communication of several neurons. Hence, careful analysis of these signals could be useful in understanding many human brain disorder diseases. One such disease topic is epileptic seizure identification, which can be identified via a classification process of the EEG signal after preprocessing with the discrete wavelet transform (DWT. To classify the EEG signal, we used a radial basis function neural network (RBFNN. As shown herein, the network can be trained to optimize the mean square error (MSE by using a modified particle swarm optimization (PSO algorithm. The key idea behind the modification of PSO is to introduce a method to overcome the problem of slow searching in and around the global optimum solution. The effectiveness of this procedure was verified by an experimental analysis on a benchmark dataset which is publicly available. The result of our experimental analysis revealed that the improvement in the algorithm is significant with respect to RBF trained by gradient descent and canonical PSO. Here, two classes of EEG signals were considered: the first being an epileptic and the other being non-epileptic. The proposed method produced a maximum accuracy of 99% as compared to the other techniques. Keywords: Electroencephalography, Radial basis function neural network, Particle swarm optimization, Discrete wavelet transform, Machine learning

  13. Adaptive neural networks control for camera stabilization with active suspension system

    Directory of Open Access Journals (Sweden)

    Feng Zhao

    2015-08-01

    Full Text Available The camera always suffers from image instability on the moving vehicle due to unintentional vibrations caused by road roughness. This article presents an adaptive neural network approach mixed with linear quadratic regulator control for a quarter-car active suspension system to stabilize the image captured area of the camera. An active suspension system provides extra force through the actuator which allows it to suppress vertical vibration of sprung mass. First, to deal with the road disturbance and the system uncertainties, radial basis function neural network is proposed to construct the map between the state error and the compensation component, which can correct the optimal state-feedback control law. The weights matrix of radial basis function neural network is adaptively tuned online. Then, the closed-loop stability and asymptotic convergence performance is guaranteed by Lyapunov analysis. Finally, the simulation results demonstrate that the proposed controller effectively suppresses the vibration of the camera and enhances the stabilization of the entire camera, where different excitations are considered to validate the system performance.

  14. Sparse Reconstruction of Electric Fields from Radial Magnetic Data

    International Nuclear Information System (INIS)

    Yeates, Anthony R.

    2017-01-01

    Accurate estimates of the horizontal electric field on the Sun’s visible surface are important not only for estimating the Poynting flux of magnetic energy into the corona but also for driving time-dependent magnetohydrodynamic models of the corona. In this paper, a method is developed for estimating the horizontal electric field from a sequence of radial-component magnetic field maps. This problem of inverting Faraday’s law has no unique solution. Unfortunately, the simplest solution (a divergence-free electric field) is not realistically localized in regions of nonzero magnetic field, as would be expected from Ohm’s law. Our new method generates instead a localized solution, using a basis pursuit algorithm to find a sparse solution for the electric field. The method is shown to perform well on test cases where the input magnetic maps are flux balanced in both Cartesian and spherical geometries. However, we show that if the input maps have a significant imbalance of flux—usually arising from data assimilation—then it is not possible to find a localized, realistic, electric field solution. This is the main obstacle to driving coronal models from time sequences of solar surface magnetic maps.

  15. An analysis of the variable radial velocity of alpha cygni

    International Nuclear Information System (INIS)

    Lucy, L.B.

    1976-01-01

    On the basis of 447 radial velocities obtained at the Lick Observatory by Paddock in the years 1927--1935, an attempt is made to discover the nature of the semiregular variability of α Cygni (A2 Ia). Harmonic analysis of the 144 velocities obtained in 1931 suggests that this variability is due to the simultaneous excitation of many discrete pulsation modes. The amplitudes and periods of these modes are then determined by least-squares fitting to all the data, and a final solution is obtained that comprises 16 terms with periods from 6.9 to 100.8 days. All terms are found to have highly significant amplitudes, and most terms also pass a test of the stability of their amplitudes and phases. Reasons are given for believing that most terms represent nonradial oscillations, and this leads to the suggestion that the resulting surface motions are to be identified with macroturbulence. An argument is also given for believing that the pulsational instability persists down to periods at which atmospheric oscillations become progressive, and this leads to the suggestion that such waves are observed as microturbulence and give rise to the observed mass loss. The importance of further monitoring of the variability of supergiants is stressed

  16. Sparse Reconstruction of Electric Fields from Radial Magnetic Data

    Energy Technology Data Exchange (ETDEWEB)

    Yeates, Anthony R. [Department of Mathematical Sciences, Durham University, Durham, DH1 3LE (United Kingdom)

    2017-02-10

    Accurate estimates of the horizontal electric field on the Sun’s visible surface are important not only for estimating the Poynting flux of magnetic energy into the corona but also for driving time-dependent magnetohydrodynamic models of the corona. In this paper, a method is developed for estimating the horizontal electric field from a sequence of radial-component magnetic field maps. This problem of inverting Faraday’s law has no unique solution. Unfortunately, the simplest solution (a divergence-free electric field) is not realistically localized in regions of nonzero magnetic field, as would be expected from Ohm’s law. Our new method generates instead a localized solution, using a basis pursuit algorithm to find a sparse solution for the electric field. The method is shown to perform well on test cases where the input magnetic maps are flux balanced in both Cartesian and spherical geometries. However, we show that if the input maps have a significant imbalance of flux—usually arising from data assimilation—then it is not possible to find a localized, realistic, electric field solution. This is the main obstacle to driving coronal models from time sequences of solar surface magnetic maps.

  17. Evaporation Limited Radial Capillary Penetration in Porous Media.

    Science.gov (United States)

    Liu, Mingchao; Wu, Jian; Gan, Yixiang; Hanaor, Dorian A H; Chen, C Q

    2016-09-27

    The capillary penetration of fluids in thin porous layers is of fundamental interest in nature and various industrial applications. When capillary flows occur in porous media, the extent of penetration is known to increase with the square root of time following the Lucas-Washburn law. In practice, volatile liquid evaporates at the surface of porous media, which restricts penetration to a limited region. In this work, on the basis of Darcy's law and mass conservation, a general theoretical model is developed for the evaporation-limited radial capillary penetration in porous media. The presented model predicts that evaporation decreases the rate of fluid penetration and limits it to a critical radius. Furthermore, we construct a unified phase diagram that describes the limited penetration in an annular porous medium, in which the boundaries of outward and inward liquid are predicted quantitatively. It is expected that the proposed theoretical model will advance the understanding of penetration dynamics in porous media and facilitate the design of engineered porous architectures.

