Speech coding code- excited linear prediction
Bäckström, Tom
2017-01-01
This book provides scientific understanding of the most central techniques used in speech coding both for advanced students as well as professionals with a background in speech audio and or digital signal processing. It provides a clear connection between the whys hows and whats thus enabling a clear view of the necessity purpose and solutions provided by various tools as well as their strengths and weaknesses in each respect Equivalently this book sheds light on the following perspectives for each technology presented Objective What do we want to achieve and especially why is this goal important Resource Information What information is available and how can it be useful and Resource Platform What kind of platforms are we working with and what are their capabilities restrictions This includes computational memory and acoustic properties and the transmission capacity of devices used. The book goes on to address Solutions Which solutions have been proposed and how can they be used to reach the stated goals and ...
Sparsity in Linear Predictive Coding of Speech
Giacobello, Daniele
of the effectiveness of their application in audio processing. The second part of the thesis deals with introducing sparsity directly in the linear prediction analysis-by-synthesis (LPAS) speech coding paradigm. We first propose a novel near-optimal method to look for a sparse approximate excitation using a compressed...... one with direct applications to coding but also consistent with the speech production model of voiced speech, where the excitation of the all-pole filter can be modeled as an impulse train, i.e., a sparse sequence. Introducing sparsity in the LP framework will also bring to de- velop the concept...... sensing formulation. Furthermore, we define a novel re-estimation procedure to adapt the predictor coefficients to the given sparse excitation, balancing the two representations in the context of speech coding. Finally, the advantages of the compact parametric representation of a segment of speech, given...
Hu, J H; Wang, Y; Cahill, P T
1997-01-01
This paper reports a multispectral code excited linear prediction (MCELP) method for the compression of multispectral images. Different linear prediction models and adaptation schemes have been compared. The method that uses a forward adaptive autoregressive (AR) model has been proven to achieve a good compromise between performance, complexity, and robustness. This approach is referred to as the MFCELP method. Given a set of multispectral images, the linear predictive coefficients are updated over nonoverlapping three-dimensional (3-D) macroblocks. Each macroblock is further divided into several 3-D micro-blocks, and the best excitation signal for each microblock is determined through an analysis-by-synthesis procedure. The MFCELP method has been applied to multispectral magnetic resonance (MR) images. To satisfy the high quality requirement for medical images, the error between the original image set and the synthesized one is further specified using a vector quantizer. This method has been applied to images from 26 clinical MR neuro studies (20 slices/study, three spectral bands/slice, 256x256 pixels/band, 12 b/pixel). The MFCELP method provides a significant visual improvement over the discrete cosine transform (DCT) based Joint Photographers Expert Group (JPEG) method, the wavelet transform based embedded zero-tree wavelet (EZW) coding method, and the vector tree (VT) coding method, as well as the multispectral segmented autoregressive moving average (MSARMA) method we developed previously.
Christensen, M. G.; Jensen, Søren Holdt
2006-01-01
A method for amplitude modulated sinusoidal audio coding is presented that has low complexity and low delay. This is based on a subband processing system, where, in each subband, the signal is modeled as an amplitude modulated sum of sinusoids. The envelopes are estimated using frequency......-domain linear prediction and the prediction coefficients are quantized. As a proof of concept, we evaluate different configurations in a subjective listening test, and this shows that the proposed method offers significant improvements in sinusoidal coding. Furthermore, the properties of the frequency...
Real time implementation of a linear predictive coding algorithm on digital signal processor DSP32C
Sheikh, N.M.; Usman, S.R.; Fatima, S.
2002-01-01
Pulse Code Modulation (PCM) has been widely used in speech coding. However, due to its high bit rate. PCM has severe limitations in application where high spectral efficiency is desired, for example, in mobile communication, CD quality broadcasting system etc. These limitation have motivated research in bit rate reduction techniques. Linear predictive coding (LPC) is one of the most powerful complex techniques for bit rate reduction. With the introduction of powerful digital signal processors (DSP) it is possible to implement the complex LPC algorithm in real time. In this paper we present a real time implementation of the LPC algorithm on AT and T's DSP32C at a sampling frequency of 8192 HZ. Application of the LPC algorithm on two speech signals is discussed. Using this implementation , a bit rate reduction of 1:3 is achieved for better than tool quality speech, while a reduction of 1.16 is possible for speech quality required in military applications. (author)
Modified linear predictive coding approach for moving target tracking by Doppler radar
Ding, Yipeng; Lin, Xiaoyi; Sun, Ke-Hui; Xu, Xue-Mei; Liu, Xi-Yao
2016-07-01
Doppler radar is a cost-effective tool for moving target tracking, which can support a large range of civilian and military applications. A modified linear predictive coding (LPC) approach is proposed to increase the target localization accuracy of the Doppler radar. Based on the time-frequency analysis of the received echo, the proposed approach first real-time estimates the noise statistical parameters and constructs an adaptive filter to intelligently suppress the noise interference. Then, a linear predictive model is applied to extend the available data, which can help improve the resolution of the target localization result. Compared with the traditional LPC method, which empirically decides the extension data length, the proposed approach develops an error array to evaluate the prediction accuracy and thus, adjust the optimum extension data length intelligently. Finally, the prediction error array is superimposed with the predictor output to correct the prediction error. A series of experiments are conducted to illustrate the validity and performance of the proposed techniques.
Random linear codes in steganography
Kamil Kaczyński
2016-12-01
Full Text Available Syndrome coding using linear codes is a technique that allows improvement in the steganographic algorithms parameters. The use of random linear codes gives a great flexibility in choosing the parameters of the linear code. In parallel, it offers easy generation of parity check matrix. In this paper, the modification of LSB algorithm is presented. A random linear code [8, 2] was used as a base for algorithm modification. The implementation of the proposed algorithm, along with practical evaluation of algorithms’ parameters based on the test images was made.[b]Keywords:[/b] steganography, random linear codes, RLC, LSB
Rumen Daskalov
2017-07-01
Full Text Available Let an $[n,k,d]_q$ code be a linear code of length $n$, dimension $k$ and minimum Hamming distance $d$ over $GF(q$. One of the most important problems in coding theory is to construct codes with optimal minimum distances. In this paper 22 new ternary linear codes are presented. Two of them are optimal. All new codes improve the respective lower bounds in [11].
Ririn Kusumawati
2016-05-01
In the classification, using Hidden Markov Model, voice signal is analyzed and searched the maximum possible value that can be recognized. The modeling results obtained parameters are used to compare with the sound of Arabic speakers. From the test results' Classification, Hidden Markov Models with Linear Predictive Coding extraction average accuracy of 78.6% for test data sampling frequency of 8,000 Hz, 80.2% for test data sampling frequency of 22050 Hz, 79% for frequencies sampling test data at 44100 Hz.
Squares of Random Linear Codes
Cascudo Pueyo, Ignacio; Cramer, Ronald; Mirandola, Diego
2015-01-01
a positive answer, for codes of dimension $k$ and length roughly $\\frac{1}{2}k^2$ or smaller. Moreover, the convergence speed is exponential if the difference $k(k+1)/2-n$ is at least linear in $k$. The proof uses random coding and combinatorial arguments, together with algebraic tools involving the precise......Given a linear code $C$, one can define the $d$-th power of $C$ as the span of all componentwise products of $d$ elements of $C$. A power of $C$ may quickly fill the whole space. Our purpose is to answer the following question: does the square of a code ``typically'' fill the whole space? We give...
Linear network error correction coding
Guang, Xuan
2014-01-01
There are two main approaches in the theory of network error correction coding. In this SpringerBrief, the authors summarize some of the most important contributions following the classic approach, which represents messages by sequences?similar to algebraic coding,?and also briefly discuss the main results following the?other approach,?that uses the theory of rank metric codes for network error correction of representing messages by subspaces. This book starts by establishing the basic linear network error correction (LNEC) model and then characterizes two equivalent descriptions. Distances an
An Optimal Linear Coding for Index Coding Problem
Pezeshkpour, Pouya
2015-01-01
An optimal linear coding solution for index coding problem is established. Instead of network coding approach by focus on graph theoric and algebraic methods a linear coding program for solving both unicast and groupcast index coding problem is presented. The coding is proved to be the optimal solution from the linear perspective and can be easily utilize for any number of messages. The importance of this work is lying mostly on the usage of the presented coding in the groupcast index coding ...
Forms and Linear Network Codes
Hansen, Johan P.
We present a general theory to obtain linear network codes utilizing forms and obtain explicit families of equidimensional vector spaces, in which any pair of distinct vector spaces intersect in the same small dimension. The theory is inspired by the methods of the author utilizing the osculating...... spaces of Veronese varieties. Linear network coding transmits information in terms of a basis of a vector space and the information is received as a basis of a possibly altered vector space. Ralf Koetter and Frank R. Kschischang introduced a metric on the set af vector spaces and showed that a minimal...... distance decoder for this metric achieves correct decoding if the dimension of the intersection of the transmitted and received vector space is sufficiently large. The vector spaces in our construction are equidistant in the above metric and the distance between any pair of vector spaces is large making...
On the linear programming bound for linear Lee codes.
Astola, Helena; Tabus, Ioan
2016-01-01
Based on an invariance-type property of the Lee-compositions of a linear Lee code, additional equality constraints can be introduced to the linear programming problem of linear Lee codes. In this paper, we formulate this property in terms of an action of the multiplicative group of the field [Formula: see text] on the set of Lee-compositions. We show some useful properties of certain sums of Lee-numbers, which are the eigenvalues of the Lee association scheme, appearing in the linear programming problem of linear Lee codes. Using the additional equality constraints, we formulate the linear programming problem of linear Lee codes in a very compact form, leading to a fast execution, which allows to efficiently compute the bounds for large parameter values of the linear codes.
The linear programming bound for binary linear codes
Brouwer, A.E.
1993-01-01
Combining Delsarte's (1973) linear programming bound with the information that certain weights cannot occur, new upper bounds for dmin (n,k), the maximum possible minimum distance of a binary linear code with given word length n and dimension k, are derived.
Linear codes associated to determinantal varieties
Beelen, Peter; Ghorpade, Sudhir R.; Hasan, Sartaj Ul
2015-01-01
We consider a class of linear codes associated to projective algebraic varieties defined by the vanishing of minors of a fixed size of a generic matrix. It is seen that the resulting code has only a small number of distinct weights. The case of varieties defined by the vanishing of 2×2 minors is ...
A symmetric Roos bound for linear codes
Duursma, I.M.; Pellikaan, G.R.
2006-01-01
The van Lint–Wilson AB-method yields a short proof of the Roos bound for the minimum distance of a cyclic code. We use the AB-method to obtain a different bound for the weights of a linear code. In contrast to the Roos bound, the role of the codes A and B in our bound is symmetric. We use the bound
Computer codes for designing proton linear accelerators
Kato, Takao
1992-01-01
Computer codes for designing proton linear accelerators are discussed from the viewpoint of not only designing but also construction and operation of the linac. The codes are divided into three categories according to their purposes: 1) design code, 2) generation and simulation code, and 3) electric and magnetic fields calculation code. The role of each category is discussed on the basis of experience at KEK (the design of the 40-MeV proton linac and its construction and operation, and the design of the 1-GeV proton linac). We introduce our recent work relevant to three-dimensional calculation and supercomputer calculation: 1) tuning of MAFIA (three-dimensional electric and magnetic fields calculation code) for supercomputer, 2) examples of three-dimensional calculation of accelerating structures by MAFIA, 3) development of a beam transport code including space charge effects. (author)
Decoding Algorithms for Random Linear Network Codes
Heide, Janus; Pedersen, Morten Videbæk; Fitzek, Frank
2011-01-01
We consider the problem of efficient decoding of a random linear code over a finite field. In particular we are interested in the case where the code is random, relatively sparse, and use the binary finite field as an example. The goal is to decode the data using fewer operations to potentially...... achieve a high coding throughput, and reduce energy consumption.We use an on-the-fly version of the Gauss-Jordan algorithm as a baseline, and provide several simple improvements to reduce the number of operations needed to perform decoding. Our tests show that the improvements can reduce the number...
Construction of Protograph LDPC Codes with Linear Minimum Distance
Divsalar, Dariush; Dolinar, Sam; Jones, Christopher
2006-01-01
A construction method for protograph-based LDPC codes that simultaneously achieve low iterative decoding threshold and linear minimum distance is proposed. We start with a high-rate protograph LDPC code with variable node degrees of at least 3. Lower rate codes are obtained by splitting check nodes and connecting them by degree-2 nodes. This guarantees the linear minimum distance property for the lower-rate codes. Excluding checks connected to degree-1 nodes, we show that the number of degree-2 nodes should be at most one less than the number of checks for the protograph LDPC code to have linear minimum distance. Iterative decoding thresholds are obtained by using the reciprocal channel approximation. Thresholds are lowered by using either precoding or at least one very high-degree node in the base protograph. A family of high- to low-rate codes with minimum distance linearly increasing in block size and with capacity-approaching performance thresholds is presented. FPGA simulation results for a few example codes show that the proposed codes perform as predicted.
The Theory of Linear Prediction
Vaidyanathan, PP
2007-01-01
Linear prediction theory has had a profound impact in the field of digital signal processing. Although the theory dates back to the early 1940s, its influence can still be seen in applications today. The theory is based on very elegant mathematics and leads to many beautiful insights into statistical signal processing. Although prediction is only a part of the more general topics of linear estimation, filtering, and smoothing, this book focuses on linear prediction. This has enabled detailed discussion of a number of issues that are normally not found in texts. For example, the theory of vecto
Dopamine reward prediction error coding.
Schultz, Wolfram
2016-03-01
Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.
Predictive coding in Agency Detection
Andersen, Marc Malmdorf
2017-01-01
Agency detection is a central concept in the cognitive science of religion (CSR). Experimental studies, however, have so far failed to lend support to some of the most common predictions that follow from current theories on agency detection. In this article, I argue that predictive coding, a highly...... promising new framework for understanding perception and action, may solve pending theoretical inconsistencies in agency detection research, account for the puzzling experimental findings mentioned above, and provide hypotheses for future experimental testing. Predictive coding explains how the brain......, unbeknownst to consciousness, engages in sophisticated Bayesian statistics in an effort to constantly predict the hidden causes of sensory input. My fundamental argument is that most false positives in agency detection can be seen as the result of top-down interference in a Bayesian system generating high...
Some new quasi-twisted ternary linear codes
Rumen Daskalov
2015-09-01
Full Text Available Let [n, k, d]_q code be a linear code of length n, dimension k and minimum Hamming distance d over GF(q. One of the basic and most important problems in coding theory is to construct codes with best possible minimum distances. In this paper seven quasi-twisted ternary linear codes are constructed. These codes are new and improve the best known lower bounds on the minimum distance in [6].
Neural Elements for Predictive Coding
Stewart SHIPP
2016-11-01
Full Text Available Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backwards in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many ‘illusory’ instances of perception where what is seen (heard, etc is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forwards and backwards pathways should be completely separate, given their functional distinction; this aspect of circuitry – that neurons with extrinsically bifurcating axons do not project in both directions – has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy formulation of predictive coding is combined with the classic ‘canonical microcircuit’ and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a updates in the microcircuitry of primate visual cortex, and (b rapid technical advances made
Neural Elements for Predictive Coding.
Shipp, Stewart
2016-01-01
Predictive coding theories of sensory brain function interpret the hierarchical construction of the cerebral cortex as a Bayesian, generative model capable of predicting the sensory data consistent with any given percept. Predictions are fed backward in the hierarchy and reciprocated by prediction error in the forward direction, acting to modify the representation of the outside world at increasing levels of abstraction, and so to optimize the nature of perception over a series of iterations. This accounts for many 'illusory' instances of perception where what is seen (heard, etc.) is unduly influenced by what is expected, based on past experience. This simple conception, the hierarchical exchange of prediction and prediction error, confronts a rich cortical microcircuitry that is yet to be fully documented. This article presents the view that, in the current state of theory and practice, it is profitable to begin a two-way exchange: that predictive coding theory can support an understanding of cortical microcircuit function, and prompt particular aspects of future investigation, whilst existing knowledge of microcircuitry can, in return, influence theoretical development. As an example, a neural inference arising from the earliest formulations of predictive coding is that the source populations of forward and backward pathways should be completely separate, given their functional distinction; this aspect of circuitry - that neurons with extrinsically bifurcating axons do not project in both directions - has only recently been confirmed. Here, the computational architecture prescribed by a generalized (free-energy) formulation of predictive coding is combined with the classic 'canonical microcircuit' and the laminar architecture of hierarchical extrinsic connectivity to produce a template schematic, that is further examined in the light of (a) updates in the microcircuitry of primate visual cortex, and (b) rapid technical advances made possible by transgenic neural
Linear and nonlinear verification of gyrokinetic microstability codes
Bravenec, R. V.; Candy, J.; Barnes, M.; Holland, C.
2011-12-01
Verification of nonlinear microstability codes is a necessary step before comparisons or predictions of turbulent transport in toroidal devices can be justified. By verification we mean demonstrating that a code correctly solves the mathematical model upon which it is based. Some degree of verification can be accomplished indirectly from analytical instability threshold conditions, nonlinear saturation estimates, etc., for relatively simple plasmas. However, verification for experimentally relevant plasma conditions and physics is beyond the realm of analytical treatment and must rely on code-to-code comparisons, i.e., benchmarking. The premise is that the codes are verified for a given problem or set of parameters if they all agree within a specified tolerance. True verification requires comparisons for a number of plasma conditions, e.g., different devices, discharges, times, and radii. Running the codes and keeping track of linear and nonlinear inputs and results for all conditions could be prohibitive unless there was some degree of automation. We have written software to do just this and have formulated a metric for assessing agreement of nonlinear simulations. We present comparisons, both linear and nonlinear, between the gyrokinetic codes GYRO [J. Candy and R. E. Waltz, J. Comput. Phys. 186, 545 (2003)] and GS2 [W. Dorland, F. Jenko, M. Kotschenreuther, and B. N. Rogers, Phys. Rev. Lett. 85, 5579 (2000)]. We do so at the mid-radius for the same discharge as in earlier work [C. Holland, A. E. White, G. R. McKee, M. W. Shafer, J. Candy, R. E. Waltz, L. Schmitz, and G. R. Tynan, Phys. Plasmas 16, 052301 (2009)]. The comparisons include electromagnetic fluctuations, passing and trapped electrons, plasma shaping, one kinetic impurity, and finite Debye-length effects. Results neglecting and including electron collisions (Lorentz model) are presented. We find that the linear frequencies with or without collisions agree well between codes, as do the time averages of
Similarities and Differences Between Warped Linear Prediction and Laguerre Linear Prediction
Brinker, Albertus C. den; Krishnamoorthi, Harish; Verbitskiy, Evgeny A.
2011-01-01
Linear prediction has been successfully applied in many speech and audio processing systems. This paper presents the similarities and differences between two classes of linear prediction schemes, namely, Warped Linear Prediction (WLP) and Laguerre Linear Prediction (LLP). It is shown that both
Riemann-Roch Spaces and Linear Network Codes
Hansen, Johan P.
We construct linear network codes utilizing algebraic curves over finite fields and certain associated Riemann-Roch spaces and present methods to obtain their parameters. In particular we treat the Hermitian curve and the curves associated with the Suzuki and Ree groups all having the maximal...... number of points for curves of their respective genera. Linear network coding transmits information in terms of a basis of a vector space and the information is received as a basis of a possibly altered vector space. Ralf Koetter and Frank R. Kschischang %\\cite{DBLP:journals/tit/KoetterK08} introduced...... in the above metric making them suitable for linear network coding....
The Use of Linear Programming for Prediction.
Schnittjer, Carl J.
The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)
Dopamine reward prediction error coding
Schultz, Wolfram
2016-01-01
Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards?an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less...
Osculating Spaces of Varieties and Linear Network Codes
Hansen, Johan P.
2013-01-01
We present a general theory to obtain good linear network codes utilizing the osculating nature of algebraic varieties. In particular, we obtain from the osculating spaces of Veronese varieties explicit families of equidimensional vector spaces, in which any pair of distinct vector spaces...... intersects in the same dimension. Linear network coding transmits information in terms of a basis of a vector space and the information is received as a basis of a possible altered vector space. Ralf Koetter and Frank R. Kschischang introduced a metric on the set af vector spaces and showed that a minimal...... distance decoder for this metric achieves correct decoding if the dimension of the intersection of the transmitted and received vector space is sufficiently large. The obtained osculating spaces of Veronese varieties are equidistant in the above metric. The parameters of the resulting linear network codes...
Osculating Spaces of Varieties and Linear Network Codes
Hansen, Johan P.
We present a general theory to obtain good linear network codes utilizing the osculating nature of algebraic varieties. In particular, we obtain from the osculating spaces of Veronese varieties explicit families of equideminsional vector spaces, in which any pair of distinct vector spaces...... intersects in the same dimension. Linear network coding transmits information in terms of a basis of a vector space and the information is received as a basis of a possible altered vector space. Ralf Koetter and Frank R. Kschischang introduced a metric on the set af vector spaces and showed that a minimal...... distance decoder for this metric achieves correct decoding if the dimension of the intersection of the transmitted and received vector space is sufficiently large. The obtained osculating spaces of Veronese varieties are equidistant in the above metric. The parameters of the resulting linear network codes...
Random linear network coding for streams with unequally sized packets
Taghouti, Maroua; Roetter, Daniel Enrique Lucani; Pedersen, Morten Videbæk
2016-01-01
State of the art Random Linear Network Coding (RLNC) schemes assume that data streams generate packets with equal sizes. This is an assumption that results in the highest efficiency gains for RLNC. A typical solution for managing unequal packet sizes is to zero-pad the smallest packets. However, ...
Linear zonal atmospheric prediction for adaptive optics
McGuire, Patrick C.; Rhoadarmer, Troy A.; Coy, Hanna A.; Angel, J. Roger P.; Lloyd-Hart, Michael
2000-07-01
We compare linear zonal predictors of atmospheric turbulence for adaptive optics. Zonal prediction has the possible advantage of being able to interpret and utilize wind-velocity information from the wavefront sensor better than modal prediction. For simulated open-loop atmospheric data for a 2- meter 16-subaperture AO telescope with 5 millisecond prediction and a lookback of 4 slope-vectors, we find that Widrow-Hoff Delta-Rule training of linear nets and Back- Propagation training of non-linear multilayer neural networks is quite slow, getting stuck on plateaus or in local minima. Recursive Least Squares training of linear predictors is two orders of magnitude faster and it also converges to the solution with global minimum error. We have successfully implemented Amari's Adaptive Natural Gradient Learning (ANGL) technique for a linear zonal predictor, which premultiplies the Delta-Rule gradients with a matrix that orthogonalizes the parameter space and speeds up the training by two orders of magnitude, like the Recursive Least Squares predictor. This shows that the simple Widrow-Hoff Delta-Rule's slow convergence is not a fluke. In the case of bright guidestars, the ANGL, RLS, and standard matrix-inversion least-squares (MILS) algorithms all converge to the same global minimum linear total phase error (approximately 0.18 rad2), which is only approximately 5% higher than the spatial phase error (approximately 0.17 rad2), and is approximately 33% lower than the total 'naive' phase error without prediction (approximately 0.27 rad2). ANGL can, in principle, also be extended to make non-linear neural network training feasible for these large networks, with the potential to lower the predictor error below the linear predictor error. We will soon scale our linear work to the approximately 108-subaperture MMT AO system, both with simulations and real wavefront sensor data from prime focus.