  18. Radial-arrayed rotary electrification for high performance triboelectric generator.

    Science.gov (United States)

    Zhu, Guang; Chen, Jun; Zhang, Tiejun; Jing, Qingshen; Wang, Zhong Lin

    2014-03-04

    Harvesting mechanical energy is an important route in obtaining cost-effective, clean and sustainable electric energy. Here we report a two-dimensional planar-structured triboelectric generator on the basis of contact electrification. The radial arrays of micro-sized sectors on the contact surfaces enable a high output power of 1.5 W (area power density of 19 mW cm(-2)) at an efficiency of 24%. The triboelectric generator can effectively harness various ambient motions, including light wind, tap water flow and normal body movement. Through a power management circuit, a triboelectric-generator-based power-supplying system can provide a constant direct-current source for sustainably driving and charging commercial electronics, immediately demonstrating the feasibility of the triboelectric generator as a practical power source. Given exceptional power density, extremely low cost and unique applicability resulting from distinctive mechanism and structure, the triboelectric generator can be applied not only to self-powered electronics but also possibly to power generation at a large scale.

  19. A New Filtering Algorithm Utilizing Radial Velocity Measurement

    Institute of Scientific and Technical Information of China (English)

    LIU Yan-feng; DU Zi-cheng; PAN Quan

    2005-01-01

    Pulse Doppler radar measurements consist of range, azimuth, elevation and radial velocity. Most of the radar tracking algorithms in engineering only utilize position measurement. The extended Kalman filter with radial velocity measureneut is presented, then a new filtering algorithm utilizing radial velocity measurement is proposed to improve tracking results and the theoretical analysis is also given. Simulation results of the new algorithm, converted measurement Kalman filter, extended Kalman filter are compared. The effectiveness of the new algorithm is verified by simulation results.

  20. Vitreous veils and radial lattice in Marshall syndrome.

    Science.gov (United States)

    Brubaker, Jacob W; Mohney, Brian G; Pulido, Jose S; Babovic-Vuksanovic, Dusica

    2008-12-01

    To report the findings of membranous vitreous veils and radial lattice in a child with Marshall syndrome. Observational case report. Retrospective review of medical records and fundus photograph of a 6-year-old boy with Marshall syndrome. Vitreoretinal findings were significant for bilateral membranous vitreous veils and radial lattice degeneration. This case demonstrates the occurrence of vitreous veils and radial lattice degeneration in patients with Marshall syndrome.

  1. Neural Network Based Maximum Power Point Tracking Control with Quadratic Boost Converter for PMSG—Wind Energy Conversion System

    Directory of Open Access Journals (Sweden)

    Ramji Tiwari

    2018-02-01

    Full Text Available This paper proposes an artificial neural network (ANN based maximum power point tracking (MPPT control strategy for wind energy conversion system (WECS implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O method and Back propagation network (BPN method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC. The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.

  2. Radioactive Waste Management Basis

    International Nuclear Information System (INIS)

    Perkins, B.K.

    2009-01-01

    The purpose of this Radioactive Waste Management Basis is to describe the systematic approach for planning, executing, and evaluating the management of radioactive waste at LLNL. The implementation of this document will ensure that waste management activities at LLNL are conducted in compliance with the requirements of DOE Order 435.1, Radioactive Waste Management, and the Implementation Guide for DOE Manual 435.1-1, Radioactive Waste Management Manual. Technical justification is provided where methods for meeting the requirements of DOE Order 435.1 deviate from the DOE Manual 435.1-1 and Implementation Guide.

  3. The effect of texture on the shaft surface on the sealing performance of radial lip seals

    Science.gov (United States)

    Guo, Fei; Jia, XiaoHong; Gao, Zhi; Wang, YuMing

    2014-07-01

    On the basis of elastohydrodynamic model, the present study numerically analyzes the effect of various microdimple texture shapes, namely, circular, square, oriented isosceles triangular, on the pumping rate and the friction torque of radial lip seals, and determines the microdimple texture shape that can produce positive pumping rate. The area ratio, depth and shape dimension of a single texture are the most important geometric parameters which influence the tribological performance. According to the selected texture shape, parameter analysis is conducted to determine the optimal combination for the above three parameters. Simultaneously, the simulated performances of radial lip seal with texture on the shaft surface are compared with those of the conventional lip seal without any texture on the shaft surface.

  4. Higher‐order mode absorption measurement of X-band choke-mode cavities in a radial line structure

    Energy Technology Data Exchange (ETDEWEB)

    Zha, Hao [Department of Engineering Physics, Tsinghua University, Beijing CN-100086 (China); Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing (China); The European Organization for Nuclear Research, Geneva CH-1211 (Switzerland); Shi, Jiaru, E-mail: shij@mail.tsinghua.edu.cn [Department of Engineering Physics, Tsinghua University, Beijing CN-100086 (China); Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing (China); The European Organization for Nuclear Research, Geneva CH-1211 (Switzerland); Wu, Xiaowei; Chen, Huaibi [Department of Engineering Physics, Tsinghua University, Beijing CN-100086 (China); Key Laboratory of Particle and Radiation Imaging, Tsinghua University, Ministry of Education, Beijing (China)

    2016-04-01

    An experiment is presented to study the higher-order mode (HOM) suppression of X-band choke-mode structures with a vector network analyzer (VNA). Specific radial line disks were built to test the reflection from the corresponding damping load and different choke geometries. The mismatch between the radial lines and the VNA was calibrated through a special multi-short-load calibration method. The measured reflections of different choke geometries showed good agreement with the theoretical calculations and verified the HOM absorption feature of each geometric design.

  5. Higher‐order mode absorption measurement of X-band choke-mode cavities in a radial line structure

    International Nuclear Information System (INIS)

    Zha, Hao; Shi, Jiaru; Wu, Xiaowei; Chen, Huaibi

    2016-01-01

    An experiment is presented to study the higher-order mode (HOM) suppression of X-band choke-mode structures with a vector network analyzer (VNA). Specific radial line disks were built to test the reflection from the corresponding damping load and different choke geometries. The mismatch between the radial lines and the VNA was calibrated through a special multi-short-load calibration method. The measured reflections of different choke geometries showed good agreement with the theoretical calculations and verified the HOM absorption feature of each geometric design.

  6. Pseudarthrosis of radial shaft with dislocation of heads of radial and ulnar bones (case report

    Directory of Open Access Journals (Sweden)

    M. E. Puseva

    2013-01-01

    Full Text Available The authors presented a rare clinical case - the injury of forearm complicated by the formation of the pseudarthrosis of the radial shaft in combination with old dislocation of heads the radius and ulna. The differentiated approach to the choice of surgical tactics was proposed, which consists of several consistent stages: taking free autotransplant from the crest of iliac bone, resection of pseudarthrosis of radius with replacement of the bone defect by the graft for restoration of anatomic length, conducting combined strained osteosynthesis and elimination of dislocation of a head of radial and ulnar bones by transosseous osteosynthesis. The chosen treatment strategy allowed to restore the anatomy and function of the upper extremity.

  7. Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

    Science.gov (United States)

    Xia, Kewei; Huo, Wei

    2016-05-01

    This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  8. Adaptive online state-of-charge determination based on neuro-controller and neural network

    Energy Technology Data Exchange (ETDEWEB)

    Shen Yanqing, E-mail: network_hawk@126.co [Department of Automation, Chongqing Industry Polytechnic College, Jiulongpo District, Chongqing 400050 (China)

    2010-05-15

    This paper presents a novel approach using adaptive artificial neural network based model and neuro-controller for online cell State of Charge (SOC) determination. Taking cell SOC as model's predictive control input unit, radial basis function neural network, which can adjust its structure to prediction error with recursive least square algorithm, is used to simulate battery system. Besides that, neuro-controller based on Back-Propagation Neural Network (BPNN) and modified PID controller is used to decide the control input of battery system, i.e., cell SOC. Finally this algorithm is applied for the SOC determination of lead-acid batteries, and results of lab tests on physical cells, compared with model prediction, are presented. Results show that the ANN based battery system model adaptively simulates battery system with great accuracy, and the predicted SOC simultaneously converges to the real value quickly within the error of +-1 as time goes on.

  9. Prediction of Force Measurements of a Microbend Sensor Based on an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Kemal Fidanboylu

    2009-09-01

    Full Text Available Artificial neural network (ANN based prediction of the response of a microbend fiber optic sensor is presented. To the best of our knowledge no similar work has been previously reported in the literature. Parallel corrugated plates with three deformation cycles, 6 mm thickness of the spacer material and 16 mm mechanical periodicity between deformations were used in the microbend sensor. Multilayer Perceptron (MLP with different training algorithms, Radial Basis Function (RBF network and General Regression Neural Network (GRNN are used as ANN models in this work. All of these models can predict the sensor responses with considerable errors. RBF has the best performance with the smallest mean square error (MSE values of training and test results. Among the MLP algorithms and GRNN the Levenberg-Marquardt algorithm has good results. These models successfully predict the sensor responses, hence ANNs can be used as useful tool in the design of more robust fiber optic sensors.

  10. STAND-LEVEL PROGNOSIS OF EUCALYPTUS CLONES USING ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Mayra Luiza Marques da Silva Binoti

    2015-03-01

    Full Text Available The objective of this study was to train, implement and evaluate the efficiency of artificial neural networks (ANN to perform production prognosis of even-aged stands of eucalyptus clones. The data used were from plantations located in southern Bahia, totaling about 2,000 acres of forest. Numeric variables, such as age, basal area, volume and categorical variables, such as soil class texture, spacing, land relief, project and clone were used. The data were randomly divided into two groups: training (80% and generalization (20%. Three types of networks were trained: perceptron, multilayer perceptron networks and radial basis function. The RNA that showed the best performance in training and generalization were selected to perform the prognosis with data from the first forest inventory. We conclude that the RNA had satisfactory results, showing the potential and applicability of the technique in solving measurement and forest management problems.

  11. Predicting wettability behavior of fluorosilica coated metal surface using optimum neural network

    Science.gov (United States)

    Taghipour-Gorjikolaie, Mehran; Valipour Motlagh, Naser

    2018-02-01

    The interaction between variables, which are effective on the surface wettability, is very complex to predict the contact angles and sliding angles of liquid drops. In this paper, in order to solve this complexity, artificial neural network was used to develop reliable models for predicting the angles of liquid drops. Experimental data are divided into training data and testing data. By using training data and feed forward structure for the neural network and using particle swarm optimization for training the neural network based models, the optimum models were developed. The obtained results showed that regression index for the proposed models for the contact angles and sliding angles are 0.9874 and 0.9920, respectively. As it can be seen, these values are close to unit and it means the reliable performance of the models. Also, it can be inferred from the results that the proposed model have more reliable performance than multi-layer perceptron and radial basis function based models.

  12. Numerical simulation of liquid-metal-flows in radial-toroidal-radial bends

    International Nuclear Information System (INIS)

    Molokov, S.; Buehler, L.

    1993-09-01

    Magnetohydrodynamic flows in a U-bend and right-angle bend are considered with reference to the radial-toroidal-radial concept of a self-cooled liquid-metal blanket. The ducts composing bends have rectangular cross-section. The applied magnetic field is aligned with the toroidal duct and perpendicular to the radial ones. At high Hartmann number the flow region is divided into cores and boundary layers of different types. The magnetohydrodynamic equations are reduced to a system of partial differential equations governing wall electric potentials and the core pressure. The system is solved numerically by two different methods. The first method is iterative with iteration between wall potential and the core pressure. The second method is a general one for the solution of the core flow equations in curvilinear coordinates generated by channel geometry and magnetic field orientation. Results obtained are in good agreement. They show, that the 3D-pressure drop of MHD flows in a U-bend is not a critical issue for blanket applications. (orig./HP) [de

  13. Fuel radial design using Path Relinking; Diseno radial de combustible usando Path Relinking

    Energy Technology Data Exchange (ETDEWEB)

    Campos S, Y. [ININ, 52750 La Marquesa, Estado de Mexico (Mexico)

    2007-07-01

    The present work shows the obtained results when implementing the combinatory optimization technique well-known as Path Re linking (Re-linkage of Trajectories), to the problem of the radial design of nuclear fuel assemblies, for boiling water reactors (BWR Boiling Water Reactor by its initials in English), this type of reactors is those that are used in the Laguna Verde Nucleo electric Central, Veracruz. As in any other electric power generation plant of that make use of some fuel to produce heat and that it needs each certain time (from 12 to 14 months) to make a supply of the same one, because this it wears away or it burns, in the nucleolectric plants to this activity is denominated fuel reload. In this reload different activities intervene, among those which its highlight the radial and axial designs of fuel assemblies, the patterns of control rods and the multi cycles study, each one of these stages with their own complexity. This work was limited to study in independent form the radial design, without considering the other activities. These phases are basic for the fuel reload design and of reactor operation strategies. (Author)

  14. Design of radial reinforcement for prestressed concrete containments

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Shen, E-mail: swang@bechtel.com [Bechtel Power Corporation, 5275 Westview Drive, BP2-2C3, Frederick, MD 21703 (United States); Munshi, Javeed A., E-mail: jamunshi@bechtel.com [Bechtel Power Corporation, 5275 Westview Drive, BP2-2C3, Frederick, MD 21703 (United States)