Simulations of linear and Hamming codes using SageMath
Timur, Tahta D.; Adzkiya, Dieky; Soleha
2018-03-01
Digital data transmission over a noisy channel could distort the message being transmitted. The goal of coding theory is to ensure data integrity, that is, to find out if and where this noise has distorted the message and what the original message was. Data transmission consists of three stages: encoding, transmission, and decoding. Linear and Hamming codes are codes that we discussed in this work, where encoding algorithms are parity check and generator matrix, and decoding algorithms are nearest neighbor and syndrome. We aim to show that we can simulate these processes using SageMath software, which has built-in class of coding theory in general and linear codes in particular. First we consider the message as a binary vector of size k. This message then will be encoded to a vector with size n using given algorithms. And then a noisy channel with particular value of error probability will be created where the transmission will took place. The last task would be decoding, which will correct and revert the received message back to the original message whenever possible, that is, if the number of error occurred is smaller or equal to the correcting radius of the code. In this paper we will use two types of data for simulations, namely vector and text data.
Improved Methods for Pitch Synchronous Linear Prediction Analysis of Speech
劉, 麗清
2015-01-01
Linear prediction (LP) analysis has been applied to speech system over the last few decades. LP technique is well-suited for speech analysis due to its ability to model speech production process approximately. Hence LP analysis has been widely used for speech enhancement, low-bit-rate speech coding in cellular telephony, speech recognition, characteristic parameter extraction (vocal tract resonances frequencies, fundamental frequency called pitch) and so on. However, the performance of the co...
Reliability of Broadcast Communications Under Sparse Random Linear Network Coding
Brown, Suzie; Johnson, Oliver; Tassi, Andrea
2018-01-01
Ultra-reliable Point-to-Multipoint (PtM) communications are expected to become pivotal in networks offering future dependable services for smart cities. In this regard, sparse Random Linear Network Coding (RLNC) techniques have been widely employed to provide an efficient way to improve the reliability of broadcast and multicast data streams. This paper addresses the pressing concern of providing a tight approximation to the probability of a user recovering a data stream protected by this kin...
Deep Learning Methods for Improved Decoding of Linear Codes
Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair
2018-02-01
The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.
New binary linear codes which are dual transforms of good codes
Jaffe, D.B.; Simonis, J.
1999-01-01
If C is a binary linear code, one may choose a subset S of C, and form a new code CST which is the row space of the matrix having the elements of S as its columns. One way of picking S is to choose a subgroup H of Aut(C) and let S be some H-stable subset of C. Using (primarily) this method for
On Predictive Coding for Erasure Channels Using a Kalman Framework
Arildsen, Thomas; Murthi, Manohar; Andersen, Søren Vang
2009-01-01
We present a new design method for robust low-delay coding of autoregressive sources for transmission across erasure channels. It is a fundamental rethinking of existing concepts. It considers the encoder a mechanism that produces signal measurements from which the decoder estimates the original...... signal. The method is based on linear predictive coding and Kalman estimation at the decoder. We employ a novel encoder state-space representation with a linear quantization noise model. The encoder is represented by the Kalman measurement at the decoder. The presented method designs the encoder...... and decoder offline through an iterative algorithm based on closed-form minimization of the trace of the decoder state error covariance. The design method is shown to provide considerable performance gains, when the transmitted quantized prediction errors are subject to loss, in terms of signal-to-noise ratio...
Linear dispersion codes in space-frequency domain for SCFDE
Marchetti, Nicola; Cianca, Ernestina; Prasad, Ramjee
2007-01-01
This paper presents a general framework for applying the Linear Dispersion Codes (LDC) in the space and frequency domains to Single Carrier - Frequency Domain Equalization (SCFDE) systems. Space-Frequency (SF)LDC are more suitable than Space-Time (ST)-LDC in high mobility environment. However......, the application of LDC in space-frequency domain in SCFDE systems is not straightforward as in Orthogonal Frequency Division Multiplexing (OFDM), since there is no direct access to the subcarriers at the transmitter. This paper describes how to build the space-time dispersion matrices to be used...
Linear Prediction Using Refined Autocorrelation Function
M. Shahidur Rahman
2007-07-01
Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.
Predictive Coding Strategies for Developmental Neurorobotics
Park, Jun-Cheol; Lim, Jae Hyun; Choi, Hansol; Kim, Dae-Shik
2012-01-01
In recent years, predictive coding strategies have been proposed as a possible means by which the brain might make sense of the truly overwhelming amount of sensory data available to the brain at any given moment of time. Instead of the raw data, the brain is hypothesized to guide its actions by assigning causal beliefs to the observed error between what it expects to happen and what actually happens. In this paper, we present a variety of developmental neurorobotics experiments in which minimalist prediction error-based encoding strategies are utilize to elucidate the emergence of infant-like behavior in humanoid robotic platforms. Our approaches will be first naively Piagian, then move onto more Vygotskian ideas. More specifically, we will investigate how simple forms of infant learning, such as motor sequence generation, object permanence, and imitation learning may arise if minimizing prediction errors are used as objective functions. PMID:22586416
Predictive Coding Strategies for Developmental Neurorobotics
Jun-Cheol ePark
2012-05-01
Full Text Available In recent years, predictive coding strategies have been proposed as a possible way of how the brain might make sense of the truly overwhelming amount of sensory data available to the brain at any given moment of time. Instead of the raw data, the brain is hypothesized to guide its actions by assigning causal believes to the observed error between what it expected to happen, and what actually happens. In this paper we present a potpourri of developmental neurorobotics experiments in which minimalist prediction-error based encoding strategies are utilize to elucidate the emergence of infant-like behavior in humanoid robotic platforms. Our approaches will be first naively Piagian, then move onto more Vygotskian ideas. More specifically, we will investigate how simple forms of infant learning such as motor sequence generation, object permanence, and imitation learning may arise if minimizing prediction errors are used as objective functions.
Random Linear Network Coding for 5G Mobile Video Delivery
Dejan Vukobratovic
2018-03-01
Full Text Available An exponential increase in mobile video delivery will continue with the demand for higher resolution, multi-view and large-scale multicast video services. Novel fifth generation (5G 3GPP New Radio (NR standard will bring a number of new opportunities for optimizing video delivery across both 5G core and radio access networks. One of the promising approaches for video quality adaptation, throughput enhancement and erasure protection is the use of packet-level random linear network coding (RLNC. In this review paper, we discuss the integration of RLNC into the 5G NR standard, building upon the ideas and opportunities identified in 4G LTE. We explicitly identify and discuss in detail novel 5G NR features that provide support for RLNC-based video delivery in 5G, thus pointing out to the promising avenues for future research.
Monte Carlo simulation of medical linear accelerator using primo code
Omer, Mohamed Osman Mohamed Elhasan
2014-12-01
The use of monte Carlo simulation has become very important in the medical field and especially in calculation in radiotherapy. Various Monte Carlo codes were developed simulating interactions of particles and photons with matter. One of these codes is PRIMO that performs simulation of radiation transport from the primary electron source of a linac to estimate the absorbed dose in a water phantom or computerized tomography (CT). PRIMO is based on Penelope Monte Carlo code. Measurements of 6 MV photon beam PDD and profile were done for Elekta precise linear accelerator at Radiation and Isotopes Center Khartoum using computerized Blue water phantom and CC13 Ionization Chamber. accept Software was used to control the phantom to measure and verify dose distribution. Elektalinac from the list of available linacs in PRIMO was tuned to model Elekta precise linear accelerator. Beam parameter of 6.0 MeV initial electron energy, 0.20 MeV FWHM, and 0.20 cm focal spot FWHM were used, and an error of 4% between calculated and measured curves was found. The buildup region Z max was 1.40 cm and homogenous profile in cross line and in line were acquired. A number of studies were done to verily the model usability one of them is the effect of the number of histories on accuracy of the simulation and the resulted profile for the same beam parameters. The effect was noticeable and inaccuracies in the profile were reduced by increasing the number of histories. Another study was the effect of Side-step errors on the calculated dose which was compared with the measured dose for the same setting.It was in range of 2% for 5 cm shift, but it was higher in the calculated dose because of the small difference between the tuned model and measured dose curves. Future developments include simulating asymmetrical fields, calculating the dose distribution in computerized tomographic (CT) volume, studying the effect of beam modifiers on beam profile for both electron and photon beams.(Author)
FEAST: a two-dimensional non-linear finite element code for calculating stresses
Tayal, M.
1986-06-01
The computer code FEAST calculates stresses, strains, and displacements. The code is two-dimensional. That is, either plane or axisymmetric calculations can be done. The code models elastic, plastic, creep, and thermal strains and stresses. Cracking can also be simulated. The finite element method is used to solve equations describing the following fundamental laws of mechanics: equilibrium; compatibility; constitutive relations; yield criterion; and flow rule. FEAST combines several unique features that permit large time-steps in even severely non-linear situations. The features include a special formulation for permitting many finite elements to simultaneously cross the boundary from elastic to plastic behaviour; accomodation of large drops in yield-strength due to changes in local temperature and a three-step predictor-corrector method for plastic analyses. These features reduce computing costs. Comparisons against twenty analytical solutions and against experimental measurements show that predictions of FEAST are generally accurate to ± 5%
Linear predictions of supercritical flow instability in two parallel channels
Shah, M.
2008-01-01
A steady state linear code that can predict thermo-hydraulic instability boundaries in a two parallel channel system under supercritical conditions has been developed. Linear and non-linear solutions of the instability boundary in a two parallel channel system are also compared. The effect of gravity on the instability boundary in a two parallel channel system, by changing the orientation of the system flow from horizontal flow to vertical up-flow and vertical down-flow has been analyzed. Vertical up-flow is found to be more unstable than horizontal flow and vertical down flow is found to be the most unstable configuration. The type of instability present in each flow-orientation of a parallel channel system has been checked and the density wave oscillation type is observed in horizontal flow and vertical up-flow, while the static type of instability is observed in a vertical down-flow for the cases studied here. The parameters affecting the instability boundary, such as the heating power, inlet temperature, inlet and outlet K-factors are varied to assess their effects. This study is important for the design of future Generation IV nuclear reactors in which supercritical light water is proposed as the primary coolant. (author)
Sonic boom predictions using a modified Euler code
Siclari, Michael J.
1992-04-01
The environmental impact of a next generation fleet of high-speed civil transports (HSCT) is of great concern in the evaluation of the commercial development of such a transport. One of the potential environmental impacts of a high speed civilian transport is the sonic boom generated by the aircraft and its effects on the population, wildlife, and structures in the vicinity of its flight path. If an HSCT aircraft is restricted from flying overland routes due to excessive booms, the commercial feasibility of such a venture may be questionable. NASA has taken the lead in evaluating and resolving the issues surrounding the development of a high speed civilian transport through its High-Speed Research Program (HSRP). The present paper discusses the usage of a Computational Fluid Dynamics (CFD) nonlinear code in predicting the pressure signature and ultimately the sonic boom generated by a high speed civilian transport. NASA had designed, built, and wind tunnel tested two low boom configurations for flight at Mach 2 and Mach 3. Experimental data was taken at several distances from these models up to a body length from the axis of the aircraft. The near field experimental data serves as a test bed for computational fluid dynamic codes in evaluating their accuracy and reliability for predicting the behavior of future HSCT designs. Sonic boom prediction methodology exists which is based on modified linear theory. These methods can be used reliably if near field signatures are available at distances from the aircraft where nonlinear and three dimensional effects have diminished in importance. Up to the present time, the only reliable method to obtain this data was via the wind tunnel with costly model construction and testing. It is the intent of the present paper to apply a modified three dimensional Euler code to predict the near field signatures of the two low boom configurations recently tested by NASA.
Linear regression crash prediction models : issues and proposed solutions.
2010-05-01
The paper develops a linear regression model approach that can be applied to : crash data to predict vehicle crashes. The proposed approach involves novice data aggregation : to satisfy linear regression assumptions; namely error structure normality ...
SPORTS - a simple non-linear thermalhydraulic stability code
Chatoorgoon, V.
1986-01-01
A simple code, called SPORTS, has been developed for two-phase stability studies. A novel method of solution of the finite difference equations was deviced and incorporated, and many of the approximations that are common in other stability codes are avoided. SPORTS is believed to be accurate and efficient, as small and large time-steps are permitted, and hence suitable for micro-computers. (orig.)
Linear tree codes and the problem of explicit constructions
Pudlák, Pavel
2016-01-01
Roč. 490, February 1 (2016), s. 124-144 ISSN 0024-3795 R&D Projects: GA ČR GBP202/12/G061 Institutional support: RVO:67985840 Keywords : tree code * error correcting code * triangular totally nonsingular matrix Subject RIV: BA - General Mathematics Impact factor: 0.973, year: 2016 http://www.sciencedirect.com/science/article/pii/S002437951500645X
Vectorized Matlab Codes for Linear Two-Dimensional Elasticity
Jonas Koko
2007-01-01
Full Text Available A vectorized Matlab implementation for the linear finite element is provided for the two-dimensional linear elasticity with mixed boundary conditions. Vectorization means that there is no loop over triangles. Numerical experiments show that our implementation is more efficient than the standard implementation with a loop over all triangles.
Two "dual" families of Nearly-Linear Codes over ℤ p , p odd
Asch, van A.G.; Tilborg, van H.C.A.
2001-01-01
Since the paper by Hammons e.a. [1], various authors have shown an enormous interest in linear codes over the ring Z4. A special weight function on Z4 was introduced and by means of the so called Gray map ¿ : Z4¿Z2 2 a relation was established between linear codes over Z4 and certain interesting
Performance analysis of linear codes under maximum-likelihood decoding: a tutorial
Sason, Igal; Shamai, Shlomo
2006-01-01
..., upper and lower bounds on the error probability of linear codes under ML decoding are surveyed and applied to codes and ensembles of codes on graphs. For upper bounds, we discuss various bounds where focus is put on Gallager bounding techniques and their relation to a variety of other reported bounds. Within the class of lower bounds, we ad...
Rate-Compatible LDPC Codes with Linear Minimum Distance
Divsalar, Dariush; Jones, Christopher; Dolinar, Samuel
2009-01-01
A recently developed method of constructing protograph-based low-density parity-check (LDPC) codes provides for low iterative decoding thresholds and minimum distances proportional to block sizes, and can be used for various code rates. A code constructed by this method can have either fixed input block size or fixed output block size and, in either case, provides rate compatibility. The method comprises two submethods: one for fixed input block size and one for fixed output block size. The first mentioned submethod is useful for applications in which there are requirements for rate-compatible codes that have fixed input block sizes. These are codes in which only the numbers of parity bits are allowed to vary. The fixed-output-blocksize submethod is useful for applications in which framing constraints are imposed on the physical layers of affected communication systems. An example of such a system is one that conforms to one of many new wireless-communication standards that involve the use of orthogonal frequency-division modulation
Transitioning from interpretive to predictive in thermal hydraulic codes
Mousseau, V.A.
2004-01-01
simulation tools. These different computer codes have then been loosely coupled to represent the transient. It is important to note that the accuracy of the transient is determined by the largest error in the system. For example, if neutron diffusion and thermal conduction are each solved in a second order in time accurate manner, but they are only exchange information every five time steps, then the system is first order in time since the coupling is first order in time. Therefore, it is important to ensure that the level of accuracy used to couple two different computer codes is as accurate as the two codes being coupled. Focusing in on the reactor cooling system (the two phase flow and the heat conduction) it is important to solve the coupling between phases and the wall as accurately as possible. In RELAP these two pieces of nonlinearly coupled physics are solved in separate linear systems. The RELAP solution procedure is to take a nonlinear system of equations, split them into two separate pieces, linearize and solve the fluid flow and heat conduction separately, then couple them together in an explicit fashion. It should be noted that different versions of RELAP allow for linearly implicit coupling of the fluid flow and wall heat transfer under special conditions. This manuscript will examine the reactor cooling system and present an analysis of the error caused by linearizing and splitting nonlinearly coupled physics. Modern computers and numerical methods allow for this system of nonlinear equations to be solved without linearizing and splitting. This coupled approach is referred to as an implicitly balanced solution method. Because of the fact that future thermal hydraulic codes will be required to move from the low accuracy requirements of data interpretation to the high accuracy requirements of data prediction, the accuracy of current thermal hydraulic codes need to be increased. This manuscript provides some of the first steps required to analyze the temporal
Iterative solution of linear equations in ODE codes. [Krylov subspaces
Gear, C. W.; Saad, Y.
1981-01-01
Each integration step of a stiff equation involves the solution of a nonlinear equation, usually by a quasi-Newton method that leads to a set of linear problems. Iterative methods for these linear equations are studied. Of particular interest are methods that do not require an explicit Jacobian, but can work directly with differences of function values using J congruent to f(x + delta) - f(x). Some numerical experiments using a modification of LSODE are reported. 1 figure, 2 tables.
Deformation Prediction Using Linear Polynomial Functions ...
By Deformation, we mean change of shape of any structure from its original shape and by monitoring over time using Geodetic means, the change in shape, size and the overall structural dynamics behaviors of structure can be detected. Prediction is therefor based on the epochs measurement obtained during monitoring, ...
Super-linear Precision in Simple Neural Population Codes
Schwab, David; Fiete, Ila
2015-03-01
A widely used tool for quantifying the precision with which a population of noisy sensory neurons encodes the value of an external stimulus is the Fisher Information (FI). Maximizing the FI is also a commonly used objective for constructing optimal neural codes. The primary utility and importance of the FI arises because it gives, through the Cramer-Rao bound, the smallest mean-squared error achievable by any unbiased stimulus estimator. However, it is well-known that when neural firing is sparse, optimizing the FI can result in codes that perform very poorly when considering the resulting mean-squared error, a measure with direct biological relevance. Here we construct optimal population codes by minimizing mean-squared error directly and study the scaling properties of the resulting network, focusing on the optimal tuning curve width. We then extend our results to continuous attractor networks that maintain short-term memory of external stimuli in their dynamics. Here we find similar scaling properties in the structure of the interactions that minimize diffusive information loss.
Development of non-linear vibration analysis code for CANDU fuelling machine
Murakami, Hajime; Hirai, Takeshi; Horikoshi, Kiyomi; Mizukoshi, Kaoru; Takenaka, Yasuo; Suzuki, Norio.
1988-01-01
This paper describes the development of a non-linear, dynamic analysis code for the CANDU 600 fuelling machine (F-M), which includes a number of non-linearities such as gap with or without Coulomb friction, special multi-linear spring connections, etc. The capabilities and features of the code and the mathematical treatment for the non-linearities are explained. The modeling and numerical methodology for the non-linearities employed in the code are verified experimentally. Finally, the simulation analyses for the full-scale F-M vibration testing are carried out, and the applicability of the code to such multi-degree of freedom systems as F-M is demonstrated. (author)
Model Predictive Control for Linear Complementarity and Extended Linear Complementarity Systems
Bambang Riyanto
2005-11-01
Full Text Available In this paper, we propose model predictive control method for linear complementarity and extended linear complementarity systems by formulating optimization along prediction horizon as mixed integer quadratic program. Such systems contain interaction between continuous dynamics and discrete event systems, and therefore, can be categorized as hybrid systems. As linear complementarity and extended linear complementarity systems finds applications in different research areas, such as impact mechanical systems, traffic control and process control, this work will contribute to the development of control design method for those areas as well, as shown by three given examples.
Equidistant Linear Network Codes with maximal Error-protection from Veronese Varieties
Hansen, Johan P.
2012-01-01
Linear network coding transmits information in terms of a basis of a vector space and the information is received as a basis of a possible altered vectorspace. Ralf Koetter and Frank R. Kschischang in Coding for errors and erasures in random network coding (IEEE Transactions on Information Theory...... construct explicit families of vector-spaces of constant dimension where any pair of distinct vector-spaces are equidistant in the above metric. The parameters of the resulting linear network codes which have maximal error-protection are determined....
Predictive coding of dynamical variables in balanced spiking networks.
Boerlin, Martin; Machens, Christian K; Denève, Sophie
2013-01-01
Two observations about the cortex have puzzled neuroscientists for a long time. First, neural responses are highly variable. Second, the level of excitation and inhibition received by each neuron is tightly balanced at all times. Here, we demonstrate that both properties are necessary consequences of neural networks that represent information efficiently in their spikes. We illustrate this insight with spiking networks that represent dynamical variables. Our approach is based on two assumptions: We assume that information about dynamical variables can be read out linearly from neural spike trains, and we assume that neurons only fire a spike if that improves the representation of the dynamical variables. Based on these assumptions, we derive a network of leaky integrate-and-fire neurons that is able to implement arbitrary linear dynamical systems. We show that the membrane voltage of the neurons is equivalent to a prediction error about a common population-level signal. Among other things, our approach allows us to construct an integrator network of spiking neurons that is robust against many perturbations. Most importantly, neural variability in our networks cannot be equated to noise. Despite exhibiting the same single unit properties as widely used population code models (e.g. tuning curves, Poisson distributed spike trains), balanced networks are orders of magnitudes more reliable. Our approach suggests that spikes do matter when considering how the brain computes, and that the reliability of cortical representations could have been strongly underestimated.
Linear-time general decoding algorithm for the surface code
Darmawan, Andrew S.; Poulin, David
2018-05-01
A quantum error correcting protocol can be substantially improved by taking into account features of the physical noise process. We present an efficient decoder for the surface code which can account for general noise features, including coherences and correlations. We demonstrate that the decoder significantly outperforms the conventional matching algorithm on a variety of noise models, including non-Pauli noise and spatially correlated noise. The algorithm is based on an approximate calculation of the logical channel using a tensor-network description of the noisy state.
Large-scale linear programs in planning and prediction.
2017-06-01
Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...
Who Will Win?: Predicting the Presidential Election Using Linear Regression
Lamb, John H.
2007-01-01
This article outlines a linear regression activity that engages learners, uses technology, and fosters cooperation. Students generated least-squares linear regression equations using TI-83 Plus[TM] graphing calculators, Microsoft[C] Excel, and paper-and-pencil calculations using derived normal equations to predict the 2004 presidential election.…
Predictive Bias and Sensitivity in NRC Fuel Performance Codes
Geelhood, Kenneth J.; Luscher, Walter G.; Senor, David J.; Cunningham, Mitchel E.; Lanning, Donald D.; Adkins, Harold E.