    2013-02-15

    Highlights: ► A rigorous formulae is proposed to calculate radial stress within prestressed concrete containments. ► The proposed method is validated by finite element analysis in an illustrative practical example. ► A partially prestressed condition is more critical than a fully prestressed condition for radial tension. ► Practical design consideration is provided for detailing of radial reinforcement. -- Abstract: Nuclear containments are critical components for safety of nuclear power plants. Failure can result in catastrophic safety consequences as a result of leakage of radiation. Prestressed concrete containments have been used in large nuclear power plants with significant design internal pressure. These containments are generally reinforced with prestressing tendons in the circumferential (hoop) and meridional (vertical) directions. The curvature effect of the tendons introduces radial tensile stresses in the concrete shell which are generally neglected in the design of such structures. It is assumed that such tensile radial stresses are small as such no radial reinforcement is provided for this purpose. But recent instances of significant delaminations in Crystal River Unit 3 in Florida have elevated the need for reevaluation of the radial tension issue in prestressed containment. Note that currently there are no well accepted industry standards for design and detailing of radial reinforcement. This paper discusses the issue of radial tension in prestressed cylindrical and dome shaped structures and proposes formulae to calculate radial stresses. A practical example is presented to illustrate the use of the proposed method which is then verified by using state of art finite element analysis. This paper also provides some practical design consideration for detailing of radial reinforcement in prestressed containments.

  15. ITER technical basis

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2002-01-01

    Following on from the Final Report of the EDA(DS/21), and the summary of the ITER Final Design report(DS/22), the technical basis gives further details of the design of ITER. It is in two parts. The first, the Plant Design specification, summarises the main constraints on the plant design and operation from the viewpoint of engineering and physics assumptions, compliance with safety regulations, and siting requirements and assumptions. The second, the Plant Description Document, describes the physics performance and engineering characteristics of the plant design, illustrates the potential operational consequences foe the locality of a generic site, gives the construction, commissioning, exploitation and decommissioning schedule, and reports the estimated lifetime costing based on data from the industry of the EDA parties.

  16. ITER technical basis

    International Nuclear Information System (INIS)

    2002-01-01

    Following on from the Final Report of the EDA(DS/21), and the summary of the ITER Final Design report(DS/22), the technical basis gives further details of the design of ITER. It is in two parts. The first, the Plant Design specification, summarises the main constraints on the plant design and operation from the viewpoint of engineering and physics assumptions, compliance with safety regulations, and siting requirements and assumptions. The second, the Plant Description Document, describes the physics performance and engineering characteristics of the plant design, illustrates the potential operational consequences foe the locality of a generic site, gives the construction, commissioning, exploitation and decommissioning schedule, and reports the estimated lifetime costing based on data from the industry of the EDA parties

  17. Investigating changes in brain network properties in HIV-associated neurocognitive disease (HAND) using mutual connectivity analysis (MCA)

    Science.gov (United States)

    Abidin, Anas Zainul; D'Souza, Adora M.; Nagarajan, Mahesh B.; Wismüller, Axel

    2016-03-01

    About 50% of subjects infected with HIV present deficits in cognitive domains, which are known collectively as HIV associated neurocognitive disorder (HAND). The underlying synaptodendritic damage can be captured using resting state functional MRI, as has been demonstrated by a few earlier studies. Such damage may induce topological changes of brain connectivity networks. We test this hypothesis by capturing the functional interdependence of 90 brain network nodes using a Mutual Connectivity Analysis (MCA) framework with non-linear time series modeling based on Generalized Radial Basis function (GRBF) neural networks. The network nodes are selected based on the regions defined in the Automated Anatomic Labeling (AAL) atlas. Each node is represented by the average time series of the voxels of that region. The resulting networks are then characterized using graph-theoretic measures that quantify various network topology properties at a global as well as at a local level. We tested for differences in these properties in network graphs obtained for 10 subjects (6 male and 4 female, 5 HIV+ and 5 HIV-). Global network properties captured some differences between these subject cohorts, though significant differences were seen only with the clustering coefficient measure. Local network properties, such as local efficiency and the degree of connections, captured significant differences in regions of the frontal lobe, precentral and cingulate cortex amongst a few others. These results suggest that our method can be used to effectively capture differences occurring in brain network connectivity properties revealed by resting-state functional MRI in neurological disease states, such as HAND.

  18. Observational hints of radial migration in disc galaxies from CALIFA

    NARCIS (Netherlands)

    Ruiz-Lara, T.; Pérez, I.; Florido, E.; Sánchez-Blázquez, P.; Méndez-Abreu, J.; Sánchez-Menguiano, L.; Sánchez, S. F.; Lyubenova, M.; Falcón-Barroso, J.; van de Ven, G.; Marino, R. A.; de Lorenzo-Cáceres, A.; Catalán-Torrecilla, C.; Costantin, L.; Bland-Hawthorn, J.; Galbany, L.; García-Benito, R.; Husemann, B.; Kehrig, C.; Márquez, I.; Mast, D.; Walcher, C. J.; Zibetti, S.; Ziegler, B.

    2017-01-01

    Context. According to numerical simulations, stars are not always kept at their birth galactocentric distances but they have a tendency to migrate. The importance of this radial migration in shaping galactic light distributions is still unclear. However, if radial migration is indeed important,

  19. Radial supports of face motors with slack compensation

    Energy Technology Data Exchange (ETDEWEB)

    Kuznetsova, I I; Gelman, A B; Krekina, T V

    1982-01-01

    The design of a radial support of a face motor with slack compensation is described, and gives the results of field tests which confirm the performance capacity of the experimental support both from the viewpoint of durability, and in relation to preventing radial slack of the face motor shaft.

  20. Radial Color Gradient in a Globular Cluster 1. M68

    Directory of Open Access Journals (Sweden)

    Sukyoung Yi

    1990-12-01

    Full Text Available Stars in M68 from the observed color-magnitude diagrams with CCD were integrated to find any radial gradient. The result shows that M68 has a slightly bluer core. The main cause of these calculated radial color variations seems to come from the random distribution of giants.

  1. Modelling and analysis of radial thermal stresses and temperature ...

    African Journals Online (AJOL)

    A theoretical investigation has been undertaken to study operating temperatures, heat fluxes and radial thermal stresses in the valves of a modern diesel engine with and without air-cavity. Temperatures, heat fluxes and radial thermal stresses were measured theoretically for both cases under all four thermal loading ...

  2. Radiographic study of distal radial physeal closure in thoroughbred horses

    International Nuclear Information System (INIS)

    Vulcano, L.C.; Mamprim, M.J.; Muniz, L.M.R.; Moreira, A.F.; Luna, S.P.L.

    1997-01-01

    Monthly radiography was performed to study distal radial physeal closure in ten male and ten female Throughbred horses. The height, thoracic circumference and metacarpus circumference were also measured, Distal radial physeal closure time was sooner in females than males, and took 701 +/- 37 and 748 +/- 55 days respectively

  3. Radial Velocities of 41 Kepler Eclipsing Binaries

    Science.gov (United States)

    Matson, Rachel A.; Gies, Douglas R.; Guo, Zhao; Williams, Stephen J.

    2017-12-01

    Eclipsing binaries are vital for directly determining stellar parameters without reliance on models or scaling relations. Spectroscopically derived parameters of detached and semi-detached binaries allow us to determine component masses that can inform theories of stellar and binary evolution. Here we present moderate resolution ground-based spectra of stars in close binary systems with and without (detected) tertiary companions observed by NASA’s Kepler mission and analyzed for eclipse timing variations. We obtain radial velocities and spectroscopic orbits for five single-lined and 35 double-lined systems, and confirm one false positive eclipsing binary. For the double-lined spectroscopic binaries, we also determine individual component masses and examine the mass ratio {M}2/{M}1 distribution, which is dominated by binaries with like-mass pairs and semi-detached classical Algol systems that have undergone mass transfer. Finally, we constrain the mass of the tertiary component for five double-lined binaries with previously detected companions.

  4. Nonlinear radial propagation of drift wave turbulence

    International Nuclear Information System (INIS)

    Prakash, M.

    1985-01-01

    We study the linear and the nonlinear radial propagation of drift wave energy in an inhomogeneous plasma. The drift mode excited in such a plasma is dispersive in nature. The drift wave energy spreads out symmetrically along the direction of inhomogeneity with a finite group velocity. To study the effect of the nonlinear coupling on the propagation of energy in a collision free plasma, we solve the Hasegawa-Mima equation as a mixed initial boundary-value problem. The solutions of the linearized equation are used to check the reliability of our numerical calculations. Additional checks are also performed on the invariants of the system. Our results reveal that a pulse gets distorted as it propagates through the medium. The peak of the pulse propagates with a finite velocity that depends on the amplitude of the initial pulse. The polarity of propagation depends on the initial parameters of the pulse. We have also studied drift wave propagation in a resistive plasma. The Hasegawa-Wakatani equations are used to investigate this problem

  5. THE NIRSPEC ULTRACOOL DWARF RADIAL VELOCITY SURVEY

    International Nuclear Information System (INIS)

    Blake, Cullen H.; Charbonneau, David; White, Russel J.

    2010-01-01

    We report the results of an infrared Doppler survey designed to detect brown dwarf and giant planetary companions to a magnitude-limited sample of ultracool dwarfs. Using the NIRSPEC spectrograph on the Keck II telescope, we obtained approximately 600 radial velocity (RV) measurements over a period of six years of a sample of 59 late-M and L dwarfs spanning spectral types M8/L0 to L6. A subsample of 46 of our targets has been observed on three or more epochs. We rely on telluric CH 4 absorption features in Earth's atmosphere as a simultaneous wavelength reference and exploit the rich set of CO absorption features found in the K-band spectra of cool stars and brown dwarfs to measure RVs and projected rotational velocities. For a bright, slowly rotating M dwarf standard we demonstrate an RV precision of 50 m s -1 and for slowly rotating L dwarfs we achieve a typical RV precision of approximately 200 m s -1 . This precision is sufficient for the detection of close-in giant planetary companions to mid-L dwarfs as well as more equal mass spectroscopic binary systems with small separations (a +0.7 -0.6 Gyr, similar to that of nearby sun-like stars. We simulate the efficiency with which we detect spectroscopic binaries and find that the rate of tight (a +8.6 -1.6 %, consistent with recent estimates in the literature of a tight binary fraction of 3%-4%.

  6. Vortex Ring Dynamics in Radially Confined Domains

    Science.gov (United States)

    Stewart, Kelley; Niebel, Casandra; Jung, Sunghwan; Vlachos, Pavlos

    2010-11-01

    Vortex ring dynamics have been studied extensively in semi-infinite quiescent volumes. However, very little is known about vortex-ring formation in wall-bounded domains where vortex wall interaction will affect both the vortex ring pinch-off and propagation velocity. This study addresses this limitation and studies vortex formation in radially confined domains to analyze the affect of vortex-ring wall interaction on the formation and propagation of the vortex ring. Vortex rings were produced using a pneumatically driven piston cylinder arrangement and were ejected into a long cylindrical tube which defined the confined downstream domain. A range of confinement domains were studied with varying confinement diameters Velocity field measurements were performed using planar Time Resolved Digital Particle Image Velocimetry (TRDPIV) and were processed using an in-house developed cross-correlation PIV algorithm. The experimental analysis was used to facilitate the development of a theoretical model to predict the variations in vortex ring circulation over time within confined domains.

  7. Radial frequency stimuli and sine-wave gratings seem to be processed by distinct contrast brain mechanisms

    Directory of Open Access Journals (Sweden)

    M.L.B. Simas

    2005-03-01

    Full Text Available An assumption commonly made in the study of visual perception is that the lower the contrast threshold for a given stimulus, the more sensitive and selective will be the mechanism that processes it. On the basis of this consideration, we investigated contrast thresholds for two classes of stimuli: sine-wave gratings and radial frequency stimuli (i.e., j0 targets or stimuli modulated by spherical Bessel functions. Employing a suprathreshold summation method, we measured the selectivity of spatial and radial frequency filters using either sine-wave gratings or j0 target contrast profiles at either 1 or 4 cycles per degree of visual angle (cpd, as the test frequencies. Thus, in a forced-choice trial, observers chose between a background spatial (or radial frequency alone and the given background stimulus plus the test frequency (1 or 4 cpd sine-wave grating or radial frequency. Contrary to our expectations, the results showed elevated thresholds (i.e., inhibition for sine-wave gratings and decreased thresholds (i.e., summation for radial frequencies when background and test frequencies were identical. This was true for both 1- and 4-cpd test frequencies. This finding suggests that sine-wave gratings and radial frequency stimuli are processed by different quasi-linear systems, one working at low luminance and contrast level (sine-wave gratings and the other at high luminance and contrast levels (radial frequency stimuli. We think that this interpretation is consistent with distinct foveal only and foveal-parafoveal mechanisms involving striate and/or other higher visual areas (i.e., V2 and V4.

  8. Numerical study of the shape parameter dependence of the local radial point interpolation method in linear elasticity.