2009-10-01
The latest versions of the fuel performance codes, FRAPCON-3 and FRAPTRAN were examined to determine if the codes are intrinsically conservative. Each individual model and type of code prediction was examined and compared to the data that was used to develop the model. In addition, a brief literature search was performed to determine if more recent data have become available since the original model development for model comparison.
Protograph based LDPC codes with minimum distance linearly growing with block size
Divsalar, Dariush; Jones, Christopher; Dolinar, Sam; Thorpe, Jeremy
2005-01-01
We propose several LDPC code constructions that simultaneously achieve good threshold and error floor performance. Minimum distance is shown to grow linearly with block size (similar to regular codes of variable degree at least 3) by considering ensemble average weight enumerators. Our constructions are based on projected graph, or protograph, structures that support high-speed decoder implementations. As with irregular ensembles, our constructions are sensitive to the proportion of degree-2 variable nodes. A code with too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code with too many such nodes tends to not exhibit a minimum distance that grows linearly in block length. In this paper we also show that precoding can be used to lower the threshold of regular LDPC codes. The decoding thresholds of the proposed codes, which have linearly increasing minimum distance in block size, outperform that of regular LDPC codes. Furthermore, a family of low to high rate codes, with thresholds that adhere closely to their respective channel capacity thresholds, is presented. Simulation results for a few example codes show that the proposed codes have low error floors as well as good threshold SNFt performance.
Predicting birth weight with conditionally linear transformation models.
Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten
2016-12-01
Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.
Montoye, Alexander H K; Begum, Munni; Henning, Zachary; Pfeiffer, Karin A
2017-02-01
This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression, linear mixed, and two ANN models. EE prediction accuracy was assessed using correlations, root mean square error (RMSE), and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements, there were no significant differences for correlations or RMSE between linear regression and linear mixed models (correlations: r = 0.71-0.88, RMSE: 1.11-1.61 METs; p > 0.05). For the thigh-worn accelerometer, there were no differences in correlations or RMSE between linear and ANN models (ANN-correlations: r = 0.89, RMSE: 1.07-1.08 METs. Linear models-correlations: r = 0.88, RMSE: 1.10-1.11 METs; p > 0.05). Conversely, one ANN had higher correlations and lower RMSE than both linear models for the hip (ANN-correlation: r = 0.88, RMSE: 1.12 METs. Linear models-correlations: r = 0.86, RMSE: 1.18-1.19 METs; p linear models for the wrist-worn accelerometers (ANN-correlations: r = 0.82-0.84, RMSE: 1.26-1.32 METs. Linear models-correlations: r = 0.71-0.73, RMSE: 1.55-1.61 METs; p models offer a significant improvement in EE prediction accuracy over linear models. Conversely, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh
Evolving a Dynamic Predictive Coding Mechanism for Novelty Detection
Haggett, Simon J.; Chu, Dominique; Marshall, Ian W.
2007-01-01
Novelty detection is a machine learning technique which identifies new or unknown information in data sets. We present our current work on the construction of a new novelty detector based on a dynamical version of predictive coding. We compare three evolutionary algorithms, a simple genetic algorithm, NEAT and FS-NEAT, for the task of optimising the structure of an illustrative dynamic predictive coding neural network to improve its performance over stimuli from a number of artificially gener...
Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes
Lin, Shu
1998-01-01
A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and
Implementation of neural network based non-linear predictive
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1998-01-01
The paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems including open loop unstable and non-minimum phase systems, but has also been proposed extended for the control of non......-linear systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi......-Newton optimization algorithm. The performance is demonstrated on a pneumatic servo system....
An online re-linearization scheme suited for Model Predictive and Linear Quadratic Control
Henriksen, Lars Christian; Poulsen, Niels Kjølstad
This technical note documents the equations for primal-dual interior-point quadratic programming problem solver used for MPC. The algorithm exploits the special structure of the MPC problem and is able to reduce the computational burden such that the computational burden scales with prediction...... horizon length in a linear way rather than cubic, which would be the case if the structure was not exploited. It is also shown how models used for design of model-based controllers, e.g. linear quadratic and model predictive, can be linearized both at equilibrium and non-equilibrium points, making...
Latency Performance of Encoding with Random Linear Network Coding
Nielsen, Lars; Hansen, René Rydhof; Lucani Rötter, Daniel Enrique
2018-01-01
the encoding process can be parallelized based on system requirements to reduce data access time within the system. Using a counting argument, we focus on predicting the effect of changes of generation (number of original packets) and symbol size (number of bytes per data packet) configurations on the encoding...... latency on full vector and on-the-fly algorithms. We show that the encoding latency doubles when either the generation size or the symbol size double and confirm this via extensive simulations. Although we show that the theoretical speed gain of on-the-fly over full vector is two, our measurements show...
Mihai-Victor PRICOP
2010-09-01
Full Text Available The present paper introduces a numerical approach of static linear elasticity equations for anisotropic materials. The domain and boundary conditions are simple, to enhance an easy implementation of the finite difference scheme. SOR and gradient are used to solve the resulting linear system. The simplicity of the geometry is also useful for MPI parallelization of the code.
Proceedings of the conference on computer codes and the linear accelerator community
Cooper, R.K.
1990-07-01
The conference whose proceedings you are reading was envisioned as the second in a series, the first having been held in San Diego in January 1988. The intended participants were those people who are actively involved in writing and applying computer codes for the solution of problems related to the design and construction of linear accelerators. The first conference reviewed many of the codes both extant and under development. This second conference provided an opportunity to update the status of those codes, and to provide a forum in which emerging new 3D codes could be described and discussed. The afternoon poster session on the second day of the conference provided an opportunity for extended discussion. All in all, this conference was felt to be quite a useful interchange of ideas and developments in the field of 3D calculations, parallel computation, higher-order optics calculations, and code documentation and maintenance for the linear accelerator community. A third conference is planned
Proceedings of the conference on computer codes and the linear accelerator community
Cooper, R.K. (comp.)
1990-07-01
The conference whose proceedings you are reading was envisioned as the second in a series, the first having been held in San Diego in January 1988. The intended participants were those people who are actively involved in writing and applying computer codes for the solution of problems related to the design and construction of linear accelerators. The first conference reviewed many of the codes both extant and under development. This second conference provided an opportunity to update the status of those codes, and to provide a forum in which emerging new 3D codes could be described and discussed. The afternoon poster session on the second day of the conference provided an opportunity for extended discussion. All in all, this conference was felt to be quite a useful interchange of ideas and developments in the field of 3D calculations, parallel computation, higher-order optics calculations, and code documentation and maintenance for the linear accelerator community. A third conference is planned.
Object-Oriented Parallel Particle-in-Cell Code for Beam Dynamics Simulation in Linear Accelerators
Qiang, J.; Ryne, R.D.; Habib, S.; Decky, V.
1999-01-01
In this paper, we present an object-oriented three-dimensional parallel particle-in-cell code for beam dynamics simulation in linear accelerators. A two-dimensional parallel domain decomposition approach is employed within a message passing programming paradigm along with a dynamic load balancing. Implementing object-oriented software design provides the code with better maintainability, reusability, and extensibility compared with conventional structure based code. This also helps to encapsulate the details of communications syntax. Performance tests on SGI/Cray T3E-900 and SGI Origin 2000 machines show good scalability of the object-oriented code. Some important features of this code also include employing symplectic integration with linear maps of external focusing elements and using z as the independent variable, typical in accelerators. A successful application was done to simulate beam transport through three superconducting sections in the APT linac design
Nonlinear to Linear Elastic Code Coupling in 2-D Axisymmetric Media.
Preston, Leiph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-08-01
Explosions within the earth nonlinearly deform the local media, but at typical seismological observation distances, the seismic waves can be considered linear. Although nonlinear algorithms can simulate explosions in the very near field well, these codes are computationally expensive and inaccurate at propagating these signals to great distances. A linearized wave propagation code, coupled to a nonlinear code, provides an efficient mechanism to both accurately simulate the explosion itself and to propagate these signals to distant receivers. To this end we have coupled Sandia's nonlinear simulation algorithm CTH to a linearized elastic wave propagation code for 2-D axisymmetric media (axiElasti) by passing information from the nonlinear to the linear code via time-varying boundary conditions. In this report, we first develop the 2-D axisymmetric elastic wave equations in cylindrical coordinates. Next we show how we design the time-varying boundary conditions passing information from CTH to axiElasti, and finally we demonstrate the coupling code via a simple study of the elastic radius.
Modelling and Predicting Backstroke Start Performance Using Non-Linear and Linear Models.
de Jesus, Karla; Ayala, Helon V H; de Jesus, Kelly; Coelho, Leandro Dos S; Medeiros, Alexandre I A; Abraldes, José A; Vaz, Mário A P; Fernandes, Ricardo J; Vilas-Boas, João Paulo
2018-03-01
Our aim was to compare non-linear and linear mathematical model responses for backstroke start performance prediction. Ten swimmers randomly completed eight 15 m backstroke starts with feet over the wedge, four with hands on the highest horizontal and four on the vertical handgrip. Swimmers were videotaped using a dual media camera set-up, with the starts being performed over an instrumented block with four force plates. Artificial neural networks were applied to predict 5 m start time using kinematic and kinetic variables and to determine the accuracy of the mean absolute percentage error. Artificial neural networks predicted start time more robustly than the linear model with respect to changing training to the validation dataset for the vertical handgrip (3.95 ± 1.67 vs. 5.92 ± 3.27%). Artificial neural networks obtained a smaller mean absolute percentage error than the linear model in the horizontal (0.43 ± 0.19 vs. 0.98 ± 0.19%) and vertical handgrip (0.45 ± 0.19 vs. 1.38 ± 0.30%) using all input data. The best artificial neural network validation revealed a smaller mean absolute error than the linear model for the horizontal (0.007 vs. 0.04 s) and vertical handgrip (0.01 vs. 0.03 s). Artificial neural networks should be used for backstroke 5 m start time prediction due to the quite small differences among the elite level performances.
Background-Modeling-Based Adaptive Prediction for Surveillance Video Coding.
Zhang, Xianguo; Huang, Tiejun; Tian, Yonghong; Gao, Wen
2014-02-01
The exponential growth of surveillance videos presents an unprecedented challenge for high-efficiency surveillance video coding technology. Compared with the existing coding standards that were basically developed for generic videos, surveillance video coding should be designed to make the best use of the special characteristics of surveillance videos (e.g., relative static background). To do so, this paper first conducts two analyses on how to improve the background and foreground prediction efficiencies in surveillance video coding. Following the analysis results, we propose a background-modeling-based adaptive prediction (BMAP) method. In this method, all blocks to be encoded are firstly classified into three categories. Then, according to the category of each block, two novel inter predictions are selectively utilized, namely, the background reference prediction (BRP) that uses the background modeled from the original input frames as the long-term reference and the background difference prediction (BDP) that predicts the current data in the background difference domain. For background blocks, the BRP can effectively improve the prediction efficiency using the higher quality background as the reference; whereas for foreground-background-hybrid blocks, the BDP can provide a better reference after subtracting its background pixels. Experimental results show that the BMAP can achieve at least twice the compression ratio on surveillance videos as AVC (MPEG-4 Advanced Video Coding) high profile, yet with a slightly additional encoding complexity. Moreover, for the foreground coding performance, which is crucial to the subjective quality of moving objects in surveillance videos, BMAP also obtains remarkable gains over several state-of-the-art methods.
Selecting Optimal Parameters of Random Linear Network Coding for Wireless Sensor Networks
Heide, J; Zhang, Qi; Fitzek, F H P
2013-01-01
This work studies how to select optimal code parameters of Random Linear Network Coding (RLNC) in Wireless Sensor Networks (WSNs). With Rateless Deluge [1] the authors proposed to apply Network Coding (NC) for Over-the-Air Programming (OAP) in WSNs, and demonstrated that with NC a significant...... reduction in the number of transmitted packets can be achieved. However, NC introduces additional computations and potentially a non-negligible transmission overhead, both of which depend on the chosen coding parameters. Therefore it is necessary to consider the trade-off that these coding parameters...... present in order to obtain the lowest energy consumption per transmitted bit. This problem is analyzed and suitable coding parameters are determined for the popular Tmote Sky platform. Compared to the use of traditional RLNC, these parameters enable a reduction in the energy spent per bit which grows...
STACK DECODING OF LINEAR BLOCK CODES FOR DISCRETE MEMORYLESS CHANNEL USING TREE DIAGRAM
H. Prashantha Kumar
2012-03-01
Full Text Available The boundaries between block and convolutional codes have become diffused after recent advances in the understanding of the trellis structure of block codes and the tail-biting structure of some convolutional codes. Therefore, decoding algorithms traditionally proposed for decoding convolutional codes have been applied for decoding certain classes of block codes. This paper presents the decoding of block codes using tree structure. Many good block codes are presently known. Several of them have been used in applications ranging from deep space communication to error control in storage systems. But the primary difficulty with applying Viterbi or BCJR algorithms to decode of block codes is that, even though they are optimum decoding methods, the promised bit error rates are not achieved in practice at data rates close to capacity. This is because the decoding effort is fixed and grows with block length, and thus only short block length codes can be used. Therefore, an important practical question is whether a suboptimal realizable soft decision decoding method can be found for block codes. A noteworthy result which provides a partial answer to this question is described in the following sections. This result of near optimum decoding will be used as motivation for the investigation of different soft decision decoding methods for linear block codes which can lead to the development of efficient decoding algorithms. The code tree can be treated as an expanded version of the trellis, where every path is totally distinct from every other path. We have derived the tree structure for (8, 4 and (16, 11 extended Hamming codes and have succeeded in implementing the soft decision stack algorithm to decode them. For the discrete memoryless channel, gains in excess of 1.5dB at a bit error rate of 10-5 with respect to conventional hard decision decoding are demonstrated for these codes.
Real coded genetic algorithm for fuzzy time series prediction
Jain, Shilpa; Bisht, Dinesh C. S.; Singh, Phool; Mathpal, Prakash C.
2017-10-01
Genetic Algorithm (GA) forms a subset of evolutionary computing, rapidly growing area of Artificial Intelligence (A.I.). Some variants of GA are binary GA, real GA, messy GA, micro GA, saw tooth GA, differential evolution GA. This research article presents a real coded GA for predicting enrollments of University of Alabama. Data of Alabama University is a fuzzy time series. Here, fuzzy logic is used to predict enrollments of Alabama University and genetic algorithm optimizes fuzzy intervals. Results are compared to other eminent author works and found satisfactory, and states that real coded GA are fast and accurate.
Eric Z. Chen
2015-01-01
Full Text Available Error control codes have been widely used in data communications and storage systems. One central problem in coding theory is to optimize the parameters of a linear code and construct codes with best possible parameters. There are tables of best-known linear codes over finite fields of sizes up to 9. Recently, there has been a growing interest in codes over $\\mathbb{F}_{13}$ and other fields of size greater than 9. The main purpose of this work is to present a database of best-known linear codes over the field $\\mathbb{F}_{13}$ together with upper bounds on the minimum distances. To find good linear codes to establish lower bounds on minimum distances, an iterative heuristic computer search algorithm is employed to construct quasi-twisted (QT codes over the field $\\mathbb{F}_{13}$ with high minimum distances. A large number of new linear codes have been found, improving previously best-known results. Tables of $[pm, m]$ QT codes over $\\mathbb{F}_{13}$ with best-known minimum distances as well as a table of lower and upper bounds on the minimum distances for linear codes of length up to 150 and dimension up to 6 are presented.
EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.
Lian, Yao; Ge, Meng; Pan, Xian-Ming
2014-12-19
B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task. In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR). A 10-fold cross-validation test on a large non-redundant dataset was performed to evaluate the performance of our model. To alleviate the problem caused by the noise of negative dataset, 300 experiments utilizing 300 sub-datasets were performed. We achieved overall sensitivity of 81.8%, precision of 64.1% and area under the receiver operating characteristic curve (AUC) of 0.728. We have presented a reliable method for the identification of linear B cell epitope using antigen's primary sequence information. Moreover, a web server EPMLR has been developed for linear B-cell epitope prediction: http://www.bioinfo.tsinghua.edu.cn/epitope/EPMLR/ .
Validation of Individual Non-Linear Predictive Pharmacokinetic ...
3Department of Veterinary Medicine, Faculty of Agriculture, University of Novi Sad, Novi Sad, Republic of Serbia ... Purpose: To evaluate the predictive performance of phenytoin multiple dosing non-linear pharmacokinetic ... status epilepticus affects an estimated 152,000 ..... causal factors, i.e., infection, inflammation, tissue.
Neural Generalized Predictive Control of a non-linear Process
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1998-01-01
The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability qu...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem.......The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial...
Implementation of neural network based non-linear predictive control
Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole
1999-01-01
This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...... on an efficient quasi-Newton algorithm. The performance is demonstrated on a pneumatic servo system....
Decision-making in schizophrenia: A predictive-coding perspective.
Sterzer, Philipp; Voss, Martin; Schlagenhauf, Florian; Heinz, Andreas
2018-05-31
Dysfunctional decision-making has been implicated in the positive and negative symptoms of schizophrenia. Decision-making can be conceptualized within the framework of hierarchical predictive coding as the result of a Bayesian inference process that uses prior beliefs to infer states of the world. According to this idea, prior beliefs encoded at higher levels in the brain are fed back as predictive signals to lower levels. Whenever these predictions are violated by the incoming sensory data, a prediction error is generated and fed forward to update beliefs encoded at higher levels. Well-documented impairments in cognitive decision-making support the view that these neural inference mechanisms are altered in schizophrenia. There is also extensive evidence relating the symptoms of schizophrenia to aberrant signaling of prediction errors, especially in the domain of reward and value-based decision-making. Moreover, the idea of altered predictive coding is supported by evidence for impaired low-level sensory mechanisms and motor processes. We review behavioral and neural findings from these research areas and provide an integrated view suggesting that schizophrenia may be related to a pervasive alteration in predictive coding at multiple hierarchical levels, including cognitive and value-based decision-making processes as well as sensory and motor systems. We relate these findings to decision-making processes and propose that varying degrees of impairment in the implicated brain areas contribute to the variety of psychotic experiences. Copyright © 2018 Elsevier Inc. All rights reserved.
Linear-Time Non-Malleable Codes in the Bit-Wise Independent Tampering Model
Cramer, Ronald; Damgård, Ivan Bjerre; Döttling, Nico
Non-malleable codes were introduced by Dziembowski et al. (ICS 2010) as coding schemes that protect a message against tampering attacks. Roughly speaking, a code is non-malleable if decoding an adversarially tampered encoding of a message m produces the original message m or a value m' (eventuall...... non-malleable codes of Agrawal et al. (TCC 2015) and of Cher- aghchi and Guruswami (TCC 2014) and improves the previous result in the bit-wise tampering model: it builds the first non-malleable codes with linear-time complexity and optimal-rate (i.e. rate 1 - o(1)).......Non-malleable codes were introduced by Dziembowski et al. (ICS 2010) as coding schemes that protect a message against tampering attacks. Roughly speaking, a code is non-malleable if decoding an adversarially tampered encoding of a message m produces the original message m or a value m' (eventually...... abort) completely unrelated with m. It is known that non-malleability is possible only for restricted classes of tampering functions. Since their introduction, a long line of works has established feasibility results of non-malleable codes against different families of tampering functions. However...
Isometries and binary images of linear block codes over ℤ4 + uℤ4 and ℤ8 + uℤ8
Sison, Virgilio; Remillion, Monica
2017-10-01
Let {{{F}}}2 be the binary field and ℤ2 r the residue class ring of integers modulo 2 r , where r is a positive integer. For the finite 16-element commutative local Frobenius non-chain ring ℤ4 + uℤ4, where u is nilpotent of index 2, two weight functions are considered, namely the Lee weight and the homogeneous weight. With the appropriate application of these weights, isometric maps from ℤ4 + uℤ4 to the binary spaces {{{F}}}24 and {{{F}}}28, respectively, are established via the composition of other weight-based isometries. The classical Hamming weight is used on the binary space. The resulting isometries are then applied to linear block codes over ℤ4+ uℤ4 whose images are binary codes of predicted length, which may or may not be linear. Certain lower and upper bounds on the minimum distances of the binary images are also derived in terms of the parameters of the ℤ4 + uℤ4 codes. Several new codes and their images are constructed as illustrative examples. An analogous procedure is performed successfully on the ring ℤ8 + uℤ8, where u 2 = 0, which is a commutative local Frobenius non-chain ring of order 64. It turns out that the method is possible in general for the class of rings ℤ2 r + uℤ2 r , where u 2 = 0, for any positive integer r, using the generalized Gray map from ℤ2 r to {{{F}}}2{2r-1}.
Linear calculations of edge current driven kink modes with BOUT++ code
Li, G. Q., E-mail: ligq@ipp.ac.cn; Xia, T. Y. [Institute of Plasma Physics, CAS, Hefei, Anhui 230031 (China); Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Xu, X. Q. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); Snyder, P. B.; Turnbull, A. D. [General Atomics, San Diego, California 92186 (United States); Ma, C. H.; Xi, P. W. [Lawrence Livermore National Laboratory, Livermore, California 94550 (United States); FSC, School of Physics, Peking University, Beijing 100871 (China)
2014-10-15
This work extends previous BOUT++ work to systematically study the impact of edge current density on edge localized modes, and to benchmark with the GATO and ELITE codes. Using the CORSICA code, a set of equilibria was generated with different edge current densities by keeping total current and pressure profile fixed. Based on these equilibria, the effects of the edge current density on the MHD instabilities were studied with the 3-field BOUT++ code. For the linear calculations, with increasing edge current density, the dominant modes are changed from intermediate-n and high-n ballooning modes to low-n kink modes, and the linear growth rate becomes smaller. The edge current provides stabilizing effects on ballooning modes due to the increase of local shear at the outer mid-plane with the edge current. For edge kink modes, however, the edge current does not always provide a destabilizing effect; with increasing edge current, the linear growth rate first increases, and then decreases. In benchmark calculations for BOUT++ against the linear results with the GATO and ELITE codes, the vacuum model has important effects on the edge kink mode calculations. By setting a realistic density profile and Spitzer resistivity profile in the vacuum region, the resistivity was found to have a destabilizing effect on both the kink mode and on the ballooning mode. With diamagnetic effects included, the intermediate-n and high-n ballooning modes can be totally stabilized for finite edge current density.
Bounded distance decoding of linear error-correcting codes with Gröbner bases
Bulygin, S.; Pellikaan, G.R.
2009-01-01
The problem of bounded distance decoding of arbitrary linear codes using Gröbner bases is addressed. A new method is proposed, which is based on reducing an initial decoding problem to solving a certain system of polynomial equations over a finite field. The peculiarity of this system is that, when
Linear calculations of edge current driven kink modes with BOUT++ code
Li, G. Q.; Xia, T. Y.; Xu, X. Q.; Snyder, P. B.; Turnbull, A. D.; Ma, C. H.; Xi, P. W.
2014-01-01
This work extends previous BOUT++ work to systematically study the impact of edge current density on edge localized modes, and to benchmark with the GATO and ELITE codes. Using the CORSICA code, a set of equilibria was generated with different edge current densities by keeping total current and pressure profile fixed. Based on these equilibria, the effects of the edge current density on the MHD instabilities were studied with the 3-field BOUT++ code. For the linear calculations, with increasing edge current density, the dominant modes are changed from intermediate-n and high-n ballooning modes to low-n kink modes, and the linear growth rate becomes smaller. The edge current provides stabilizing effects on ballooning modes due to the increase of local shear at the outer mid-plane with the edge current. For edge kink modes, however, the edge current does not always provide a destabilizing effect; with increasing edge current, the linear growth rate first increases, and then decreases. In benchmark calculations for BOUT++ against the linear results with the GATO and ELITE codes, the vacuum model has important effects on the edge kink mode calculations. By setting a realistic density profile and Spitzer resistivity profile in the vacuum region, the resistivity was found to have a destabilizing effect on both the kink mode and on the ballooning mode. With diamagnetic effects included, the intermediate-n and high-n ballooning modes can be totally stabilized for finite edge current density
Throughput vs. Delay in Lossy Wireless Mesh Networks with Random Linear Network Coding
Hundebøll, Martin; Pahlevani, Peyman; Roetter, Daniel Enrique Lucani
2014-01-01
This work proposes a new protocol applying on– the–fly random linear network coding in wireless mesh net- works. The protocol provides increased reliability, low delay, and high throughput to the upper layers, while being oblivious to their specific requirements. This seemingly conflicting goals ...
Solving linear systems in FLICA-4, thermohydraulic code for 3-D transient computations
Allaire, G.
1995-01-01
FLICA-4 is a computer code, developed at the CEA (France), devoted to steady state and transient thermal-hydraulic analysis of nuclear reactor cores, for small size problems (around 100 mesh cells) as well as for large ones (more than 100000), on, either standard workstations or vector super-computers. As for time implicit codes, the largest time and memory consuming part of FLICA-4 is the routine dedicated to solve the linear system (the size of which is of the order of the number of cells). Therefore, the efficiency of the code is crucially influenced by the optimization of the algorithms used in assembling and solving linear systems: direct methods as the Gauss (or LU) decomposition for moderate size problems, iterative methods as the preconditioned conjugate gradient for large problems. 6 figs., 13 refs
Predictive coding of music--brain responses to rhythmic incongruity.
Vuust, Peter; Ostergaard, Leif; Pallesen, Karen Johanne; Bailey, Christopher; Roepstorff, Andreas
2009-01-01
During the last decades, models of music processing in the brain have mainly discussed the specificity of brain modules involved in processing different musical components. We argue that predictive coding offers an explanatory framework for functional integration in musical processing. Further, we provide empirical evidence for such a network in the analysis of event-related MEG-components to rhythmic incongruence in the context of strong metric anticipation. This is seen in a mismatch negativity (MMNm) and a subsequent P3am component, which have the properties of an error term and a subsequent evaluation in a predictive coding framework. There were both quantitative and qualitative differences in the evoked responses in expert jazz musicians compared with rhythmically unskilled non-musicians. We propose that these differences trace a functional adaptation and/or a genetic pre-disposition in experts which allows for a more precise rhythmic prediction.
Ramani, D.T.
1977-01-01
The 'INTRANS' system is a general purpose computer code, designed to perform linear and non-linear structural stress and deflection analysis of impacting or non-impacting nuclear reactor internals components coupled with reactor vessel, shield building and external as well as internal gapped spring support system. This paper describes in general a unique computational procedure for evaluating the dynamic response of reactor internals, descretised as beam and lumped mass structural system and subjected to external transient loads such as seismic and LOCA time-history forces. The computational procedure is outlined in the INTRANS code, which computes component flexibilities of a discrete lumped mass planar model of reactor internals by idealising an assemblage of finite elements consisting of linear elastic beams with bending, torsional and shear stiffnesses interacted with external or internal linear as well as non-linear multi-gapped spring support system. The method of analysis is based on the displacement method and the code uses the fourth-order Runge-Kutta numerical integration technique as a basis for solution of dynamic equilibrium equations of motion for the system. During the computing process, the dynamic response of each lumped mass is calculated at specific instant of time using well-known step-by-step procedure. At any instant of time then, the transient dynamic motions of the system are held stationary and based on the predicted motions and internal forces of the previous instant. From which complete response at any time-step of interest may then be computed. Using this iterative process, the relationship between motions and internal forces is satisfied step by step throughout the time interval
Fitzek, Frank; Toth, Tamas; Szabados, Áron
2014-01-01
This paper advocates the use of random linear network coding for storage in distributed clouds in order to reduce storage and traffic costs in dynamic settings, i.e. when adding and removing numerous storage devices/clouds on-the-fly and when the number of reachable clouds is limited. We introduce...... various network coding approaches that trade-off reliability, storage and traffic costs, and system complexity relying on probabilistic recoding for cloud regeneration. We compare these approaches with other approaches based on data replication and Reed-Solomon codes. A simulator has been developed...... to carry out a thorough performance evaluation of the various approaches when relying on different system settings, e.g., finite fields, and network/storage conditions, e.g., storage space used per cloud, limited network use, and limited recoding capabilities. In contrast to standard coding approaches, our...
Linear and nonlinear dynamic systems in financial time series prediction
Salim Lahmiri
2012-10-01
Full Text Available Autoregressive moving average (ARMA process and dynamic neural networks namely the nonlinear autoregressive moving average with exogenous inputs (NARX are compared by evaluating their ability to predict financial time series; for instance the S&P500 returns. Two classes of ARMA are considered. The first one is the standard ARMA model which is a linear static system. The second one uses Kalman filter (KF to estimate and predict ARMA coefficients. This model is a linear dynamic system. The forecasting ability of each system is evaluated by means of mean absolute error (MAE and mean absolute deviation (MAD statistics. Simulation results indicate that the ARMA-KF system performs better than the standard ARMA alone. Thus, introducing dynamics into the ARMA process improves the forecasting accuracy. In addition, the ARMA-KF outperformed the NARX. This result may suggest that the linear component found in the S&P500 return series is more dominant than the nonlinear part. In sum, we conclude that introducing dynamics into the ARMA process provides an effective system for S&P500 time series prediction.
DYMEL code for prediction of dynamic stability limits in boilers
Deam, R.T.
1980-01-01
Theoretical and experimental studies of Hydrodynamic Instability in boilers were undertaken to resolve the uncertainties of the existing predictive methods at the time the first Advanced Gas Cooled Reactor (AGR) plant was commissioned. The experiments were conducted on a full scale electrical simulation of an AGR boiler and revealed inadequacies in existing methods. As a result a new computer code called DYMEL was developed based on linearisation and Fourier/Laplace Transformation of the one-dimensional boiler equations in both time and space. Beside giving good agreement with local experimental data, the DYMEL code has since shown agreement with stability data from the plant, sodium heated helical tubes, a gas heated helical tube and an electrically heated U-tube. The code is now used widely within the U.K. (author)
Void fraction prediction of NUPEC PSBT tests by CATHARE code
Del Nevo, A.; Michelotti, L.; Moretti, F.; Rozzia, D.; D'Auria, F.
2011-01-01
The current generation of thermal-hydraulic system codes benefits of about sixty years of experiments and forty years of development and are considered mature tools to provide best estimate description of phenomena and detailed reactor system representations. However, there are continuous needs for checking the code capabilities in representing nuclear system, for drawing attention to their weak points, for identifying models which need to be refined for best-estimate calculations. Prediction of void fraction and Departure from Nucleate Boiling (DNB) in system thermal-hydraulics is currently based on empirical approaches. The database carried out by Nuclear Power Engineering Corporation (NUPEC), Japan addresses these issues. It is suitable for supporting the development of new computational tools based on more mechanistic approaches (i.e. three-field codes, two-phase CFD, etc.) as well as for validating current generation of thermal-hydraulic system codes. Selected experiments belonging to this database are used for the OECD/NRC PSBT benchmark. The paper reviews the activity carried out by CATHARE2 code on the basis of the subchannel (four test sections) and presents rod bundle (different axial power profile and test sections) experiments available in the database in steady state and transient conditions. The results demonstrate the accuracy of the code in predicting the void fraction in different thermal-hydraulic conditions. The tests are performed varying the pressure, coolant temperature, mass flow and power. Sensitivity analyses are carried out addressing nodalization effect and the influence of the initial and boundary conditions of the tests. (author)
Comparison of the nuclear code systems LINEAR-RECENT-NJOY and NJOY
Seehusen, J.
1983-07-01
The reconstructed cross sections of the code systems LINEAR-RECENT-GROUPIE (Version 1982) and NJOY (Version 1982) have been compared for several materials. Some fuel cycle isotopes and structural materials of the ENDF/B-4 general purpose and ENDF/B-5 dosimetry files have been choosen. The reconstructed total, capture and fission cross sections calculated by LINEAR-RECENT and NJOY have been analized. The two sets of pointwise cross sections differ significantly. Another disagreement was found in the transformation of ENDF/B-4 and 5 files into data with a linear interpolation scheme. Unshielded multigroup constants at O 0 K (620 groups, SANDII) have been calculated by the three code systems LINEAR-RECENT-GROUPIE, NJOY and RESEND5-INTEND. The code system RESEND5-INTEND calculates wrong group constants and should not be used any more. The two sets of group constants obtained from ENDF/B-4 data using GROUPIE and NJOY differ for some group constants by more than 2%. Some disagreements at low energies (10 -3 -eV) of the total cross section of Na-23 and Al-27 are difficult to understand. For ENDF/B-5 dosimetry data the capture group constants differ significantly. (Author) [pt
Non-linear aeroelastic prediction for aircraft applications
de C. Henshaw, M. J.; Badcock, K. J.; Vio, G. A.; Allen, C. B.; Chamberlain, J.; Kaynes, I.; Dimitriadis, G.; Cooper, J. E.; Woodgate, M. A.; Rampurawala, A. M.; Jones, D.; Fenwick, C.; Gaitonde, A. L.; Taylor, N. V.; Amor, D. S.; Eccles, T. A.; Denley, C. J.
2007-05-01
Current industrial practice for the prediction and analysis of flutter relies heavily on linear methods and this has led to overly conservative design and envelope restrictions for aircraft. Although the methods have served the industry well, it is clear that for a number of reasons the inclusion of non-linearity in the mathematical and computational aeroelastic prediction tools is highly desirable. The increase in available and affordable computational resources, together with major advances in algorithms, mean that non-linear aeroelastic tools are now viable within the aircraft design and qualification environment. The Partnership for Unsteady Methods in Aerodynamics (PUMA) Defence and Aerospace Research Partnership (DARP) was sponsored in 2002 to conduct research into non-linear aeroelastic prediction methods and an academic, industry, and government consortium collaborated to address the following objectives: To develop useable methodologies to model and predict non-linear aeroelastic behaviour of complete aircraft. To evaluate the methodologies on real aircraft problems. To investigate the effect of non-linearities on aeroelastic behaviour and to determine which have the greatest effect on the flutter qualification process. These aims have been very effectively met during the course of the programme and the research outputs include: New methods available to industry for use in the flutter prediction process, together with the appropriate coaching of industry engineers. Interesting results in both linear and non-linear aeroelastics, with comprehensive comparison of methods and approaches for challenging problems. Additional embryonic techniques that, with further research, will further improve aeroelastics capability. This paper describes the methods that have been developed and how they are deployable within the industrial environment. We present a thorough review of the PUMA aeroelastics programme together with a comprehensive review of the relevant research
Least-Square Prediction for Backward Adaptive Video Coding
Li Xin
2006-01-01
Full Text Available Almost all existing approaches towards video coding exploit the temporal redundancy by block-matching-based motion estimation and compensation. Regardless of its popularity, block matching still reflects an ad hoc understanding of the relationship between motion and intensity uncertainty models. In this paper, we present a novel backward adaptive approach, named "least-square prediction" (LSP, and demonstrate its potential in video coding. Motivated by the duality between edge contour in images and motion trajectory in video, we propose to derive the best prediction of the current frame from its causal past using least-square method. It is demonstrated that LSP is particularly effective for modeling video material with slow motion and can be extended to handle fast motion by temporal warping and forward adaptation. For typical QCIF test sequences, LSP often achieves smaller MSE than , full-search, quarter-pel block matching algorithm (BMA without the need of transmitting any overhead.
Evaluation of the MMCLIFE 3.0 code in predicting crack growth in titanium aluminide composites
Harmon, D.; Larsen, J.M.
1999-01-01
Crack growth and fatigue life predictions made with the MMCLIFE 3.0 code are compared to test data for unidirectional, continuously reinforced SCS-6/Ti-14Al-21Nb (wt pct) composite laminates. The MMCLIFE 3.0 analysis package is a design tool capable of predicting strength and fatigue performance in metal matrix composite (MMC) laminates. The code uses a combination of micromechanic lamina and macromechanic laminate analyses to predict stresses and uses linear elastic fracture mechanics to predict crack growth. The crack growth analysis includes a fiber bridging model to predict the growth of matrix flaws in 0 degree laminates and is capable of predicting the effects of interfacial shear stress and thermal residual stresses. The code has also been modified to include edge-notch flaws in addition to center-notch flaws. The model was correlated with constant amplitude, isothermal data from crack growth tests conducted on 0- and 90 degree SCS-6/Ti-14-21 laminates. Spectrum fatigue tests were conducted, which included dwell times and frequency effects. Strengths and areas for improvement for the analysis are discussed
Kirillov, Igor R.; Obukhov, Denis M.; Ogorodnikov, Anatoly P.; Araseki, Hideo
2004-01-01
The paper describes and compares three computer codes that are able to estimate the double-supply-frequency (DSF) pulsations in annular linear induction pumps (ALIPs). The DSF pulsations are the result of interaction of the magnetic field and induced in liquid metal currents both changing with supply-frequency. They may be of some concern for electromagnetic pumps (EMP) exploitation and need to be evaluated at their design. The results of computer simulation are compared with experimental ones for annular linear induction pump ALIP-1
Development of a 3D non-linear implicit MHD code
Nicolas, T.; Ichiguchi, K.
2016-06-01
This paper details the on-going development of a 3D non-linear implicit MHD code, which aims at making possible large scale simulations of the non-linear phase of the interchange mode. The goal of the paper is to explain the rationale behind the choices made along the development, and the technical difficulties encountered. At the present stage, the development of the code has not been completed yet. Most of the discussion is concerned with the first approach, which utilizes cartesian coordinates in the poloidal plane. This approach shows serious difficulties in writing the preconditioner, closely related to the choice of coordinates. A second approach, based on curvilinear coordinates, also faced significant difficulties, which are detailed. The third and last approach explored involves unstructured tetrahedral grids, and indicates the possibility to solve the problem. The issue to domain meshing is addressed. (author)
New approach to derive linear power/burnup history input for CANDU fuel codes
Lac Tang, T.; Richards, M.; Parent, G.
2003-01-01
The fuel element linear power / burnup history is a required input for the ELESTRES code in order to simulate CANDU fuel behavior during normal operating conditions and also to provide input for the accident analysis codes ELOCA and SOURCE. The purpose of this paper is to present a new approach to derive 'true', or at least more realistic linear power / burnup histories. Such an approach can be used to recreate any typical bundle power history if only a single pair of instantaneous values of bundle power and burnup, together with the position in the channel, are known. The histories obtained could be useful to perform more realistic simulations for safety analyses for cases where the reference (overpower) history is not appropriate. (author)
Technical note: A linear model for predicting δ13 Cprotein.
Pestle, William J; Hubbe, Mark; Smith, Erin K; Stevenson, Joseph M
2015-08-01
Development of a model for the prediction of δ(13) Cprotein from δ(13) Ccollagen and Δ(13) Cap-co . Model-generated values could, in turn, serve as "consumer" inputs for multisource mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ(13) Cprotein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ(13) Cco and Δ(13) Cap-co ). Regression analysis resulted in a two-term linear model (δ(13) Cprotein (%) = (0.78 × δ(13) Cco ) - (0.58× Δ(13) Cap-co ) - 4.7), possessing a high R-value of 0.93 (r(2) = 0.86, P analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. © 2015 Wiley Periodicals, Inc.
Throughput vs. Delay in Lossy Wireless Mesh Networks with Random Linear Network Coding
Hundebøll, Martin; Pahlevani, Peyman; Roetter, Daniel Enrique Lucani; Fitzek, Frank
2014-01-01
This work proposes a new protocol applying on–the–fly random linear network coding in wireless mesh net-works. The protocol provides increased reliability, low delay,and high throughput to the upper layers, while being obliviousto their specific requirements. This seemingly conflicting goalsare achieved by design, using an on–the–fly network codingstrategy. Our protocol also exploits relay nodes to increasethe overall performance of individual links. Since our protocolnaturally masks random p...
Rate-compatible protograph LDPC code families with linear minimum distance
Divsalar, Dariush (Inventor); Dolinar, Jr., Samuel J. (Inventor); Jones, Christopher R. (Inventor)
2012-01-01
Digital communication coding methods are shown, which generate certain types of low-density parity-check (LDPC) codes built from protographs. A first method creates protographs having the linear minimum distance property and comprising at least one variable node with degree less than 3. A second method creates families of protographs of different rates, all structurally identical for all rates except for a rate-dependent designation of certain variable nodes as transmitted or non-transmitted. A third method creates families of protographs of different rates, all structurally identical for all rates except for a rate-dependent designation of the status of certain variable nodes as non-transmitted or set to zero. LDPC codes built from the protographs created by these methods can simultaneously have low error floors and low iterative decoding thresholds.
Power Allocation Optimization: Linear Precoding Adapted to NB-LDPC Coded MIMO Transmission
Tarek Chehade
2015-01-01
Full Text Available In multiple-input multiple-output (MIMO transmission systems, the channel state information (CSI at the transmitter can be used to add linear precoding to the transmitted signals in order to improve the performance and the reliability of the transmission system. This paper investigates how to properly join precoded closed-loop MIMO systems and nonbinary low density parity check (NB-LDPC. The q elements in the Galois field, GF(q, are directly mapped to q transmit symbol vectors. This allows NB-LDPC codes to perfectly fit with a MIMO precoding scheme, unlike binary LDPC codes. The new transmission model is detailed and studied for several linear precoders and various designed LDPC codes. We show that NB-LDPC codes are particularly well suited to be jointly used with precoding schemes based on the maximization of the minimum Euclidean distance (max-dmin criterion. These results are theoretically supported by extrinsic information transfer (EXIT analysis and are confirmed by numerical simulations.
Novel Intermode Prediction Algorithm for High Efficiency Video Coding Encoder
Chan-seob Park
2014-01-01
Full Text Available The joint collaborative team on video coding (JCT-VC is developing the next-generation video coding standard which is called high efficiency video coding (HEVC. In the HEVC, there are three units in block structure: coding unit (CU, prediction unit (PU, and transform unit (TU. The CU is the basic unit of region splitting like macroblock (MB. Each CU performs recursive splitting into four blocks with equal size, starting from the tree block. In this paper, we propose a fast CU depth decision algorithm for HEVC technology to reduce its computational complexity. In 2N×2N PU, the proposed method compares the rate-distortion (RD cost and determines the depth using the compared information. Moreover, in order to speed up the encoding time, the efficient merge SKIP detection method is developed additionally based on the contextual mode information of neighboring CUs. Experimental result shows that the proposed algorithm achieves the average time-saving factor of 44.84% in the random access (RA at Main profile configuration with the HEVC test model (HM 10.0 reference software. Compared to HM 10.0 encoder, a small BD-bitrate loss of 0.17% is also observed without significant loss of image quality.
Quantitative accuracy assessment of thermalhydraulic code predictions with SARBM
Prosek, A.
2001-01-01
In recent years, the nuclear reactor industry has focused significant attention on nuclear reactor systems code accuracy and uncertainty issues. A few methods suitable to quantify code accuracy of thermalhydraulic code calculations were proposed and applied in the past. In this study a Stochastic Approximation Ratio Based Method (SARBM) was adapted and proposed for accuracy quantification. The objective of the study was to qualify the SARBM. The study compare the accuracy obtained by SARBM with the results obtained by widely used Fast Fourier Transform Based Method (FFTBM). The methods were applied to RELAP5/MOD3.2 code calculations of various BETHSY experiments. The obtained results showed that the SARBM was able to satisfactorily predict the accuracy of the calculated trends when visually comparing plots and comparing the results with the qualified FFTBM. The analysis also showed that the new figure-of-merit called accuracy factor (AF) is more convenient than stochastic approximation ratio for combining single variable accuracy's into total accuracy. The accuracy results obtained for the selected tests suggest that the acceptability factors for the SAR method were reasonably defined. The results also indicate that AF is a useful quantitative measure of accuracy.(author)
Tayal, M.
1987-01-01
Structures often operate at elevated temperatures. Temperature calculations are needed so that the design can accommodate thermally induced stresses and material changes. A finite element computer called FEAT has been developed to calculate temperatures in solids of arbitrary shapes. FEAT solves the classical equation for steady state conduction of heat. The solution is obtained for two-dimensional (plane or axisymmetric) or for three-dimensional problems. Gap elements are use to simulate interfaces between neighbouring surfaces. The code can model: conduction; internal generation of heat; prescribed convection to a heat sink; prescribed temperatures at boundaries; prescribed heat fluxes on some surfaces; and temperature-dependence of material properties like thermal conductivity. The user has a option of specifying the detailed variation of thermal conductivity with temperature. For convenience to the nuclear fuel industry, the user can also opt for pre-coded values of thermal conductivity, which are obtained from the MATPRO data base (sponsored by the U.S. Nuclear Regulatory Commission). The finite element method makes FEAT versatile, and enables it to accurately accommodate complex geometries. The optional link to MATPRO makes it convenient for the nuclear fuel industry to use FEAT, without loss of generality. Special numerical techniques make the code inexpensive to run, for the type of material non-linearities often encounter in the analysis of nuclear fuel. The code, however, is general, and can be used for other components of the reactor, or even for non-nuclear systems. The predictions of FEAT have been compared against several analytical solutions. The agreement is usually better than 5%. Thermocouple measurements show that the FEAT predictions are consistent with measured changes in temperatures in simulated pressure tubes. FEAT was also found to predict well, the axial variations in temperatures in the end-pellets(UO 2 ) of two fuel elements irradiated
Intra prediction using face continuity in 360-degree video coding
Hanhart, Philippe; He, Yuwen; Ye, Yan
2017-09-01
This paper presents a new reference sample derivation method for intra prediction in 360-degree video coding. Unlike the conventional reference sample derivation method for 2D video coding, which uses the samples located directly above and on the left of the current block, the proposed method considers the spherical nature of 360-degree video when deriving reference samples located outside the current face to which the block belongs, and derives reference samples that are geometric neighbors on the sphere. The proposed reference sample derivation method was implemented in the Joint Exploration Model 3.0 (JEM-3.0) for the cubemap projection format. Simulation results for the all intra configuration show that, when compared with the conventional reference sample derivation method, the proposed method gives, on average, luma BD-rate reduction of 0.3% in terms of the weighted spherical PSNR (WS-PSNR) and spherical PSNR (SPSNR) metrics.