    Science.gov (United States)

    Moussaoui, Ahmed; Bouziane, Touria

    2016-01-01

    The method LRPIM is a Meshless method with properties of simple implementation of the essential boundary conditions and less costly than the moving least squares (MLS) methods. This method is proposed to overcome the singularity associated to polynomial basis by using radial basis functions. In this paper, we will present a study of a 2D problem of an elastic homogenous rectangular plate by using the method LRPIM. Our numerical investigations will concern the influence of different shape parameters on the domain of convergence,accuracy and using the radial basis function of the thin plate spline. It also will presents a comparison between numerical results for different materials and the convergence domain by precising maximum and minimum values as a function of distribution nodes number. The analytical solution of the deflection confirms the numerical results. The essential points in the method are: •The LRPIM is derived from the local weak form of the equilibrium equations for solving a thin elastic plate.•The convergence of the LRPIM method depends on number of parameters derived from local weak form and sub-domains.•The effect of distributions nodes number by varying nature of material and the radial basis function (TPS).

  9. Probabilistic neural network algorithm for using radon emanations as an earthquake precursor

    International Nuclear Information System (INIS)

    Gupta, Dhawal; Shahani, D.T.

    2014-01-01

    The investigation throughout the world in past two decades provides evidence which indicate that significance variation of radon and other soil gases occur in association with major geophysical events such as earthquake. The traditional statistical algorithm includes regression to remove the effect of the meteorological parameters from the raw radon and anomalies are calculated either taking the periodicity in seasonal variations or periodicity computed using Fast Fourier Transform. In case of neural networks the regression step is avoided. A neural network model can be found which can learn the behavior of radon with respect to meteorological parameter in order that changing emission patterns may be adapted to by the model on its own. The output of this neural model is the estimated radon values. This estimated radon value is used to decide whether anomalous behavior of radon has occurred and a valid precursor may be identified. The neural network model developed using Radial Basis function network gave a prediction rate of 87.7%. The same was accompanied by huge false alarms. The present paper deals with improved neural network algorithm using Probabilistic Neural Networks that requires neither an explicit step of regression nor use of any specific period. This neural network model reduces the false alarms to zero and gave same prediction rate as RBF networks. (author)

  10. Neural network for optimal capacitor placement and its impact on power quality in electric distribution systems

    International Nuclear Information System (INIS)

    Mohamed, A.A.E.S.

    2013-01-01

    Capacitors are widely installed in distribution systems for reactive power compensation to achieve power and energy loss reduction, voltage regulation and system capacity release. The extent of these benefits depends greatly on how the capacitors are placed on the system. The problem of how to place capacitors on the system such that these benefits are achieved and maximized against the cost associated with the capacitor placement is termed the general capacitor placement problem. The capacitor placement problem has been formulated as the maximization of the savings resulted from reduction in both peak power and energy losses considering capacitor installation cost and maintaining the buses voltage within acceptable limits. After an appropriate analysis, the optimization problem was formulated in a quadratic form. For solving capacitor placement a new combinatorial heuristic and quadratic programming technique has been presented and applied in the MATLAB software. The proposed strategy was applied on two different radial distribution feeders. The results have been compared with previous works. The comparison showed the validity and the effectiveness of this strategy. Secondly, two artificial intelligence techniques for predicting the capacitor switching state in radial distribution feeders have been investigated; one is based on basis Radial Basis Neural Network (RBNN) and the other is based on Adaptive Neuro-Fuzzy Inference System (ANFIS). The ANFIS technique gives better results with a minimum total error compared to RBNN. The learning duration of ANFIS was very short than the neural network case. It implied that ANFIS reaches to the target faster than neural network. Thirdly, an artificial intelligence (RBNN) approach for estimation of transient overvoltage during capacitor switching has been studied. The artificial intelligence approach estimated the transient overvoltages with a minimum error in a short computational time. Finally, a capacitor switching

  11. File access prediction using neural networks.

    Science.gov (United States)

    Patra, Prashanta Kumar; Sahu, Muktikanta; Mohapatra, Subasish; Samantray, Ronak Kumar

    2010-06-01

    One of the most vexing issues in design of a high-speed computer is the wide gap of access times between the memory and the disk. To solve this problem, static file access predictors have been used. In this paper, we propose dynamic file access predictors using neural networks to significantly improve upon the accuracy, success-per-reference, and effective-success-rate-per-reference by using neural-network-based file access predictor with proper tuning. In particular, we verified that the incorrect prediction has been reduced from 53.11% to 43.63% for the proposed neural network prediction method with a standard configuration than the recent popularity (RP) method. With manual tuning for each trace, we are able to improve upon the misprediction rate and effective-success-rate-per-reference using a standard configuration. Simulations on distributed file system (DFS) traces reveal that exact fit radial basis function (RBF) gives better prediction in high end system whereas multilayer perceptron (MLP) trained with Levenberg-Marquardt (LM) backpropagation outperforms in system having good computational capability. Probabilistic and competitive predictors are the most suitable for work stations having limited resources to deal with and the former predictor is more efficient than the latter for servers having maximum system calls. Finally, we conclude that MLP with LM backpropagation algorithm has better success rate of file prediction than those of simple perceptron, last successor, stable successor, and best k out of m predictors.

  12. RADIAL VELOCITY MONITORING OF KEPLER HEARTBEAT STARS

    Energy Technology Data Exchange (ETDEWEB)

    Shporer, Avi [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109 (United States); Fuller, Jim [TAPIR, Walter Burke Institute for Theoretical Physics, Mailcode 350-17, Caltech, Pasadena, CA 91125 (United States); Isaacson, Howard [Department of Astronomy, University of California, Berkeley CA 94720 (United States); Hambleton, Kelly; Prša, Andrej [Department of Astrophysics and Planetary Science, Villanova University, 800 East Lancaster Avenue, Villanova, PA 19085 (United States); Thompson, Susan E. [NASA Ames Research Center, Moffett Field, CA 94035 (United States); Kurtz, Donald W. [Jeremiah Horrocks Institute, University of Central Lancashire, Preston, PR1 2HE (United Kingdom); Howard, Andrew W. [Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822 (United States); O’Leary, Ryan M. [JILA, University of Colorado and NIST, 440 UCB, Boulder, 80309-0440 (United States)

    2016-09-20

    Heartbeat stars (HB stars) are a class of eccentric binary stars with close periastron passages. The characteristic photometric HB signal evident in their light curves is produced by a combination of tidal distortion, heating, and Doppler boosting near orbital periastron. Many HB stars continue to oscillate after periastron and along the entire orbit, indicative of the tidal excitation of oscillation modes within one or both stars. These systems are among the most eccentric binaries known, and they constitute astrophysical laboratories for the study of tidal effects. We have undertaken a radial velocity (RV) monitoring campaign of Kepler HB stars in order to measure their orbits. We present our first results here, including a sample of 22 Kepler HB systems, where for 19 of them we obtained the Keplerian orbit and for 3 other systems we did not detect a statistically significant RV variability. Results presented here are based on 218 spectra obtained with the Keck/HIRES spectrograph during the 2015 Kepler observing season, and they have allowed us to obtain the largest sample of HB stars with orbits measured using a single instrument, which roughly doubles the number of HB stars with an RV measured orbit. The 19 systems measured here have orbital periods from 7 to 90 days and eccentricities from 0.2 to 0.9. We show that HB stars draw the upper envelope of the eccentricity–period distribution. Therefore, HB stars likely represent a population of stars currently undergoing high eccentricity migration via tidal orbital circularization, and they will allow for new tests of high eccentricity migration theories.