Predicting Madura cattle growth curve using non-linear model
Widyas, N.; Prastowo, S.; Widi, T. S. M.; Baliarti, E.
2018-03-01
Madura cattle is Indonesian native. It is a composite breed that has undergone hundreds of years of selection and domestication to reach nowadays remarkable uniformity. Crossbreeding has reached the isle of Madura and the Madrasin, a cross between Madura cows and Limousine semen emerged. This paper aimed to compare the growth curve between Madrasin and one type of pure Madura cows, the common Madura cattle (Madura) using non-linear models. Madura cattles are kept traditionally thus reliable records are hardly available. Data were collected from small holder farmers in Madura. Cows from different age classes (5years) were observed, and body measurements (chest girth, body length and wither height) were taken. In total 63 Madura and 120 Madrasin records obtained. Linear model was built with cattle sub-populations and age as explanatory variables. Body weights were estimated based on the chest girth. Growth curves were built using logistic regression. Results showed that within the same age, Madrasin has significantly larger body compared to Madura (plogistic models fit better for Madura and Madrasin cattle data; with the estimated MSE for these models were 39.09 and 759.28 with prediction accuracy of 99 and 92% for Madura and Madrasin, respectively. Prediction of growth curve using logistic regression model performed well in both types of Madura cattle. However, attempts to administer accurate data on Madura cattle are necessary to better characterize and study these cattle.
Coding Scheme for Assessment of Students’ Explanations and Predictions
Mihael Gojkošek
2017-04-01
Full Text Available In the process of analyzing students’ explanations and predictions for interaction between brightness enhancement ﬁlm and beam of white light, a need for objective and reliable assessment instrumentarose. Consequently, we developed a codingscheme that was mostly inspired by the rubrics for self-assessment of scientiﬁc abilities. In the paper we present the grading categories that were integrated in the coding scheme, and descriptions of criteria used for evaluation of students work. We report the results of reliability analysis of new assessment tool and present some examples of its application.
Biocomputational prediction of small non-coding RNAs in Streptomyces
Pánek, Josef; Bobek, Jan; Mikulík, Karel; Basler, Marek; Vohradský, Jiří
2008-01-01
Roč. 9, č. 217 (2008), s. 1-14 ISSN 1471-2164 R&D Projects: GA ČR GP204/07/P361; GA ČR GA203/05/0106; GA ČR GA310/07/1009 Grant - others:XE(XE) EC Integrated Project ActinoGEN, LSHM-CT-2004-005224. Institutional research plan: CEZ:AV0Z50200510 Keywords : non-coding RNA * streptomyces * biocomputational prediction Subject RIV: IN - Informatics, Computer Science Impact factor: 3.926, year: 2008
Predictive Coding: A Possible Explanation of Filling-In at the Blind Spot
Raman, Rajani; Sarkar, Sandip
2016-01-01
Filling-in at the blind spot is a perceptual phenomenon in which the visual system fills the informational void, which arises due to the absence of retinal input corresponding to the optic disc, with surrounding visual attributes. It is known that during filling-in, nonlinear neural responses are observed in the early visual area that correlates with the perception, but the knowledge of underlying neural mechanism for filling-in at the blind spot is far from complete. In this work, we attempted to present a fresh perspective on the computational mechanism of filling-in process in the framework of hierarchical predictive coding, which provides a functional explanation for a range of neural responses in the cortex. We simulated a three-level hierarchical network and observe its response while stimulating the network with different bar stimulus across the blind spot. We find that the predictive-estimator neurons that represent blind spot in primary visual cortex exhibit elevated non-linear response when the bar stimulated both sides of the blind spot. Using generative model, we also show that these responses represent the filling-in completion. All these results are consistent with the finding of psychophysical and physiological studies. In this study, we also demonstrate that the tolerance in filling-in qualitatively matches with the experimental findings related to non-aligned bars. We discuss this phenomenon in the predictive coding paradigm and show that all our results could be explained by taking into account the efficient coding of natural images along with feedback and feed-forward connections that allow priors and predictions to co-evolve to arrive at the best prediction. These results suggest that the filling-in process could be a manifestation of the general computational principle of hierarchical predictive coding of natural images. PMID:26959812
Comparison of Linear Prediction Models for Audio Signals
2009-03-01
Full Text Available While linear prediction (LP has become immensely popular in speech modeling, it does not seem to provide a good approach for modeling audio signals. This is somewhat surprising, since a tonal signal consisting of a number of sinusoids can be perfectly predicted based on an (all-pole LP model with a model order that is twice the number of sinusoids. We provide an explanation why this result cannot simply be extrapolated to LP of audio signals. If noise is taken into account in the tonal signal model, a low-order all-pole model appears to be only appropriate when the tonal components are uniformly distributed in the Nyquist interval. Based on this observation, different alternatives to the conventional LP model can be suggested. Either the model should be changed to a pole-zero, a high-order all-pole, or a pitch prediction model, or the conventional LP model should be preceded by an appropriate frequency transform, such as a frequency warping or downsampling. By comparing these alternative LP models to the conventional LP model in terms of frequency estimation accuracy, residual spectral flatness, and perceptual frequency resolution, we obtain several new and promising approaches to LP-based audio modeling.
Simulating the performance of a distance-3 surface code in a linear ion trap
Trout, Colin J.; Li, Muyuan; Gutiérrez, Mauricio; Wu, Yukai; Wang, Sheng-Tao; Duan, Luming; Brown, Kenneth R.
2018-04-01
We explore the feasibility of implementing a small surface code with 9 data qubits and 8 ancilla qubits, commonly referred to as surface-17, using a linear chain of 171Yb+ ions. Two-qubit gates can be performed between any two ions in the chain with gate time increasing linearly with ion distance. Measurement of the ion state by fluorescence requires that the ancilla qubits be physically separated from the data qubits to avoid errors on the data due to scattered photons. We minimize the time required to measure one round of stabilizers by optimizing the mapping of the two-dimensional surface code to the linear chain of ions. We develop a physically motivated Pauli error model that allows for fast simulation and captures the key sources of noise in an ion trap quantum computer including gate imperfections and ion heating. Our simulations showed a consistent requirement of a two-qubit gate fidelity of ≥99.9% for the logical memory to have a better fidelity than physical two-qubit operations. Finally, we perform an analysis of the error subsets from the importance sampling method used to bound the logical error rates to gain insight into which error sources are particularly detrimental to error correction.
A Linear Algebra Framework for Static High Performance Fortran Code Distribution
Corinne Ancourt
1997-01-01
Full Text Available High Performance Fortran (HPF was developed to support data parallel programming for single-instruction multiple-data (SIMD and multiple-instruction multiple-data (MIMD machines with distributed memory. The programmer is provided a familiar uniform logical address space and specifies the data distribution by directives. The compiler then exploits these directives to allocate arrays in the local memories, to assign computations to elementary processors, and to migrate data between processors when required. We show here that linear algebra is a powerful framework to encode HPF directives and to synthesize distributed code with space-efficient array allocation, tight loop bounds, and vectorized communications for INDEPENDENT loops. The generated code includes traditional optimizations such as guard elimination, message vectorization and aggregation, and overlap analysis. The systematic use of an affine framework makes it possible to prove the compilation scheme correct.
Analysis and Optimization of Sparse Random Linear Network Coding for Reliable Multicast Services
Tassi, Andrea; Chatzigeorgiou, Ioannis; Roetter, Daniel Enrique Lucani
2016-01-01
Point-to-multipoint communications are expected to play a pivotal role in next-generation networks. This paper refers to a cellular system transmitting layered multicast services to a multicast group of users. Reliability of communications is ensured via different random linear network coding (RLNC......) techniques. We deal with a fundamental problem: the computational complexity of the RLNC decoder. The higher the number of decoding operations is, the more the user's computational overhead grows and, consequently, the faster the battery of mobile devices drains. By referring to several sparse RLNC...... techniques, and without any assumption on the implementation of the RLNC decoder in use, we provide an efficient way to characterize the performance of users targeted by ultra-reliable layered multicast services. The proposed modeling allows to efficiently derive the average number of coded packet...
Particle-in-Cell Code BEAMPATH for Beam Dynamics Simulations in Linear Accelerators and Beamlines
Batygin, Y.
2004-01-01
A code library BEAMPATH for 2 - dimensional and 3 - dimensional space charge dominated beam dynamics study in linear particle accelerators and beam transport lines is developed. The program is used for particle-in-cell simulation of axial-symmetric, quadrupole-symmetric and z-uniform beams in a channel containing RF gaps, radio-frequency quadrupoles, multipole lenses, solenoids and bending magnets. The programming method includes hierarchical program design using program-independent modules and a flexible combination of modules to provide the most effective version of the structure for every specific case of simulation. Numerical techniques as well as the results of beam dynamics studies are presented
Particle-in-Cell Code BEAMPATH for Beam Dynamics Simulations in Linear Accelerators and Beamlines
Batygin, Y.
2004-10-28
A code library BEAMPATH for 2 - dimensional and 3 - dimensional space charge dominated beam dynamics study in linear particle accelerators and beam transport lines is developed. The program is used for particle-in-cell simulation of axial-symmetric, quadrupole-symmetric and z-uniform beams in a channel containing RF gaps, radio-frequency quadrupoles, multipole lenses, solenoids and bending magnets. The programming method includes hierarchical program design using program-independent modules and a flexible combination of modules to provide the most effective version of the structure for every specific case of simulation. Numerical techniques as well as the results of beam dynamics studies are presented.
Computer codes for three dimensional mass transport with non-linear sorption
Noy, D.J.
1985-03-01
The report describes the mathematical background and data input to finite element programs for three dimensional mass transport in a porous medium. The transport equations are developed and sorption processes are included in a general way so that non-linear equilibrium relations can be introduced. The programs are described and a guide given to the construction of the required input data sets. Concluding remarks indicate that the calculations require substantial computer resources and suggest that comprehensive preliminary analysis with lower dimensional codes would be important in the assessment of field data. (author)
Genomic prediction based on data from three layer lines: a comparison between linear methods
Calus, M.P.L.; Huang, H.; Vereijken, J.; Visscher, J.; Napel, ten J.; Windig, J.J.
2014-01-01
Background The prediction accuracy of several linear genomic prediction models, which have previously been used for within-line genomic prediction, was evaluated for multi-line genomic prediction. Methods Compared to a conventional BLUP (best linear unbiased prediction) model using pedigree data, we
Further development of the V-code for recirculating linear accelerator simulations
Franke, Sylvain; Ackermann, Wolfgang; Weiland, Thomas [Institut fuer Theorie Elektromagnetischer Felder, Technische Universitaet Darmstadt (Germany); Eichhorn, Ralf; Hug, Florian; Kleinmann, Michaela; Platz, Markus [Institut fuer Kernphysik, Technische Universitaet Darmstadt (Germany)
2011-07-01
The Superconducting Darmstaedter LINear Accelerator (S-DALINAC) installed at the institute of nuclear physics (IKP) at TU Darmstadt is designed as a recirculating linear accelerator. The beam is first accelerated up to 10 MeV in the injector beam line. Then it is deflected by 180 degrees into the main linac. The linac section with eight superconducting cavities is passed up to three times, providing a maximal energy gain of 40 MeV on each passage. Due to this recirculating layout it is complicated to find an accurate setup for the various beam line elements. Fast online beam dynamics simulations can advantageously assist the operators because they provide a more detailed insight into the actual machine status. In this contribution further developments of the moment based simulation tool V-code which enables to simulate recirculating machines are presented together with simulation results.
Software Code Smell Prediction Model Using Shannon, Rényi and Tsallis Entropies
Aakanshi Gupta
2018-05-01
Full Text Available The current era demands high quality software in a limited time period to achieve new goals and heights. To meet user requirements, the source codes undergo frequent modifications which can generate the bad smells in software that deteriorate the quality and reliability of software. Source code of the open source software is easily accessible by any developer, thus frequently modifiable. In this paper, we have proposed a mathematical model to predict the bad smells using the concept of entropy as defined by the Information Theory. Open-source software Apache Abdera is taken into consideration for calculating the bad smells. Bad smells are collected using a detection tool from sub components of the Apache Abdera project, and different measures of entropy (Shannon, Rényi and Tsallis entropy. By applying non-linear regression techniques, the bad smells that can arise in the future versions of software are predicted based on the observed bad smells and entropy measures. The proposed model has been validated using goodness of fit parameters (prediction error, bias, variation, and Root Mean Squared Prediction Error (RMSPE. The values of model performance statistics ( R 2 , adjusted R 2 , Mean Square Error (MSE and standard error also justify the proposed model. We have compared the results of the prediction model with the observed results on real data. The results of the model might be helpful for software development industries and future researchers.
Development of flow network analysis code for block type VHTR core by linear theory method
Lee, J. H.; Yoon, S. J.; Park, J. W.; Park, G. C.
2012-01-01
VHTR (Very High Temperature Reactor) is high-efficiency nuclear reactor which is capable of generating hydrogen with high temperature of coolant. PMR (Prismatic Modular Reactor) type reactor consists of hexagonal prismatic fuel blocks and reflector blocks. The flow paths in the prismatic VHTR core consist of coolant holes, bypass gaps and cross gaps. Complicated flow paths are formed in the core since the coolant holes and bypass gap are connected by the cross gap. Distributed coolant was mixed in the core through the cross gap so that the flow characteristics could not be modeled as a simple parallel pipe system. It requires lot of effort and takes very long time to analyze the core flow with CFD analysis. Hence, it is important to develop the code for VHTR core flow which can predict the core flow distribution fast and accurate. In this study, steady state flow network analysis code is developed using flow network algorithm. Developed flow network analysis code was named as FLASH code and it was validated with the experimental data and CFD simulation results. (authors)
Burke, B. J.; Kruger, S. E.; Hegna, C. C.; Zhu, P.; Snyder, P. B.; Sovinec, C. R.; Howell, E. C.
2010-01-01
A linear benchmark between the linear ideal MHD stability codes ELITE [H. R. Wilson et al., Phys. Plasmas 9, 1277 (2002)], GATO [L. Bernard et al., Comput. Phys. Commun. 24, 377 (1981)], and the extended nonlinear magnetohydrodynamic (MHD) code, NIMROD [C. R. Sovinec et al.., J. Comput. Phys. 195, 355 (2004)] is undertaken for edge-localized (MHD) instabilities. Two ballooning-unstable, shifted-circle tokamak equilibria are compared where the stability characteristics are varied by changing the equilibrium plasma profiles. The equilibria model an H-mode plasma with a pedestal pressure profile and parallel edge currents. For both equilibria, NIMROD accurately reproduces the transition to instability (the marginally unstable mode), as well as the ideal growth spectrum for a large range of toroidal modes (n=1-20). The results use the compressible MHD model and depend on a precise representation of 'ideal-like' and 'vacuumlike' or 'halo' regions within the code. The halo region is modeled by the introduction of a Lundquist-value profile that transitions from a large to a small value at a flux surface location outside of the pedestal region. To model an ideal-like MHD response in the core and a vacuumlike response outside the transition, separate criteria on the plasma and halo Lundquist values are required. For the benchmarked equilibria the critical Lundquist values are 10 8 and 10 3 for the ideal-like and halo regions, respectively. Notably, this gives a ratio on the order of 10 5 , which is much larger than experimentally measured values using T e values associated with the top of the pedestal and separatrix. Excellent agreement with ELITE and GATO calculations are made when sharp boundary transitions in the resistivity are used and a small amount of physical dissipation is added for conditions very near and below marginal ideal stability.
Iterative linear solvers in a 2D radiation-hydrodynamics code: Methods and performance
Baldwin, C.; Brown, P.N.; Falgout, R.; Graziani, F.; Jones, J.
1999-01-01
Computer codes containing both hydrodynamics and radiation play a central role in simulating both astrophysical and inertial confinement fusion (ICF) phenomena. A crucial aspect of these codes is that they require an implicit solution of the radiation diffusion equations. The authors present in this paper the results of a comparison of five different linear solvers on a range of complex radiation and radiation-hydrodynamics problems. The linear solvers used are diagonally scaled conjugate gradient, GMRES with incomplete LU preconditioning, conjugate gradient with incomplete Cholesky preconditioning, multigrid, and multigrid-preconditioned conjugate gradient. These problems involve shock propagation, opacities varying over 5--6 orders of magnitude, tabular equations of state, and dynamic ALE (Arbitrary Lagrangian Eulerian) meshes. They perform a problem size scalability study by comparing linear solver performance over a wide range of problem sizes from 1,000 to 100,000 zones. The fundamental question they address in this paper is: Is it more efficient to invert the matrix in many inexpensive steps (like diagonally scaled conjugate gradient) or in fewer expensive steps (like multigrid)? In addition, what is the answer to this question as a function of problem size and is the answer problem dependent? They find that the diagonally scaled conjugate gradient method performs poorly with the growth of problem size, increasing in both iteration count and overall CPU time with the size of the problem and also increasing for larger time steps. For all problems considered, the multigrid algorithms scale almost perfectly (i.e., the iteration count is approximately independent of problem size and problem time step). For pure radiation flow problems (i.e., no hydrodynamics), they see speedups in CPU time of factors of ∼15--30 for the largest problems, when comparing the multigrid solvers relative to diagonal scaled conjugate gradient
Comparison of GLIMPS and HFAST Stirling engine code predictions with experimental data
Geng, Steven M.; Tew, Roy C.
1992-01-01
Predictions from GLIMPS and HFAST design codes are compared with experimental data for the RE-1000 and SPRE free piston Stirling engines. Engine performance and available power loss predictions are compared. Differences exist between GLIMPS and HFAST loss predictions. Both codes require engine specific calibration to bring predictions and experimental data into agreement.
Comparison of GLIMPS and HFAST Stirling engine code predictions with experimental data
Geng, S.M.; Tew, R.C.
1994-01-01
Predictions from GLIMPS and HFAST design codes are compared with experimental data for the RE-1000 and SPRE free-piston Stirling engines. Engine performance and available power loss predictions are compared. Differences exist between GLIMPS and HFAST loss predictions. Both codes require engine-specific calibration to bring predictions and experimental data into agreement
Comparison of l₁-Norm SVR and Sparse Coding Algorithms for Linear Regression.
Zhang, Qingtian; Hu, Xiaolin; Zhang, Bo
2015-08-01
Support vector regression (SVR) is a popular function estimation technique based on Vapnik's concept of support vector machine. Among many variants, the l1-norm SVR is known to be good at selecting useful features when the features are redundant. Sparse coding (SC) is a technique widely used in many areas and a number of efficient algorithms are available. Both l1-norm SVR and SC can be used for linear regression. In this brief, the close connection between the l1-norm SVR and SC is revealed and some typical algorithms are compared for linear regression. The results show that the SC algorithms outperform the Newton linear programming algorithm, an efficient l1-norm SVR algorithm, in efficiency. The algorithms are then used to design the radial basis function (RBF) neural networks. Experiments on some benchmark data sets demonstrate the high efficiency of the SC algorithms. In particular, one of the SC algorithms, the orthogonal matching pursuit is two orders of magnitude faster than a well-known RBF network designing algorithm, the orthogonal least squares algorithm.
Frequency prediction by linear stability analysis around mean flow
Bengana, Yacine; Tuckerman, Laurette
2017-11-01
The frequency of certain limit cycles resulting from a Hopf bifurcation, such as the von Karman vortex street, can be predicted by linear stability analysis around their mean flows. Barkley (2006) has shown this to yield an eigenvalue whose real part is zero and whose imaginary part matches the nonlinear frequency. This property was named RZIF by Turton et al. (2015); moreover they found that the traveling waves (TW) of thermosolutal convection have the RZIF property. They explained this as a consequence of the fact that the temporal Fourier spectrum is dominated by the mean flow and first harmonic. We could therefore consider that only the first mode is important in the saturation of the mean flow as presented in the Self-Consistent Model (SCM) of Mantic-Lugo et al. (2014). We have implemented a full Newton's method to solve the SCM for thermosolutal convection. We show that while the RZIF property is satisfied far from the threshold, the SCM model reproduces the exact frequency only very close to the threshold. Thus, the nonlinear interaction of only the first mode with itself is insufficiently accurate to estimate the mean flow. Our next step will be to take into account higher harmonics and to apply this analysis to the standing waves, for which RZIF does not hold.
Flow discharge prediction in compound channels using linear genetic programming
Azamathulla, H. Md.; Zahiri, A.
2012-08-01
SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.
C code generation applied to nonlinear model predictive control for an artificial pancreas
Boiroux, Dimitri; Jørgensen, John Bagterp
2017-01-01
This paper presents a method to generate C code from MATLAB code applied to a nonlinear model predictive control (NMPC) algorithm. The C code generation uses the MATLAB Coder Toolbox. It can drastically reduce the time required for development compared to a manual porting of code from MATLAB to C...
Computer code to predict the heat of explosion of high energy materials
Muthurajan, H.; Sivabalan, R.; Pon Saravanan, N.; Talawar, M.B.
2009-01-01
The computational approach to the thermochemical changes involved in the process of explosion of a high energy materials (HEMs) vis-a-vis its molecular structure aids a HEMs chemist/engineers to predict the important thermodynamic parameters such as heat of explosion of the HEMs. Such a computer-aided design will be useful in predicting the performance of a given HEM as well as in conceiving futuristic high energy molecules that have significant potential in the field of explosives and propellants. The software code viz., LOTUSES developed by authors predicts various characteristics of HEMs such as explosion products including balanced explosion reactions, density of HEMs, velocity of detonation, CJ pressure, etc. The new computational approach described in this paper allows the prediction of heat of explosion (ΔH e ) without any experimental data for different HEMs, which are comparable with experimental results reported in literature. The new algorithm which does not require any complex input parameter is incorporated in LOTUSES (version 1.5) and the results are presented in this paper. The linear regression analysis of all data point yields the correlation coefficient R 2 = 0.9721 with a linear equation y = 0.9262x + 101.45. The correlation coefficient value 0.9721 reveals that the computed values are in good agreement with experimental values and useful for rapid hazard assessment of energetic materials
Random Linear Network Coding is Key to Data Survival in Highly Dynamic Distributed Storage
Sipos, Marton A.; Fitzek, Frank; Roetter, Daniel Enrique Lucani
2015-01-01
Distributed storage solutions have become widespread due to their ability to store large amounts of data reliably across a network of unreliable nodes, by employing repair mechanisms to prevent data loss. Conventional systems rely on static designs with a central control entity to oversee...... and control the repair process. Given the large costs for maintaining and cooling large data centers, our work proposes and studies the feasibility of a fully decentralized systems that can store data even on unreliable and, sometimes, unavailable mobile devices. This imposes new challenges on the design...... as the number of available nodes varies greatly over time and keeping track of the system's state becomes unfeasible. As a consequence, conventional erasure correction approaches are ill-suited for maintaining data integrity. In this highly dynamic context, random linear network coding (RLNC) provides...