  13. Scaling laws for radial foil bearings

    Science.gov (United States)

    Honavara Prasad, Srikanth

    The effects of fluid pressurization, structural deformation of the compliant members and heat generation in foil bearings make the design and analysis of foil bearings very complicated. The complex fluid-structural-thermal interactions in foil bearings also make modeling efforts challenging because these phenomena are governed by highly non-linear partial differential equations. Consequently, comparison of various bearing designs require detailed calculation of the flow fields (velocities, pressures), bump deflections (structural compliance) and heat transfer phenomena (viscous dissipation in the fluid, frictional heating, temperature profile etc.,) resulting in extensive computational effort (time/hardware). To obviate rigorous computations and aid in feasibility assessments of foil bearings of various sizes, NASA developed the "rule of thumb" design guidelines for estimation of journal bearing load capacity. The guidelines are based on extensive experimental data. The goal of the current work is the development of scaling laws for radial foil bearings to establish an analytical "rule of thumb" for bearing clearance and bump stiffness. The use of scale invariant Reynolds equation and experimentally observed NASA "rule of thumb" yield scale factors which can be deduced from first principles. Power-law relationships between: a. Bearing clearance and bearing radius, and b. bump stiffness and bearing radius, are obtained. The clearance and bump stiffness values obtained from scaling laws are used as inputs for Orbit simulation to study various cases. As the clearance of the bearing reaches the dimensions of the material surface roughness, asperity contact breaks the fluid film which results in wear. Similarly, as the rotor diameter increases (requiring larger bearing diameters), the load capacity of the fluid film should increase to prevent dry rubbing. This imposes limits on the size of the rotor diameter and consequently bearing diameter. Therefore, this thesis aims

  14. RADIAL VELOCITY MONITORING OF KEPLER HEARTBEAT STARS

    International Nuclear Information System (INIS)

    Shporer, Avi; Fuller, Jim; Isaacson, Howard; Hambleton, Kelly; Prša, Andrej; Thompson, Susan E.; Kurtz, Donald W.; Howard, Andrew W.; O’Leary, Ryan M.

    2016-01-01

    Heartbeat stars (HB stars) are a class of eccentric binary stars with close periastron passages. The characteristic photometric HB signal evident in their light curves is produced by a combination of tidal distortion, heating, and Doppler boosting near orbital periastron. Many HB stars continue to oscillate after periastron and along the entire orbit, indicative of the tidal excitation of oscillation modes within one or both stars. These systems are among the most eccentric binaries known, and they constitute astrophysical laboratories for the study of tidal effects. We have undertaken a radial velocity (RV) monitoring campaign of Kepler HB stars in order to measure their orbits. We present our first results here, including a sample of 22 Kepler HB systems, where for 19 of them we obtained the Keplerian orbit and for 3 other systems we did not detect a statistically significant RV variability. Results presented here are based on 218 spectra obtained with the Keck/HIRES spectrograph during the 2015 Kepler observing season, and they have allowed us to obtain the largest sample of HB stars with orbits measured using a single instrument, which roughly doubles the number of HB stars with an RV measured orbit. The 19 systems measured here have orbital periods from 7 to 90 days and eccentricities from 0.2 to 0.9. We show that HB stars draw the upper envelope of the eccentricity–period distribution. Therefore, HB stars likely represent a population of stars currently undergoing high eccentricity migration via tidal orbital circularization, and they will allow for new tests of high eccentricity migration theories.

  15. Static Voltage Stability Analysis by Using SVM and Neural Network

    Directory of Open Access Journals (Sweden)

    Mehdi Hajian

    2013-01-01

    Full Text Available Voltage stability is an important problem in power system networks. In this paper, in terms of static voltage stability, and application of Neural Networks (NN and Supported Vector Machine (SVM for estimating of voltage stability margin (VSM and predicting of voltage collapse has been investigated. This paper considers voltage stability in power system in two parts. The first part calculates static voltage stability margin by Radial Basis Function Neural Network (RBFNN. The advantage of the used method is high accuracy in online detecting the VSM. Whereas the second one, voltage collapse analysis of power system is performed by Probabilistic Neural Network (PNN and SVM. The obtained results in this paper indicate, that time and number of training samples of SVM, are less than NN. In this paper, a new model of training samples for detection system, using the normal distribution load curve at each load feeder, has been used. Voltage stability analysis is estimated by well-know L and VSM indexes. To demonstrate the validity of the proposed methods, IEEE 14 bus grid and the actual network of Yazd Province are used.

  16. Radial head fracture associated with posterior interosseous nerve injury

    Directory of Open Access Journals (Sweden)

    Bernardo Barcellos Terra

    Full Text Available ABSTRACT Fractures of the radial head and radial neck correspond to 1.7-5.4% of all fractures and approximately 30% may present associated injuries. In the literature, there are few reports of radial head fracture with posterior interosseous nerve injury. This study aimed to report a case of radial head fracture associated with posterior interosseous nerve injury. CASE REPORT: A male patient, aged 42 years, sought medical care after falling from a skateboard. The patient related pain and limitation of movement in the right elbow and difficulty to extend the fingers of the right hand. During physical examination, thumb and fingers extension deficit was observed. The wrist extension showed a slight radial deviation. After imaging, it became evident that the patient had a fracture of the radial head that was classified as grade III in the Mason classification. The patient underwent fracture fixation; at the first postoperative day, thumb and fingers extension was observed. Although rare, posterior interosseous nerve branch injury may be associated with radial head fractures. In the present case, the authors believe that neuropraxia occurred as a result of the fracture hematoma and edema.

  17. Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

    Science.gov (United States)

    Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

    2015-06-01

    Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

  18. Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

    International Nuclear Information System (INIS)

    Hosseini-Golgoo, S M; Bozorgi, H; Saberkari, A

    2015-01-01

    Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively. (paper)

  19. The biological basis of radiotherapy

    International Nuclear Information System (INIS)

    Steel, G.G.; Adams, G.E.; Horwich, A.