Lundsager, P.; Krenk, S.
1975-08-01
The static and dynamic response of a cylindrical/ spherical containment to a Boeing 720 impact is computed using 3 different linear elastic computer codes: FINEL, SAP and STARDYNE. Stress and displacement fields are shown together with time histories for a point in the impact zone. The main conclusions from this study are: - In this case the maximum dynamic load factors for stress and displacements were close to 1, but a static analysis alone is not fully sufficient. - More realistic load time histories should be considered. - The main effects seem to be local. The present study does not indicate general collapse from elastic stresses alone. - Further study of material properties at high rates is needed. (author)
QR code-based non-linear image encryption using Shearlet transform and spiral phase transform
Kumar, Ravi; Bhaduri, Basanta; Hennelly, Bryan
2018-02-01
In this paper, we propose a new quick response (QR) code-based non-linear technique for image encryption using Shearlet transform (ST) and spiral phase transform. The input image is first converted into a QR code and then scrambled using the Arnold transform. The scrambled image is then decomposed into five coefficients using the ST and the first Shearlet coefficient, C1 is interchanged with a security key before performing the inverse ST. The output after inverse ST is then modulated with a random phase mask and further spiral phase transformed to get the final encrypted image. The first coefficient, C1 is used as a private key for decryption. The sensitivity of the security keys is analysed in terms of correlation coefficient and peak signal-to noise ratio. The robustness of the scheme is also checked against various attacks such as noise, occlusion and special attacks. Numerical simulation results are shown in support of the proposed technique and an optoelectronic set-up for encryption is also proposed.
Chang, Chau-Lyan
2003-01-01
During the past two decades, our understanding of laminar-turbulent transition flow physics has advanced significantly owing to, in a large part, the NASA program support such as the National Aerospace Plane (NASP), High-speed Civil Transport (HSCT), and Advanced Subsonic Technology (AST). Experimental, theoretical, as well as computational efforts on various issues such as receptivity and linear and nonlinear evolution of instability waves take part in broadening our knowledge base for this intricate flow phenomenon. Despite all these advances, transition prediction remains a nontrivial task for engineers due to the lack of a widely available, robust, and efficient prediction tool. The design and development of the LASTRAC code is aimed at providing one such engineering tool that is easy to use and yet capable of dealing with a broad range of transition related issues. LASTRAC was written from scratch based on the state-of-the-art numerical methods for stability analysis and modem software technologies. At low fidelity, it allows users to perform linear stability analysis and N-factor transition correlation for a broad range of flow regimes and configurations by using either the linear stability theory (LST) or linear parabolized stability equations (LPSE) method. At high fidelity, users may use nonlinear PSE to track finite-amplitude disturbances until the skin friction rise. Coupled with the built-in receptivity model that is currently under development, the nonlinear PSE method offers a synergistic approach to predict transition onset for a given disturbance environment based on first principles. This paper describes the governing equations, numerical methods, code development, and case studies for the current release of LASTRAC. Practical applications of LASTRAC are demonstrated for linear stability calculations, N-factor transition correlation, non-linear breakdown simulations, and controls of stationary crossflow instability in supersonic swept wing boundary
Fast Algorithms for High-Order Sparse Linear Prediction with Applications to Speech Processing
Jensen, Tobias Lindstrøm; Giacobello, Daniele; van Waterschoot, Toon
2016-01-01
In speech processing applications, imposing sparsity constraints on high-order linear prediction coefficients and prediction residuals has proven successful in overcoming some of the limitation of conventional linear predictive modeling. However, this modeling scheme, named sparse linear prediction...... problem with lower accuracy than in previous work. In the experimental analysis, we clearly show that a solution with lower accuracy can achieve approximately the same performance as a high accuracy solution both objectively, in terms of prediction gain, as well as with perceptual relevant measures, when...... evaluated in a speech reconstruction application....
The log-linear return approximation, bubbles, and predictability
Engsted, Tom; Pedersen, Thomas Quistgaard; Tanggaard, Carsten
We study in detail the log-linear return approximation introduced by Campbell and Shiller (1988a). First, we derive an upper bound for the mean approximation error, given stationarity of the log dividendprice ratio. Next, we simulate various rational bubbles which have explosive conditional expec...
The Log-Linear Return Approximation, Bubbles, and Predictability
Engsted, Tom; Pedersen, Thomas Quistgaard; Tanggaard, Carsten
2012-01-01
We study in detail the log-linear return approximation introduced by Campbell and Shiller (1988a). First, we derive an upper bound for the mean approximation error, given stationarity of the log dividend-price ratio. Next, we simulate various rational bubbles which have explosive conditional expe...
Improving performance of single-path code through a time-predictable memory hierarchy
Cilku, Bekim; Puffitsch, Wolfgang; Prokesch, Daniel
2017-01-01
-predictable memory hierarchy with a prefetcher that exploits the predictability of execution traces in single-path code to speed up code execution. The new memory hierarchy reduces both the cache-miss penalty time and the cache-miss rate on the instruction cache. The benefit of the approach is demonstrated through...
Linear-time non-malleable codes in the bit-wise independent tampering model
R.J.F. Cramer (Ronald); I.B. Damgård (Ivan); N.M. Döttling (Nico); I. Giacomelli (Irene); C. Xing (Chaoping)
2017-01-01
textabstractNon-malleable codes were introduced by Dziembowski et al. (ICS 2010) as coding schemes that protect a message against tampering attacks. Roughly speaking, a code is non-malleable if decoding an adversarially tampered encoding of a message m produces the original message m or a value m′
Non linear predictive control of a LEGO mobile robot
Merabti, H.; Bouchemal, B.; Belarbi, K.; Boucherma, D.; Amouri, A.
2014-10-01
Metaheuristics are general purpose heuristics which have shown a great potential for the solution of difficult optimization problems. In this work, we apply the meta heuristic, namely particle swarm optimization, PSO, for the solution of the optimization problem arising in NLMPC. This algorithm is easy to code and may be considered as alternatives for the more classical solution procedures. The PSO- NLMPC is applied to control a mobile robot for the tracking trajectory and obstacles avoidance. Experimental results show the strength of this approach.
Biancalani, A.; Bottino, A.; Ehrlacher, C.; Grandgirard, V.; Merlo, G.; Novikau, I.; Qiu, Z.; Sonnendrücker, E.; Garbet, X.; Görler, T.; Leerink, S.; Palermo, F.; Zarzoso, D.
2017-06-01
The linear properties of the geodesic acoustic modes (GAMs) in tokamaks are investigated by means of the comparison of analytical theory and gyrokinetic numerical simulations. The dependence on the value of the safety factor, finite-orbit-width of the ions in relation to the radial mode width, magnetic-flux-surface shaping, and electron/ion mass ratio are considered. Nonuniformities in the plasma profiles (such as density, temperature, and safety factor), electro-magnetic effects, collisions, and the presence of minority species are neglected. Also, only linear simulations are considered, focusing on the local dynamics. We use three different gyrokinetic codes: the Lagrangian (particle-in-cell) code ORB5, the Eulerian code GENE, and semi-Lagrangian code GYSELA. One of the main aims of this paper is to provide a detailed comparison of the numerical results and analytical theory, in the regimes where this is possible. This helps understanding better the behavior of the linear GAM dynamics in these different regimes, the behavior of the codes, which is crucial in the view of a future work where more physics is present, and the regimes of validity of each specific analytical dispersion relation.
Ishitani, Terry T.
2010-01-01
This study applied hierarchical linear modeling to investigate the effect of congruence on intrinsic and extrinsic aspects of job satisfaction. Particular focus was given to differences in job satisfaction by gender and by Holland's first-letter codes. The study sample included nationally represented 1462 female and 1280 male college graduates who…
Decoding linear error-correcting codes up to half the minimum distance with Gröbner bases
Bulygin, S.; Pellikaan, G.R.; Sala, M.; Mora, T.; Perret, L.; Sakata, S.; Traverso, C.
2009-01-01
In this short note we show how one can decode linear error-correcting codes up to half the minimum distance via solving a system of polynomial equations over a finite field. We also explicitly present the reduced Gröbner basis for the system considered.
Dattoli, Giuseppe
2005-01-01
The coherent synchrotron radiation (CSR) is one of the main problems limiting the performance of high intensity electron accelerators. A code devoted to the analysis of this type of problems should be fast and reliable: conditions that are usually hardly achieved at the same time. In the past, codes based on Lie algebraic techniques have been very efficient to treat transport problem in accelerators. The extension of these method to the non-linear case is ideally suited to treat CSR instability problems. We report on the development of a numerical code, based on the solution of the Vlasov equation, with the inclusion of non-linear contribution due to wake field effects. The proposed solution method exploits an algebraic technique, using exponential operators implemented numerically in C++. We show that the integration procedure is capable of reproducing the onset of an instability and effects associated with bunching mechanisms leading to the growth of the instability itself. In addition, parametric studies a...
Linear-quadratic model predictions for tumor control probability
Yaes, R.J.
1987-01-01
Sigmoid dose-response curves for tumor control are calculated from the linear-quadratic model parameters α and Β, obtained from human epidermoid carcinoma cell lines, and are much steeper than the clinical dose-response curves for head and neck cancers. One possible explanation is the presence of small radiation-resistant clones arising from mutations in an initially homogeneous tumor. Using the mutation theory of Delbruck and Luria and of Goldie and Coldman, the authors discuss the implications of such radiation-resistant clones for clinical radiation therapy
Genomic prediction based on data from three layer lines using non-linear regression models.
Huang, Heyun; Windig, Jack J; Vereijken, Addie; Calus, Mario P L
2014-11-06
Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. In an attempt to alleviate potential discrepancies between assumptions of linear models and multi-population data, two types of alternative models were used: (1) a multi-trait genomic best linear unbiased prediction (GBLUP) model that modelled trait by line combinations as separate but correlated traits and (2) non-linear models based on kernel learning. These models were compared to conventional linear models for genomic prediction for two lines of brown layer hens (B1 and B2) and one line of white hens (W1). The three lines each had 1004 to 1023 training and 238 to 240 validation animals. Prediction accuracy was evaluated by estimating the correlation between observed phenotypes and predicted breeding values. When the training dataset included only data from the evaluated line, non-linear models yielded at best a similar accuracy as linear models. In some cases, when adding a distantly related line, the linear models showed a slight decrease in performance, while non-linear models generally showed no change in accuracy. When only information from a closely related line was used for training, linear models and non-linear radial basis function (RBF) kernel models performed similarly. The multi-trait GBLUP model took advantage of the estimated genetic correlations between the lines. Combining linear and non-linear models improved the accuracy of multi-line genomic prediction. Linear models and non-linear RBF models performed very similarly for genomic prediction, despite the expectation that non-linear models could deal better with the heterogeneous multi-population data. This heterogeneity of the data can be overcome by modelling trait by line combinations as separate but correlated traits, which avoids the occasional
A comparison of oxide thickness predictability from the perspective of codes
Park, Joo-Young; Shin, Hye-In; Kim, Kyung-Tae; Han, Hee-Tak; Kim, Hong-Jin; Kim, Yong-Hwan [KEPCO Nuclear Fuel Co. Ltd., Daejeon (Korea, Republic of)
2016-10-15
In Korea, OPR1000 and Westinghouse type nuclear power plant reactor fuel rods oxide thickness has been evaluated by imported code A. Because of this, there have been multiple constraints in operation and maintenance of fuel rod design system. For this reason, there has been a growing demand to establish an independent fuel rod design system. To meet this goal, KNF has recently developed its own code B for fuel rod design. The objective of this study is to compare oxide thickness prediction performance between code A and code B and to check the validity of predicting corrosion behaviors of newly developed code B. This study is based on Pool Side Examination (PSE) data for the performance confirmation. For the examination procedures, the oxide thickness measurement methods and equipment of PSE are described in detail. In this study, code B is confirmed conservatism and validity on evaluating cladding oxide thickness through the comparison with code A. Code prediction values show higher value than measured data from PSE. Throughout this study, the values by code B are evaluated and proved to be valid in a view point of the oxide thickness evaluation. However, the code B input for prediction has been made by designer's judgment with complex handwork that might be lead to excessive conservative result and ineffective design process with some possibility of errors.
Raisee, M.; Hejazi, S.H.
2007-01-01
This paper presents comparisons between heat transfer predictions and measurements for developing turbulent flow through straight rectangular channels with sudden contractions at the mid-channel section. The present numerical results were obtained using a two-dimensional finite-volume code which solves the governing equations in a vertical plane located at the lateral mid-point of the channel. The pressure field is obtained with the well-known SIMPLE algorithm. The hybrid scheme was employed for the discretization of convection in all transport equations. For modeling of the turbulence, a zonal low-Reynolds number k-ε model and the linear and non-linear low-Reynolds number k-ε models with the 'Yap' and 'NYP' length-scale correction terms have been employed. The main objective of present study is to examine the ability of the above turbulence models in the prediction of convective heat transfer in channels with sudden contraction at a mid-channel section. The results of this study show that a sudden contraction creates a relatively small recirculation bubble immediately downstream of the channel contraction. This separation bubble influences the distribution of local heat transfer coefficient and increases the heat transfer levels by a factor of three. Computational results indicate that all the turbulence models employed produce similar flow fields. The zonal k-ε model produces the wrong Nusselt number distribution by underpredicting heat transfer levels in the recirculation bubble and overpredicting them in the developing region. The linear low-Re k-ε model, on the other hand, returns the correct Nusselt number distribution in the recirculation region, although it somewhat overpredicts heat transfer levels in the developing region downstream of the separation bubble. The replacement of the 'Yap' term with the 'NYP' term in the linear low-Re k-ε model results in a more accurate local Nusselt number distribution. Moreover, the application of the non-linear k
ISODEP, A Fuel Depletion Analysis Code for Predicting Isotopic ...
The trend of results was found to be consistent with those obtained by analytical and other numerical methods. Discovery and Innovation Vol. 13 no. 3/4 December (2001) pp. 184-195. KEY WORDS: depletion analysis, code, research reactor, simultaneous equations, decay of nuclides, radionuclitides, isotope. Résumé
Glass, Alexis; Fukudome, Kimitoshi
2004-12-01
A sound recording of a plucked string instrument is encoded and resynthesized using two stages of prediction. In the first stage of prediction, a simple physical model of a plucked string is estimated and the instrument excitation is obtained. The second stage of prediction compensates for the simplicity of the model in the first stage by encoding either the instrument excitation or the model error using warped linear prediction. These two methods of compensation are compared with each other, and to the case of single-stage warped linear prediction, adjustments are introduced, and their applications to instrument synthesis and MPEG4's audio compression within the structured audio format are discussed.
R. Barbiero
2007-05-01
Full Text Available Model Output Statistics (MOS refers to a method of post-processing the direct outputs of numerical weather prediction (NWP models in order to reduce the biases introduced by a coarse horizontal resolution. This technique is especially useful in orographically complex regions, where large differences can be found between the NWP elevation model and the true orography. This study carries out a comparison of linear and non-linear MOS methods, aimed at the prediction of minimum temperatures in a fruit-growing region of the Italian Alps, based on the output of two different NWPs (ECMWF T511–L60 and LAMI-3. Temperature, of course, is a particularly important NWP output; among other roles it drives the local frost forecast, which is of great interest to agriculture. The mechanisms of cold air drainage, a distinctive aspect of mountain environments, are often unsatisfactorily captured by global circulation models. The simplest post-processing technique applied in this work was a correction for the mean bias, assessed at individual model grid points. We also implemented a multivariate linear regression on the output at the grid points surrounding the target area, and two non-linear models based on machine learning techniques: Neural Networks and Random Forest. We compare the performance of all these techniques on four different NWP data sets. Downscaling the temperatures clearly improved the temperature forecasts with respect to the raw NWP output, and also with respect to the basic mean bias correction. Multivariate methods generally yielded better results, but the advantage of using non-linear algorithms was small if not negligible. RF, the best performing method, was implemented on ECMWF prognostic output at 06:00 UTC over the 9 grid points surrounding the target area. Mean absolute errors in the prediction of 2 m temperature at 06:00 UTC were approximately 1.2°C, close to the natural variability inside the area itself.
A predictive transport modeling code for ICRF-heated tokamaks
Phillips, C.K.; Hwang, D.Q.
1992-02-01
In this report, a detailed description of the physic included in the WHIST/RAZE package as well as a few illustrative examples of the capabilities of the package will be presented. An in depth analysis of ICRF heating experiments using WHIST/RAZE will be discussed in a forthcoming report. A general overview of philosophy behind the structure of the WHIST/RAZE package, a summary of the features of the WHIST code, and a description of the interface to the RAZE subroutines are presented in section 2 of this report. Details of the physics contained in the RAZE code are examined in section 3. Sample results from the package follow in section 4, with concluding remarks and a discussion of possible improvements to the package discussed in section 5
Development of a relativistic Particle In Cell code PARTDYN for linear accelerator beam transport
Phadte, D., E-mail: deepraj@rrcat.gov.in [LPD, Raja Ramanna Centre for Advanced Technology, Indore 452013 (India); Patidar, C.B.; Pal, M.K. [MAASD, Raja Ramanna Centre for Advanced Technology, Indore (India)
2017-04-11
A relativistic Particle In Cell (PIC) code PARTDYN is developed for the beam dynamics simulation of z-continuous and bunched beams. The code is implemented in MATLAB using its MEX functionality which allows both ease of development as well higher performance similar to a compiled language like C. The beam dynamics calculations carried out by the code are compared with analytical results and with other well developed codes like PARMELA and BEAMPATH. The effect of finite number of simulation particles on the emittance growth of intense beams has been studied. Corrections to the RF cavity field expressions were incorporated in the code so that the fields could be calculated correctly. The deviations of the beam dynamics results between PARTDYN and BEAMPATH for a cavity driven in zero-mode have been discussed. The beam dynamics studies of the Low Energy Beam Transport (LEBT) using PARTDYN have been presented.
Efficient Dual Domain Decoding of Linear Block Codes Using Genetic Algorithms
Ahmed Azouaoui
2012-01-01
Full Text Available A computationally efficient algorithm for decoding block codes is developed using a genetic algorithm (GA. The proposed algorithm uses the dual code in contrast to the existing genetic decoders in the literature that use the code itself. Hence, this new approach reduces the complexity of decoding the codes of high rates. We simulated our algorithm in various transmission channels. The performance of this algorithm is investigated and compared with competitor decoding algorithms including Maini and Shakeel ones. The results show that the proposed algorithm gives large gains over the Chase-2 decoding algorithm and reach the performance of the OSD-3 for some quadratic residue (QR codes. Further, we define a new crossover operator that exploits the domain specific information and compare it with uniform and two point crossover. The complexity of this algorithm is also discussed and compared to other algorithms.
Comparing Fine-Grained Source Code Changes And Code Churn For Bug Prediction
Giger, E.; Pinzger, M.; Gall, H.C.
2011-01-01
A significant amount of research effort has been dedicated to learning prediction models that allow project managers to efficiently allocate resources to those parts of a software system that most likely are bug-prone and therefore critical. Prominent measures for building bug prediction models are
Force prediction in permanent magnet flat linear motors (abstract)
Eastham, J.F.; Akmese, R.
1991-01-01
The advent of neodymium iron boron rare-earth permanent magnet material has afforded the opportunity to construct linear machines of high force to weight ratio. The paper describes the design and construction of an axial flux machine and rotating drum test rig. The machine occupies an arc of 45 degree on a drum 1.22 m in diameter. The excitation is provided by blocks of NdFeB material which are skewed in order to minimize the force variations due to slotting. The stator carries a three-phase short-chorded double-layer winding of four poles. The machine is supplied by a PWM inverter the fundamental component of which is phase locked to the rotor position so that a ''dc brushless'' drive system is produced. Electromagnetic forces including ripple forces are measured at supply frequencies up to 100 Hz. They are compared with finite-element analysis which calculates the force variation over the time period. The paper then considers some of the causes of ripple torque. In particular, the force production due solely to the permanent magnet excitation is considered. This has two important components each acting along the line of motion of the machine, one is due to slotting and the other is due to the finite length of the primary. In the practical machine the excitation poles are skewed to minimize the slotting force and the effectiveness of this is confirmed by both results from the experiments and the finite-element analysis. The end effect force is shown to have a space period of twice that of the excitation. The amplitude of this force and its period are again confirmed by practical results
Binary Linear-Time Erasure Decoding for Non-Binary LDPC codes
Savin, Valentin
2009-01-01
In this paper, we first introduce the extended binary representation of non-binary codes, which corresponds to a covering graph of the bipartite graph associated with the non-binary code. Then we show that non-binary codewords correspond to binary codewords of the extended representation that further satisfy some simplex-constraint: that is, bits lying over the same symbol-node of the non-binary graph must form a codeword of a simplex code. Applied to the binary erasure channel, this descript...
The Barrier code for predicting long-term concrete performance
Shuman, R.; Rogers, V.C.; Shaw, R.A.
1989-01-01
There are numerous features incorporated into a LLW disposal facility that deal directly with critical safety objectives required by the NRC in 10 CFR 61. Engineered barriers or structures incorporating concrete are commonly being considered for waste disposal facilities. The Barrier computer code calculates the long-term degradation of concrete structures in LLW disposal facilities. It couples this degradation with water infiltration into the facility, nuclide leaching from the waste, contaminated water release from the facility, and associated doses to members of the critical population group. The concrete degradation methodology of Barrier is described
Predictive codes of familiarity and context during the perceptual learning of facial identities
Apps, Matthew A. J.; Tsakiris, Manos
2013-11-01
Face recognition is a key component of successful social behaviour. However, the computational processes that underpin perceptual learning and recognition as faces transition from unfamiliar to familiar are poorly understood. In predictive coding, learning occurs through prediction errors that update stimulus familiarity, but recognition is a function of both stimulus and contextual familiarity. Here we show that behavioural responses on a two-option face recognition task can be predicted by the level of contextual and facial familiarity in a computational model derived from predictive-coding principles. Using fMRI, we show that activity in the superior temporal sulcus varies with the contextual familiarity in the model, whereas activity in the fusiform face area covaries with the prediction error parameter that updated facial familiarity. Our results characterize the key computations underpinning the perceptual learning of faces, highlighting that the functional properties of face-processing areas conform to the principles of predictive coding.
FIRAC: a computer code to predict fire-accident effects in nuclear facilities
Bolstad, J.W.; Krause, F.R.; Tang, P.K.; Andrae, R.W.; Martin, R.A.; Gregory, W.S.
1983-01-01
FIRAC is a medium-sized computer code designed to predict fire-induced flows, temperatures, and material transport within the ventilating systems and other airflow pathways in nuclear-related facilities. The code is designed to analyze the behavior of interconnected networks of rooms and typical ventilation system components. This code is one in a family of computer codes that is designed to provide improved methods of safety analysis for the nuclear industry. The structure of this code closely follows that of the previously developed TVENT and EVENT codes. Because a lumped-parameter formulation is used, this code is particularly suitable for calculating the effects of fires in the far field (that is, in regions removed from the fire compartment), where the fire may be represented parametrically. However, a fire compartment model to simulate conditions in the enclosure is included. This model provides transport source terms to the ventilation system that can affect its operation and in turn affect the fire
Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression
Abdul Jameel, Abdul Gani; Naser, Nimal; Emwas, Abdul-Hamid M.; Dooley, Stephen; Sarathy, Mani
2016-01-01
An improved model for the prediction of ignition quality of hydrocarbon fuels has been developed using 1H nuclear magnetic resonance (NMR) spectroscopy and multiple linear regression (MLR) modeling. Cetane number (CN) and derived cetane number (DCN
Muayad Al-Qaisy
2015-02-01
Full Text Available In this article, multi-input multi-output (MIMO linear model predictive controller (LMPC based on state space model and nonlinear model predictive controller based on neural network (NNMPC are applied on a continuous stirred tank reactor (CSTR. The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA and reactor temperature (T. NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.
Fleming, David P.; Poplawski, J. V.
2002-01-01
Rolling-element bearing forces vary nonlinearly with bearing deflection. Thus an accurate rotordynamic transient analysis requires bearing forces to be determined at each step of the transient solution. Analyses have been carried out to show the effect of accurate bearing transient forces (accounting for non-linear speed and load dependent bearing stiffness) as compared to conventional use of average rolling-element bearing stiffness. Bearing forces were calculated by COBRA-AHS (Computer Optimized Ball and Roller Bearing Analysis - Advanced High Speed) and supplied to the rotordynamics code ARDS (Analysis of Rotor Dynamic Systems) for accurate simulation of rotor transient behavior. COBRA-AHS is a fast-running 5 degree-of-freedom computer code able to calculate high speed rolling-element bearing load-displacement data for radial and angular contact ball bearings and also for cylindrical and tapered roller beatings. Results show that use of nonlinear bearing characteristics is essential for accurate prediction of rotordynamic behavior.
Yablonovitch, Eli
2000-01-01
.... The equipment purchased under this grant has permitted UCLA to purchase a number of broad-band optical components, including especially some unique code division multiplexing filters that permitted...
Genomic prediction based on data from three layer lines using non-linear regression models
Huang, H.; Windig, J.J.; Vereijken, A.; Calus, M.P.L.
2014-01-01
Background - Most studies on genomic prediction with reference populations that include multiple lines or breeds have used linear models. Data heterogeneity due to using multiple populations may conflict with model assumptions used in linear regression methods. Methods - In an attempt to alleviate
A predictive coding account of bistable perception - a model-based fMRI study.
Veith Weilnhammer
2017-05-01
Full Text Available In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the model's predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants' perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together
A predictive coding account of bistable perception - a model-based fMRI study.
Weilnhammer, Veith; Stuke, Heiner; Hesselmann, Guido; Sterzer, Philipp; Schmack, Katharina
2017-05-01
In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the model's predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants' perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together, our current work
Kondo, Yoshihisa; Yomo, Hiroyuki; Yamaguchi, Shinji; Davis, Peter; Miura, Ryu; Obana, Sadao; Sampei, Seiichi
This paper proposes multipoint-to-multipoint (MPtoMP) real-time broadcast transmission using network coding for ad-hoc networks like video game networks. We aim to achieve highly reliable MPtoMP broadcasting using IEEE 802.11 media access control (MAC) that does not include a retransmission mechanism. When each node detects packets from the other nodes in a sequence, the correctly detected packets are network-encoded, and the encoded packet is broadcasted in the next sequence as a piggy-back for its native packet. To prevent increase of overhead in each packet due to piggy-back packet transmission, network coding vector for each node is exchanged between all nodes in the negotiation phase. Each user keeps using the same coding vector generated in the negotiation phase, and only coding information that represents which user signal is included in the network coding process is transmitted along with the piggy-back packet. Our simulation results show that the proposed method can provide higher reliability than other schemes using multi point relay (MPR) or redundant transmissions such as forward error correction (FEC). We also implement the proposed method in a wireless testbed, and show that the proposed method achieves high reliability in a real-world environment with a practical degree of complexity when installed on current wireless devices.
Evolutionary modeling and prediction of non-coding RNAs in Drosophila.
Robert K Bradley
2009-08-01
Full Text Available We performed benchmarks of phylogenetic grammar-based ncRNA gene prediction, experimenting with eight different models of structural evolution and two different programs for genome alignment. We evaluated our models using alignments of twelve Drosophila genomes. We find that ncRNA prediction performance can vary greatly between different gene predictors and subfamilies of ncRNA gene. Our estimates for false positive rates are based on simulations which preserve local islands of conservation; using these simulations, we predict a higher rate of false positives than previous computational ncRNA screens have reported. Using one of the tested prediction grammars, we provide an updated set of ncRNA predictions for D. melanogaster and compare them to previously-published predictions and experimental data. Many of our predictions show correlations with protein-coding genes. We found significant depletion of intergenic predictions near the 3' end of coding regions and furthermore depletion of predictions in the first intron of protein-coding genes. Some of our predictions are colocated with larger putative unannotated genes: for example, 17 of our predictions showing homology to the RFAM family snoR28 appear in a tandem array on the X chromosome; the 4.5 Kbp spanned by the predicted tandem array is contained within a FlyBase-annotated cDNA.
Rahman, Imadur Mohamed; Marchetti, Nicola; Fitzek, Frank
2005-01-01
(SIC) receiver where the detection is done on subcarrier by sub-carrier basis based on both Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) nulling criterion for the system. In terms of Frame Error Rate (FER), MMSE based SIC receiver performs better than all other receivers compared......In this work, we have analyzed a joint spatial diversity and multiplexing transmission structure for MIMO-OFDM system, where Orthogonal Space-Frequency Block Coding (OSFBC) is used across all spatial multiplexing branches. We have derived a BLAST-like non-linear Successive Interference Cancellation...... in this paper. We have found that a linear two-stage receiver for the proposed system [1] performs very close to the non-linear receiver studied in this work. Finally, we compared the system performance in spatially correlated scenario. It is found that higher amount of spatial correlation at the transmitter...
Fokker-Planck code for the quasi-linear absorption of electron cyclotron waves in a tokamak plasma
Meyer, R.L.; Giruzzi, G.; Krivenski, V.
1986-01-01
We present the solution of the kinetic equation describing the quasi-linear evolution of the electron momentum distribution function under the influence of the electron cyclotron wave absorption. Coulomb collisions and the dc electric field in a tokamak plasma. The solution of the quasi-linear equation is obtained numerically using a two-dimensional initial value code following an ADI scheme. Most emphasis is given to the full non-linear and self-consistent problem, namely, the wave amplitude is evaluated at any instant and any point in space according to the actual damping. This is necessary since wave damping is a very sensitive function of the slope of the local momentum distribution function because the resonance condition relates the electron momentum to the location of wave energy deposition. (orig.)
Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne
2012-12-01
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.
Toprak, A. Emre; Guelay, F. Guelten; Ruge, Peter
2008-01-01
Determination of seismic performance of existing buildings has become one of the key concepts in structural analysis topics after recent earthquakes (i.e. Izmit and Duzce Earthquakes in 1999, Kobe Earthquake in 1995 and Northridge Earthquake in 1994). Considering the need for precise assessment tools to determine seismic performance level, most of earthquake hazardous countries try to include performance based assessment in their seismic codes. Recently, Turkish Earthquake Code 2007 (TEC'07), which was put into effect in March 2007, also introduced linear and non-linear assessment procedures to be applied prior to building retrofitting. In this paper, a comparative study is performed on the code-based seismic assessment of RC buildings with linear static methods of analysis, selecting an existing RC building. The basic principles dealing the procedure of seismic performance evaluations for existing RC buildings according to Eurocode 8 and TEC'07 will be outlined and compared. Then the procedure is applied to a real case study building is selected which is exposed to 1998 Adana-Ceyhan Earthquake in Turkey, the seismic action of Ms = 6.3 with a maximum ground acceleration of 0.28 g It is a six-storey RC residential building with a total of 14.65 m height, composed of orthogonal frames, symmetrical in y direction and it does not have any significant structural irregularities. The rectangular shaped planar dimensions are 16.40 mx7.80 m = 127.90 m 2 with five spans in x and two spans in y directions. It was reported that the building had been moderately damaged during the 1998 earthquake and retrofitting process was suggested by the authorities with adding shear-walls to the system. The computations show that the performing methods of analysis with linear approaches using either Eurocode 8 or TEC'07 independently produce similar performance levels of collapse for the critical storey of the structure. The computed base shear value according to Eurocode is much higher
Toprak, A. Emre; Gülay, F. Gülten; Ruge, Peter
2008-07-01
Determination of seismic performance of existing buildings has become one of the key concepts in structural analysis topics after recent earthquakes (i.e. Izmit and Duzce Earthquakes in 1999, Kobe Earthquake in 1995 and Northridge Earthquake in 1994). Considering the need for precise assessment tools to determine seismic performance level, most of earthquake hazardous countries try to include performance based assessment in their seismic codes. Recently, Turkish Earthquake Code 2007 (TEC'07), which was put into effect in March 2007, also introduced linear and non-linear assessment procedures to be applied prior to building retrofitting. In this paper, a comparative study is performed on the code-based seismic assessment of RC buildings with linear static methods of analysis, selecting an existing RC building. The basic principles dealing the procedure of seismic performance evaluations for existing RC buildings according to Eurocode 8 and TEC'07 will be outlined and compared. Then the procedure is applied to a real case study building is selected which is exposed to 1998 Adana-Ceyhan Earthquake in Turkey, the seismic action of Ms = 6.3 with a maximum ground acceleration of 0.28 g It is a six-storey RC residential building with a total of 14.65 m height, composed of orthogonal frames, symmetrical in y direction and it does not have any significant structural irregularities. The rectangular shaped planar dimensions are 16.40 m×7.80 m = 127.90 m2 with five spans in x and two spans in y directions. It was reported that the building had been moderately damaged during the 1998 earthquake and retrofitting process was suggested by the authorities with adding shear-walls to the system. The computations show that the performing methods of analysis with linear approaches using either Eurocode 8 or TEC'07 independently produce similar performance levels of collapse for the critical storey of the structure. The computed base shear value according to Eurocode is much higher
A unified frame of predicting side effects of drugs by using linear neighborhood similarity.
Zhang, Wen; Yue, Xiang; Liu, Feng; Chen, Yanlin; Tu, Shikui; Zhang, Xining
2017-12-14
Drug side effects are one of main concerns in the drug discovery, which gains wide attentions. Investigating drug side effects is of great importance, and the computational prediction can help to guide wet experiments. As far as we known, a great number of computational methods have been proposed for the side effect predictions. The assumption that similar drugs may induce same side effects is usually employed for modeling, and how to calculate the drug-drug similarity is critical in the side effect predictions. In this paper, we present a novel measure of drug-drug similarity named "linear neighborhood similarity", which is calculated in a drug feature space by exploring linear neighborhood relationship. Then, we transfer the similarity from the feature space into the side effect space, and predict drug side effects by propagating known side effect information through a similarity-based graph. Under a unified frame based on the linear neighborhood similarity, we propose method "LNSM" and its extension "LNSM-SMI" to predict side effects of new drugs, and propose the method "LNSM-MSE" to predict unobserved side effect of approved drugs. We evaluate the performances of LNSM and LNSM-SMI in predicting side effects of new drugs, and evaluate the performances of LNSM-MSE in predicting missing side effects of approved drugs. The results demonstrate that the linear neighborhood similarity can improve the performances of side effect prediction, and the linear neighborhood similarity-based methods can outperform existing side effect prediction methods. More importantly, the proposed methods can predict side effects of new drugs as well as unobserved side effects of approved drugs under a unified frame.
Basic prediction techniques in modern video coding standards
Kim, Byung-Gyu
2016-01-01
This book discusses in detail the basic algorithms of video compression that are widely used in modern video codec. The authors dissect complicated specifications and present material in a way that gets readers quickly up to speed by describing video compression algorithms succinctly, without going to the mathematical details and technical specifications. For accelerated learning, hybrid codec structure, inter- and intra- prediction techniques in MPEG-4, H.264/AVC, and HEVC are discussed together. In addition, the latest research in the fast encoder design for the HEVC and H.264/AVC is also included.
Hundebøll, Martin; Pedersen, Morten Videbæk; Roetter, Daniel Enrique Lucani
2014-01-01
This work studies the potential and impact of the FRANC network coding protocol for delivering high quality Dynamic Adaptive Streaming over HTTP (DASH) in wireless networks. Although DASH aims to tailor the video quality rate based on the available throughput to the destination, it relies...
Dropped fuel damage prediction techniques and the DROPFU code
Mottershead, K.J.; Beardsmore, D.W.; Money, G.
1995-01-01
During refuelling, and fuel handling, at UK Advanced Gas Cooled Reactor (AGR) stations it is recognised that the accidental dropping of fuel is a possibility. This can result in dropping individual fuel elements, a complete fuel stringer, or a whole assembly. The techniques for assessing potential damage have been developed over a number of years. This paper describes how damage prediction techniques have subsequently evolved to meet changing needs. These have been due to later fuel designs and the need to consider drops in facilities outside the reactor. The paper begins by briefly describing AGR fuel and possible dropped fuel scenarios. This is followed by a brief summary of the damage mechanisms and the assessment procedure as it was first developed. The paper then describes the additional test work carried out, followed by the detailed numerical modelling. Finally, the paper describes the extensions to the practical assessment methods. (author)
Structural Dynamic Analyses And Test Predictions For Spacecraft Structures With Non-Linearities
Vergniaud, Jean-Baptiste; Soula, Laurent; Newerla, Alfred
2012-07-01
The overall objective of the mechanical development and verification process is to ensure that the spacecraft structure is able to sustain the mechanical environments encountered during launch. In general the spacecraft structures are a-priori assumed to behave linear, i.e. the responses to a static load or dynamic excitation, respectively, will increase or decrease proportionally to the amplitude of the load or excitation induced. However, past experiences have shown that various non-linearities might exist in spacecraft structures and the consequences of their dynamic effects can significantly affect the development and verification process. Current processes are mainly adapted to linear spacecraft structure behaviour. No clear rules exist for dealing with major structure non-linearities. They are handled outside the process by individual analysis and margin policy, and analyses after tests to justify the CLA coverage. Non-linearities can primarily affect the current spacecraft development and verification process on two aspects. Prediction of flights loads by launcher/satellite coupled loads analyses (CLA): only linear satellite models are delivered for performing CLA and no well-established rules exist how to properly linearize a model when non- linearities are present. The potential impact of the linearization on the results of the CLA has not yet been properly analyzed. There are thus difficulties to assess that CLA results will cover actual flight levels. Management of satellite verification tests: the CLA results generated with a linear satellite FEM are assumed flight representative. If the internal non- linearities are present in the tested satellite then there might be difficulties to determine which input level must be passed to cover satellite internal loads. The non-linear behaviour can also disturb the shaker control, putting the satellite at risk by potentially imposing too high levels. This paper presents the results of a test campaign performed in
Validation of favor code linear elastic fracture solutions for finite-length flaw geometries
Dickson, T.L.; Keeney, J.A.; Bryson, J.W.
1995-01-01
One of the current tasks within the US Nuclear Regulatory Commission (NRC)-funded Heavy Section Steel Technology Program (HSST) at Oak Ridge National Laboratory (ORNL) is the continuing development of the FAVOR (Fracture, analysis of Vessels: Oak Ridge) computer code. FAVOR performs structural integrity analyses of embrittled nuclear reactor pressure vessels (RPVs) with stainless steel cladding, to evaluate compliance with the applicable regulatory criteria. Since the initial release of FAVOR, the HSST program has continued to enhance the capabilities of the FAVOR code. ABAQUS, a nuclear quality assurance certified (NQA-1) general multidimensional finite element code with fracture mechanics capabilities, was used to generate a database of stress-intensity-factor influence coefficients (SIFICs) for a range of axially and circumferentially oriented semielliptical inner-surface flaw geometries applicable to RPVs with an internal radius (Ri) to wall thickness (w) ratio of 10. This database of SIRCs has been incorporated into a development version of FAVOR, providing it with the capability to perform deterministic and probabilistic fracture analyses of RPVs subjected to transients, such as pressurized thermal shock (PTS), for various flaw geometries. This paper discusses the SIFIC database, comparisons with other investigators, and some of the benchmark verification problem specifications and solutions
Fast bi-directional prediction selection in H.264/MPEG-4 AVC temporal scalable video coding.
Lin, Hung-Chih; Hang, Hsueh-Ming; Peng, Wen-Hsiao
2011-12-01
In this paper, we propose a fast algorithm that efficiently selects the temporal prediction type for the dyadic hierarchical-B prediction structure in the H.264/MPEG-4 temporal scalable video coding (SVC). We make use of the strong correlations in prediction type inheritance to eliminate the superfluous computations for the bi-directional (BI) prediction in the finer partitions, 16×8/8×16/8×8 , by referring to the best temporal prediction type of 16 × 16. In addition, we carefully examine the relationship in motion bit-rate costs and distortions between the BI and the uni-directional temporal prediction types. As a result, we construct a set of adaptive thresholds to remove the unnecessary BI calculations. Moreover, for the block partitions smaller than 8 × 8, either the forward prediction (FW) or the backward prediction (BW) is skipped based upon the information of their 8 × 8 partitions. Hence, the proposed schemes can efficiently reduce the extensive computational burden in calculating the BI prediction. As compared to the JSVM 9.11 software, our method saves the encoding time from 48% to 67% for a large variety of test videos over a wide range of coding bit-rates and has only a minor coding performance loss. © 2011 IEEE
Machine learning-based methods for prediction of linear B-cell epitopes.
Wang, Hsin-Wei; Pai, Tun-Wen
2014-01-01
B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.
Applications of Kalman filters based on non-linear functions to numerical weather predictions
G. Galanis
2006-10-01
Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.
Applications of Kalman filters based on non-linear functions to numerical weather predictions
G. Galanis
2006-10-01
Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.
Glazer, S.; Todreas, N.; Rohsenow, W.; Sonin, A.
1981-02-01
This document is intended as a user/programmer manual for the TRANSENERGY-S computer code. The code represents an extension of the steady state ENERGY model, originally developed by E. Khan, to predict coolant and fuel pin temperatures in a single LMFBR core assembly during transient events. Effects which may be modelled in the analysis include temporal variation in gamma heating in the coolant and duct wall, rod power production, coolant inlet temperature, coolant flow rate, and thermal boundary conditions around the single assembly. Numerical formulations of energy equations in the fuel and coolant are presented, and the solution schemes and stability criteria are discussed. A detailed description of the input deck preparation is presented, as well as code logic flowcharts, and a complete program listing. TRANSENERGY-S code predictions are compared with those of two different versions of COBRA, and partial results of a 61 pin bundle test case are presented
I. Udeh; J.O. Isikwenu and G. Ukughere
2011-01-01
The objectives of this study were to compare the performance characteristics of four strains of broiler chicken from 2 to 8 weeks of age and predict body weight of the broilers using linear body measurements. The four strains of broiler chicken used were Anak, Arbor Acre, Ross and Marshall. The parameters recorded were bodyweight, weight gain, total feed intake, feed conversion ratio, mortality and some linear body measurements (body length, body width, breast width, drumstick length, shank l...
Predicting musically induced emotions from physiological inputs: linear and neural network models.
Russo, Frank A; Vempala, Naresh N; Sandstrom, Gillian M
2013-01-01
Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of "felt" emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants-heart rate (HR), respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA) dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a non-linear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The non-linear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the non-linear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.
Malatara, G.; Kappas, K.; Sphiris, N.
1994-01-01
In this work, a Monte Carlo EGS4 code was used to simulate radiation transport through linear accelerators to produce and score energy spectra and angular distributions of 6, 12, 15 and 25 MeV bremsstrahlung photons exiting from different accelerator treatment heads. The energy spectra was used as input for a convolution method program to calculate the tissue-maximum ratio in water. 100.000 histories are recorded in the scoring plane for each simulation. The validity of the Monte Carlo simulation and the precision to the calculated spectra have been verified experimentally and were in good agreement. We believe that the accurate simulation of the different components of the linear accelerator head is very important for the precision of the results. The results of the Monte Carlo and the Convolution Method can be compared with experimental data for verification and they are powerful and practical tools to generate accurate spectra and dosimetric data. (authors)
Iterated non-linear model predictive control based on tubes and contractive constraints.
Murillo, M; Sánchez, G; Giovanini, L
2016-05-01
This paper presents a predictive control algorithm for non-linear systems based on successive linearizations of the non-linear dynamic around a given trajectory. A linear time varying model is obtained and the non-convex constrained optimization problem is transformed into a sequence of locally convex ones. The robustness of the proposed algorithm is addressed adding a convex contractive constraint. To account for linearization errors and to obtain more accurate results an inner iteration loop is added to the algorithm. A simple methodology to obtain an outer bounding-tube for state trajectories is also presented. The convergence of the iterative process and the stability of the closed-loop system are analyzed. The simulation results show the effectiveness of the proposed algorithm in controlling a quadcopter type unmanned aerial vehicle. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Great Expectations: Is there Evidence for Predictive Coding in Auditory Cortex?