    1989-01-01

    The focus of this book is the biological basis of radiotherapy. The papers presented include: Temporal stages of radiation action:free radical processes; The molecular basis of radiosensitivity; and Radiation damage to early-reacting normal tissue

  20. Structural health monitoring and damage assessment using measured FRFs from multiple sensors. Part II. Decision making with RBF networks

    Energy Technology Data Exchange (ETDEWEB)

    Zang, C.; Friswell, M.I. [Dept. of Aerospace Engineering, Univ. of Bristol, Bristol (United Kingdom); Imregun, M. [Dept. of Mechanical Engineering, Imperial Coll., London (United Kingdom)

    2003-07-01

    This paper is the second of two papers concerned with structural health monitoring and damage assessment using measured FRFs from multiple sensors, and discusses the decision making technique with radial basis function (RBF) neural networks. In PART 1 of the paper, the correlation criteria showed their capability to indicate various changes to the structure's state. PART 2, presented here, develops the methodology of decision theory to identify precisely all of the structure states. Although, the statistical approach can be used for classification, interpreting the information is difficult. Neural network techniques have been proven to possess many advantages for classification due to their learning ability and good generalization. In this paper, the radial basis function neural network is applied for function approximation and recognition. The key idea is to partition the input space (the indicators of the correlation criteria) into a number of subspaces that are in the form of hyper spheres. Then, the widely used k-mean clustering algorithm was selected as a logical approach to detecting the structure states. A bookshelf structure with measured frequency responses from 24 accelerometers was used to demonstrate the effectiveness of the method. The results show the successful classification of all structure states, for instance, the undamaged and damage states, damage locations and damage levels, and the environmental variability. (orig.)

  1. Systematic determination of extended atomic orbital basis sets and application to molecular SCF and MCSCF calculations

    Energy Technology Data Exchange (ETDEWEB)

    Feller, D.F.

    1979-01-01

    The behavior of the two exponential parameters in an even-tempered gaussian basis set is investigated as the set optimally approaches an integral transform representation of the radial portion of atomic and molecular orbitals. This approach permits a highly accurate assessment of the Hartree-Fock limit for atoms and molecules.

  2. Stellar Angular Momentum Distributions and Preferential Radial Migration

    Science.gov (United States)

    Wyse, Rosemary; Daniel, Kathryne J.

    2018-04-01

    I will present some results from our recent investigations into the efficiency of radial migration in stellar disks of differing angular momentum distributions, within a given adopted 2D spiral disk potential. We apply to our models an analytic criterion that determines whether or not individual stars are in orbits that could lead to radial migration around the corotation resonance. We couch our results in terms of the local stellar velocity dispersion and find that the fraction of stars that could migrate radially decreases as the velocity dispersion increases. I will discuss implications and comparisons with the results of other approaches.

  3. Research on Radial Vibration of a Circular Plate

    Directory of Open Access Journals (Sweden)

    Wei Liu

    2016-01-01

    Full Text Available Radial vibration of the circular plate is presented using wave propagation approach and classical method containing Bessel solution and Hankel solution for calculating the natural frequency theoretically. In cylindrical coordinate system, in order to obtain natural frequency, propagation and reflection matrices are deduced at the boundaries of free-free, fixed-fixed, and fixed-free using wave propagation approach. Furthermore, radial phononic crystal is constructed by connecting two materials periodically for the analysis of band phenomenon. Also, Finite Element Simulation (FEM is adopted to verify the theoretical results. Finally, the radial and piezoelectric effects on the band are also discussed.

  4. Small disturbances stability analysis applied in a radial distribution system with distributed generation units; Analise de estabilidade a pequenos disturbios aplicada em um sistema de distribuicao radial com unidades de geracao distribuida

    Energy Technology Data Exchange (ETDEWEB)

    Dorca, Daniel Azevedo; Camacho, Jose Roberto [Universidade Federal de Uberlandia (UFU), MG (Brazil). Curso de Mestrado em Engenharia Eletrica

    2008-07-01

    This work investigates the small-disturbance stability of a 30 bus radial distribution system with distributed generation units. This work is realized through the time domain simulations and through the eigenvalue analysis and participation factors. The eigenvalue analysis show that is possible to predict a possible system instability face to a disturbance. The development of this work was stimulated by the increasing of the distributed generation units in the distribution networks. (author)

  5. Predicting hourly cooling load in the building: A comparison of support vector machine and different artificial neural networks

    International Nuclear Information System (INIS)

    Li Qiong; Meng Qinglin; Cai Jiejin; Yoshino, Hiroshi; Mochida, Akashi

    2009-01-01

    This study presents four modeling techniques for the prediction of hourly cooling load in the building. In addition to the traditional back propagation neural network (BPNN), the radial basis function neural network (RBFNN), general regression neural network (GRNN) and support vector machine (SVM) are considered. All the prediction models have been applied to an office building in Guangzhou, China. Evaluation of the prediction accuracy of the four models is based on the root mean square error (RMSE) and mean relative error (MRE). The simulation results demonstrate that the four discussed models can be effective for building cooling load prediction. The SVM and GRNN methods can achieve better accuracy and generalization than the BPNN and RBFNN methods

  6. RBF neural network based PI pitch controller for a class of 5-MW wind turbines using particle swarm optimization algorithm.

    Science.gov (United States)

    Poultangari, Iman; Shahnazi, Reza; Sheikhan, Mansour

    2012-09-01

    In order to control the pitch angle of blades in wind turbines, commonly the proportional and integral (PI) controller due to its simplicity and industrial usability is employed. The neural networks and evolutionary algorithms are tools that provide a suitable ground to determine the optimal PI gains. In this paper, a radial basis function (RBF) neural network based PI controller is proposed for collective pitch control (CPC) of a 5-MW wind turbine. In order to provide an optimal dataset to train the RBF neural network, particle swarm optimization (PSO) evolutionary algorithm is used. The proposed method does not need the complexities, nonlinearities and uncertainties of the system under control. The simulation results show that the proposed controller has satisfactory performance. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Granular Corneal Dystrophy Manifesting after Radial Keratotomy

    Directory of Open Access Journals (Sweden)

    Sepehr Feizi

    2008-12-01

    Full Text Available

    PURPOSE: To report manifestation of granular corneal dystrophy after radial keratotomy (RK. CASE REPORT: A 32-year-old man presented with white radial lines in both corneas. He had undergone uncomplicated RK in both eyes 8 years ago. Preoperative refraction had been OD: -3.5 -0.75@180 and OS: -3.0 -0.5@175. Uncorrected visual acuity was OD: 8/10 and OS: 7/10; best corrected visual acuity was 9/10 in both eyes with OD: -0.5 -0.5@60 and OS: -0.75 -0.5@80. Slit lamp examination revealed discrete well-demarcated whitish lesions with clear intervening stroma in the central anterior cornea consistent with granular dystrophy. Similar opacities were present within the RK incisions. CONCLUSION: Granular dystrophy deposits may appear within RK incisions besides other previously reported locations.