Heilbron, Micha; Chait, Maria
2017-08-04
Predictive coding is possibly one of the most influential, comprehensive, and controversial theories of neural function. While proponents praise its explanatory potential, critics object that key tenets of the theory are untested or even untestable. The present article critically examines existing evidence for predictive coding in the auditory modality. Specifically, we identify five key assumptions of the theory and evaluate each in the light of animal, human and modeling studies of auditory pattern processing. For the first two assumptions - that neural responses are shaped by expectations and that these expectations are hierarchically organized - animal and human studies provide compelling evidence. The anticipatory, predictive nature of these expectations also enjoys empirical support, especially from studies on unexpected stimulus omission. However, for the existence of separate error and prediction neurons, a key assumption of the theory, evidence is lacking. More work exists on the proposed oscillatory signatures of predictive coding, and on the relation between attention and precision. However, results on these latter two assumptions are mixed or contradictory. Looking to the future, more collaboration between human and animal studies, aided by model-based analyses will be needed to test specific assumptions and implementations of predictive coding - and, as such, help determine whether this popular grand theory can fulfill its expectations. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Goriely, S.; Hilaire, S.; Koning, A.J
2008-01-01
Context. Nuclear reaction rates of astrophysical applications are traditionally determined on the basis of Hauser-Feshbach reaction codes. These codes adopt a number of approximations that have never been tested, such as a simplified width fluctuation correction, the neglect of delayed or multiple-particle emission during the electromagnetic decay cascade, or the absence of the pre-equilibrium contribution at increasing incident energies. Aims. The reaction code TALYS has been recently updated to estimate the Maxwellian-averaged reaction rates that are of astrophysical relevance. These new developments enable the reaction rates to be calculated with increased accuracy and reliability and the approximations of previous codes to be investigated. Methods. The TALYS predictions for the thermonuclear rates of relevance to astrophysics are detailed and compared with those derived by widely-used codes for the same nuclear ingredients. Results. It is shown that TALYS predictions may differ significantly from those of previous codes, in particular for nuclei for which no or little nuclear data is available. The pre-equilibrium process is shown to influence the astrophysics rates of exotic neutron-rich nuclei significantly. For the first time, the Maxwellian- averaged (n, 2n) reaction rate is calculated for all nuclei and its competition with the radiative capture rate is discussed. Conclusions. The TALYS code provides a new tool to estimate all nuclear reaction rates of relevance to astrophysics with improved accuracy and reliability. (authors)
Ogawa, Hiromichi; Ohnuki, Toshihiko
1986-07-01
A computer code (MIGSTEM-FIT) has been developed to determine the prediction parameters, retardation factor, water flow velocity, dispersion coefficient, etc., of radionuclide migration in soil layer from the concentration distribution of radionuclide in soil layer or in effluent. In this code, the solution of the predicting equation for radionuclide migration is compared with the concentration distribution measured, and the most adequate values of parameter can be determined by the flexible tolerance method. The validity of finite differential method, which was one of the method to solve the predicting equation, was confirmed by comparison with the analytical solution, and also the validity of fitting method was confirmed by the fitting of the concentration distribution calculated from known parameters. From the examination about the error, it was found that the error of the parameter obtained by using this code was smaller than that of the concentration distribution measured. (author)
Non-linear heat transfer computer code by finite element method
Nagato, Kotaro; Takikawa, Noboru
1977-01-01
The computer code THETA-2D for the calculation of temperature distribution by the two-dimensional finite element method was made for the analysis of heat transfer in a high temperature structure. Numerical experiment was performed for the numerical integration of the differential equation of heat conduction. The Runge-Kutta method of the numerical experiment produced an unstable solution. A stable solution was obtained by the β method with the β value of 0.35. In high temperature structures, the radiative heat transfer can not be neglected. To introduce a term of the radiative heat transfer, a functional neglecting the radiative heat transfer was derived at first. Then, the radiative term was added after the discretion by variation method. Five model calculations were carried out by the computer code. Calculation of steady heat conduction was performed. When estimated initial temperature is 1,000 degree C, reasonable heat blance was obtained. In case of steady-unsteady temperature calculation, the time integral by THETA-2D turned out to be under-estimation for enthalpy change. With a one-dimensional model, the temperature distribution in a structure, in which heat conductivity is dependent on temperature, was calculated. Calculation with a model which has a void inside was performed. Finally, model calculation for a complex system was carried out. (Kato, T.)
Establishment the code for prediction of waste volume on NPP decommissioning
Cho, W. H.; Park, S. K.; Choi, Y. D.; Kim, I. S.; Moon, J. K.
2013-01-01
In practice, decommissioning waste volume can be estimated appropriately by finding the differences between prediction and actual operation and considering the operational problem or supplementary matters. So in the nuclear developed countries such as U.S. or Japan, the decommissioning waste volume is predicted on the basis of the experience in their own decommissioning projects. Because of the contamination caused by radioactive material, decontamination activity and management of radio-active waste should be considered in decommissioning of nuclear facility unlike the usual plant or facility. As the decommissioning activity is performed repeatedly, data for similar activities are accumulated, and optimal strategy can be achieved by comparison with the predicted strategy. Therefore, a variety of decommissioning experiences are the most important. In Korea, there is no data on the decommissioning of commercial nuclear power plants yet. However, KAERI has accumulated the basis decommissioning data of nuclear facility through decommissioning of research reactor (KRR-2) and uranium conversion plant (UCP). And DECOMMIS(DECOMMissioning Information Management System) was developed to provide and manage the whole data of decommissioning project. Two codes, FAC code and WBS code, were established in this process. FAC code is the one which is classified by decommissioning target of nuclear facility, and WBS code is classified by each decommissioning activity. The reason why two codes where created is that the codes used in DEFACS (Decommissioning Facility Characterization management System) and DEWOCS (Decommissioning Work-unit productivity Calculation System) are different from each other, and they were classified each purpose. DEFACS which manages the facility needs the code that categorizes facility characteristics, and DEWOCS which calculates unit productivity needs the code that categorizes decommissioning waste volume. KAERI has accumulated decommissioning data of KRR
Modification in the FUDA computer code to predict fuel performance at high burnup
Das, M; Arunakumar, B V; Prasad, P N [Nuclear Power Corp., Mumbai (India)
1997-08-01
The computer code FUDA (FUel Design Analysis) participated in the blind exercises organized by the IAEA CRP (Co-ordinated Research Programme) on FUMEX (Fuel Modelling at Extended Burnup). While the code prediction compared well with the experiments at Halden under various parametric and operating conditions, the fission gas release and fission gas pressure were found to be slightly over-predicted, particularly at high burnups. In view of the results of 6 FUMEX cases, the main models and submodels of the code were reviewed and necessary improvements were made. The new version of the code FUDA MOD 2 is now able to predict fuel performance parameter for burn-ups up to 50000 MWD/TeU. The validation field of the code has been extended to prediction of thorium oxide fuel performance. An analysis of local deformations at pellet interfaces and near the end caps is carried out considering the hourglassing of the pellet by finite element technique. (author). 15 refs, 1 fig.
Modification in the FUDA computer code to predict fuel performance at high burnup
Das, M.; Arunakumar, B.V.; Prasad, P.N.
1997-01-01
The computer code FUDA (FUel Design Analysis) participated in the blind exercises organized by the IAEA CRP (Co-ordinated Research Programme) on FUMEX (Fuel Modelling at Extended Burnup). While the code prediction compared well with the experiments at Halden under various parametric and operating conditions, the fission gas release and fission gas pressure were found to be slightly over-predicted, particularly at high burnups. In view of the results of 6 FUMEX cases, the main models and submodels of the code were reviewed and necessary improvements were made. The new version of the code FUDA MOD 2 is now able to predict fuel performance parameter for burn-ups up to 50000 MWD/TeU. The validation field of the code has been extended to prediction of thorium oxide fuel performance. An analysis of local deformations at pellet interfaces and near the end caps is carried out considering the hourglassing of the pellet by finite element technique. (author). 15 refs, 1 fig
FIRAC - a computer code to predict fire accident effects in nuclear facilities
Bolstad, J.W.; Foster, R.D.; Gregory, W.S.
1983-01-01
FIRAC is a medium-sized computer code designed to predict fire-induced flows, temperatures, and material transport within the ventilating systems and other airflow pathways in nuclear-related facilities. The code is designed to analyze the behavior of interconnected networks of rooms and typical ventilation system components. This code is one in a family of computer codes that is designed to provide improved methods of safety analysis for the nuclear industry. The structure of this code closely follows that of the previously developed TVENT and EVENT codes. Because a lumped-parameter formulation is used, this code is particularly suitable for calculating the effects of fires in the far field (that is, in regions removed from the fire compartment), where the fire may be represented parametrically. However, a fire compartment model to simulate conditions in the enclosure is included. This model provides transport source terms to the ventilation system that can affect its operation and in turn affect the fire. A basic material transport capability that features the effects of convection, deposition, entrainment, and filtration of material is included. The interrelated effects of filter plugging, heat transfer, gas dynamics, and material transport are taken into account. In this paper the authors summarize the physical models used to describe the gas dynamics, material transport, and heat transfer processes. They also illustrate how a typical facility is modeled using the code
Deep linear autoencoder and patch clustering-based unified one-dimensional coding of image and video
Li, Honggui
2017-09-01
This paper proposes a unified one-dimensional (1-D) coding framework of image and video, which depends on deep learning neural network and image patch clustering. First, an improved K-means clustering algorithm for image patches is employed to obtain the compact inputs of deep artificial neural network. Second, for the purpose of best reconstructing original image patches, deep linear autoencoder (DLA), a linear version of the classical deep nonlinear autoencoder, is introduced to achieve the 1-D representation of image blocks. Under the circumstances of 1-D representation, DLA is capable of attaining zero reconstruction error, which is impossible for the classical nonlinear dimensionality reduction methods. Third, a unified 1-D coding infrastructure for image, intraframe, interframe, multiview video, three-dimensional (3-D) video, and multiview 3-D video is built by incorporating different categories of videos into the inputs of patch clustering algorithm. Finally, it is shown in the results of simulation experiments that the proposed methods can simultaneously gain higher compression ratio and peak signal-to-noise ratio than those of the state-of-the-art methods in the situation of low bitrate transmission.
Model for predicting non-linear crack growth considering load sequence effects (LOSEQ)
Fuehring, H.
1982-01-01
A new analytical model for predicting non-linear crack growth is presented which takes into account the retardation as well as the acceleration effects due to irregular loading. It considers not only the maximum peak of a load sequence to effect crack growth but also all other loads of the history according to a generalised memory criterion. Comparisons between crack growth predicted by using the LOSEQ-programme and experimentally observed data are presented. (orig.) [de
Assessment of subchannel code ASSERT-PV for flow-distribution predictions
Nava-Dominguez, A.; Rao, Y.F.; Waddington, G.M.
2014-01-01
Highlights: • Assessment of the subchannel code ASSERT-PV 3.2 for the prediction of flow distribution. • Open literature and in-house experimental data to quantify ASSERT-PV predictions. • Model changes assessed against vertical and horizontal flow experiments. • Improvement of flow-distribution predictions under CANDU-relevant conditions. - Abstract: This paper reports an assessment of the recently released subchannel code ASSERT-PV 3.2 for the prediction of flow-distribution in fuel bundles, including subchannel void fraction, quality and mass fluxes. Experimental data from open literature and from in-house tests are used to assess the flow-distribution models in ASSERT-PV 3.2. The prediction statistics using the recommended model set of ASSERT-PV 3.2 are compared to those from previous code versions. Separate-effects sensitivity studies are performed to quantify the contribution of each flow-distribution model change or enhancement to the improvement in flow-distribution prediction. The assessment demonstrates significant improvement in the prediction of flow-distribution in horizontal fuel channels containing CANDU bundles
Assessment of subchannel code ASSERT-PV for flow-distribution predictions
Nava-Dominguez, A., E-mail: navadoma@aecl.ca; Rao, Y.F., E-mail: raoy@aecl.ca; Waddington, G.M., E-mail: waddingg@aecl.ca
2014-08-15
Highlights: • Assessment of the subchannel code ASSERT-PV 3.2 for the prediction of flow distribution. • Open literature and in-house experimental data to quantify ASSERT-PV predictions. • Model changes assessed against vertical and horizontal flow experiments. • Improvement of flow-distribution predictions under CANDU-relevant conditions. - Abstract: This paper reports an assessment of the recently released subchannel code ASSERT-PV 3.2 for the prediction of flow-distribution in fuel bundles, including subchannel void fraction, quality and mass fluxes. Experimental data from open literature and from in-house tests are used to assess the flow-distribution models in ASSERT-PV 3.2. The prediction statistics using the recommended model set of ASSERT-PV 3.2 are compared to those from previous code versions. Separate-effects sensitivity studies are performed to quantify the contribution of each flow-distribution model change or enhancement to the improvement in flow-distribution prediction. The assessment demonstrates significant improvement in the prediction of flow-distribution in horizontal fuel channels containing CANDU bundles.
Lee, Dongyul; Lee, Chaewoo
2014-01-01
The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.
Dongyul Lee
2014-01-01
Full Text Available The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC with adaptive modulation and coding (AMC provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.
Horiuchi, Toshiyuki; Watanabe, Jun; Suzuki, Yuta; Iwasaki, Jun-ya
2017-05-01
Two dimensional code marks are often used for the production management. In particular, in the production lines of liquid-crystal-display panels and others, data on fabrication processes such as production number and process conditions are written on each substrate or device in detail, and they are used for quality managements. For this reason, lithography system specialized in code mark printing is developed. However, conventional systems using lamp projection exposure or laser scan exposure are very expensive. Therefore, development of a low-cost exposure system using light emitting diodes (LEDs) and optical fibers with squared ends arrayed in a matrix is strongly expected. In the past research, feasibility of such a new exposure system was demonstrated using a handmade system equipped with 100 LEDs with a central wavelength of 405 nm, a 10×10 matrix of optical fibers with 1 mm square ends, and a 10X projection lens. Based on these progresses, a new method for fabricating large-scale arrays of finer fibers with squared ends was developed in this paper. At most 40 plastic optical fibers were arranged in a linear gap of an arraying instrument, and simultaneously squared by heating them on a hotplate at 120°C for 7 min. Fiber sizes were homogeneous within 496+/-4 μm. In addition, average light leak was improved from 34.4 to 21.3% by adopting the new method in place of conventional one by one squaring method. Square matrix arrays necessary for printing code marks will be obtained by piling the newly fabricated linear arrays up.
Cosmological N-body simulations with a tree code - Fluctuations in the linear and nonlinear regimes
Suginohara, Tatsushi; Suto, Yasushi; Bouchet, F.R.; Hernquist, L.
1991-01-01
The evolution of gravitational systems is studied numerically in a cosmological context using a hierarchical tree algorithm with fully periodic boundary conditions. The simulations employ 262,144 particles, which are initially distributed according to scale-free power spectra. The subsequent evolution is followed in both flat and open universes. With this large number of particles, the discretized system can accurately model the linear phase. It is shown that the dynamics in the nonlinear regime depends on both the spectral index n and the density parameter Omega. In Omega = 1 universes, the evolution of the two-point correlation function Xi agrees well with similarity solutions for Xi greater than about 100 but its slope is steeper in open models with the same n. 28 refs
Lee, Jin-Yong . E-mail jinyong1@fnctech.com; Lee, Jung-Jae; Park, Goon-Cherl . E-mail parkgc@snu.ac.kr
2006-01-01
With the rising concerns regarding the time and space dependent hydrogen behavior in severe accidents, the calculation for local hydrogen combustion in compartment has been attempted using CFD codes like GOTHIC. In particular, the space resolved hydrogen combustion analysis is essential to address certain safety issues such as the safety components survivability, and to determine proper positions for hydrogen control devices as e.q. recombiners or igniters. In the GOTHIC 6.1b code, there are many advanced features associated with the hydrogen burn models to enhance its calculation capability. In this study, we performed premixed hydrogen/air combustion experiments with an upright, rectangular shaped, combustion chamber of dimensions 1 m x 0.024 m x 1 m. The GOTHIC 6.1b code was used to simulate the hydrogen/air combustion experiments, and its prediction capability was assessed by comparing the experimental with multidimensional calculational results. Especially, the prediction capability of the GOTHIC 6.1b code for local hydrogen flame propagation phenomena was examined. For some cases, comparisons are also presented for lumped modeling of hydrogen combustion. By evaluating the effect of parametric simulations, we present some instructions for local hydrogen combustion analysis using the GOTHIC 6.1b code. From the analyses results, it is concluded that the modeling parameter of GOTHIC 6.1b code should be modified when applying the mechanistic burn model for hydrogen propagation analysis in small geometry
Bayesian prediction of spatial count data using generalized linear mixed models
Christensen, Ole Fredslund; Waagepetersen, Rasmus Plenge
2002-01-01
Spatial weed count data are modeled and predicted using a generalized linear mixed model combined with a Bayesian approach and Markov chain Monte Carlo. Informative priors for a data set with sparse sampling are elicited using a previously collected data set with extensive sampling. Furthermore, ...
Fung, Karen; ElAtia, Samira
2015-01-01
Using Hierarchical Linear Modelling (HLM), this study aimed to identify factors such as ESL/ELL/EAL status that would predict students' reading performance in an English language arts exam taken across Canada. Using data from the 2007 administration of the Pan-Canadian Assessment Program (PCAP) along with the accompanying surveys for students and…
An improved robust model predictive control for linear parameter-varying input-output models
Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.
2018-01-01
This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal
Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik
2014-01-01
This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP...
Akbulut, Yavuz
2007-01-01
Factors predicting vocabulary learning and reading comprehension of advanced language learners of English in a linear multimedia text were investigated in the current study. Predictor variables of interest were multimedia type, reading proficiency, learning styles, topic interest and background knowledge about the topic. The outcome variables of…
Hickok, Gregory
2012-01-01
Speech recognition is an active process that involves some form of predictive coding. This statement is relatively uncontroversial. What is less clear is the source of the prediction. The dual-stream model of speech processing suggests that there are two possible sources of predictive coding in speech perception: the motor speech system and the…
Convergence Guaranteed Nonlinear Constraint Model Predictive Control via I/O Linearization
Xiaobing Kong
2013-01-01
Full Text Available Constituting reliable optimal solution is a key issue for the nonlinear constrained model predictive control. Input-output feedback linearization is a popular method in nonlinear control. By using an input-output feedback linearizing controller, the original linear input constraints will change to nonlinear constraints and sometimes the constraints are state dependent. This paper presents an iterative quadratic program (IQP routine on the continuous-time system. To guarantee its convergence, another iterative approach is incorporated. The proposed algorithm can reach a feasible solution over the entire prediction horizon. Simulation results on both a numerical example and the continuous stirred tank reactors (CSTR demonstrate the effectiveness of the proposed method.
A study on two phase flows of linear compressors for the prediction of refrigerant leakage
Hwang, Il Sun; Lee, Young Lim; Oh, Won Sik; Park, Kyeong Bae
2015-01-01
Usage of linear compressors is on the rise due to their high efficiency. In this paper, leakage of a linear compressor has been studied through numerical analysis and experiments. First, nitrogen leakage for a stagnant piston with fixed cylinder pressure as well as for a moving piston with fixed cylinder pressure was analyzed to verify the validity of the two-phase flow analysis model. Next, refrigerant leakage of a linear compressor in operation was finally predicted through 3-dimensional unsteady, two phase flow CFD (Computational fluid dynamics). According to the research results, the numerical analyses for the fixed cylinder pressure models were in good agreement with the experimental results. The refrigerant leakage of the linear compressor in operation mainly occurred through the oil exit and the leakage became negligible after about 0.4s following operation where the leakage became lower than 2.0x10 -4 kg/s.
Status of development of a code for predicting the migration of ground additions - MOGRA
Amano, Hikaru; Uchida, Shigeo; Matsuoka, Syungo; Ikeda, Hiroshi; Hayashi, Hiroko; Kurosawa, Naohiro
2003-01-01
MOGRA (Migration Of GRound Additions) is a migration prediction code for toxic ground additions including radioactive materials in a terrestrial environment. MOGRA consists of computational codes that are applicable to various evaluation target systems, and can be used on personal computers. The computational code has the dynamic compartment analysis block at its core, the graphical user interface (GUI) for computation parameter settings and results displays, data bases and so on. The compartments are obtained by classifying various natural environments into groups that exhibit similar properties. These codes are able to create or delete compartments and set the migration of environmental-load substances between compartments by a simple mouse operation. The system features universality and excellent expandability in the application of computations to various nuclides. (author)
Godin, Bruno; Mayer, Frédéric; Agneessens, Richard; Gerin, Patrick; Dardenne, Pierre; Delfosse, Philippe; Delcarte, Jérôme
2015-01-01
The reliability of different models to predict the biochemical methane potential (BMP) of various plant biomasses using a multispecies dataset was compared. The most reliable prediction models of the BMP were those based on the near infrared (NIR) spectrum compared to those based on the chemical composition. The NIR predictions of local (specific regression and non-linear) models were able to estimate quantitatively, rapidly, cheaply and easily the BMP. Such a model could be further used for biomethanation plant management and optimization. The predictions of non-linear models were more reliable compared to those of linear models. The presentation form (green-dried, silage-dried and silage-wet form) of biomasses to the NIR spectrometer did not influence the performances of the NIR prediction models. The accuracy of the BMP method should be improved to enhance further the BMP prediction models. Copyright © 2014 Elsevier Ltd. All rights reserved.
Comparison of LIFE-4 and TEMECH code predictions with TREAT transient test data
Gneiting, B.C.; Bard, F.E.; Hunter, C.W.
1984-09-01
Transient tests in the TREAT reactor were performed on FFTF Reference design mixed-oxide fuel pins, most of which had received prior steady-state irradiation in the EBR-II reactor. These transient test results provide a data base for calibration and verification of fuel performance codes and for evaluation of processes that affect pin damage during transient events. This paper presents a comparison of the LIFE-4 and TEMECH fuel pin thermal/mechanical analysis codes with the results from 20 HEDL TREAT experiments, ten of which resulted in pin failure. Both the LIFE-4 and TEMECH codes provided an adequate representation of the thermal and mechanical data from the TREAT experiments. Also, a criterion for 50% probability of pin failure was developed for each code using an average cumulative damage fraction value calculated for the pins that failed. Both codes employ the two major cladding loading mechanisms of differential thermal expansion and central cavity pressurization which were demonstrated by the test results. However, a detailed evaluation of the code predictions shows that the two code systems weigh the loading mechanism differently to reach the same end points of the TREAT transient results
A code MOGRA for predicting and assessing the migration of ground additions
Amano, Hikaru; Atarashi-Andoh, Mariko; Uchida, Shigeo; Matsuoka, Syungo; Ikeda, Hiroshi; Hayashi, Hiroko; Kurosawa, Naohiro
2004-01-01
The environment should be protected from the toxic effects of not only ionizing radiation but also any other environmental load materials. A Code MOGRA (Migration Of GRound Additions) is a migration prediction code for toxic ground additions including radioactive materials in a terrestrial environment, which consists of computational codes that are applicable to various evaluation target systems, and can be used on personal computers for not only the purpose of the migration analysis but also the environmental assessment to livings of the environmental load materials. The functionality of MOGRA has been verified by applying it in the analyses of the migration rates of radioactive substances from the atmosphere to soils and plants and flow rates into the rivers. Migration of radionuclides in combinations of hypothetical various land utilization areas was also verified. The system can analyze the dynamic changes of target radionuclide's concentrations in each compartment, fluxes from one compartment to another compartment. The code MOGRA has varieties of databases, which is included in an additional code MOGRA-DB. This additional code MOGRA-DB consists of radionuclides decay chart, distribution coefficients between solid and liquid, transfer factors from soil to plant, transfer coefficients from feed to beef and milk, concentration factors, and age dependent dose conversion factors for many radionuclides. Another additional code MOGRA-MAP can take in graphic map such as JPEG, TIFF, BITMAP, and GIF files, and calculate the square measure of the target land. (author)
Suzuki, Makoto; Sugimura, Yuko; Yamada, Sumio; Omori, Yoshitsugu; Miyamoto, Masaaki; Yamamoto, Jun-ichi
2013-01-01
Cognitive disorders in the acute stage of stroke are common and are important independent predictors of adverse outcome in the long term. Despite the impact of cognitive disorders on both patients and their families, it is still difficult to predict the extent or duration of cognitive impairments. The objective of the present study was, therefore, to provide data on predicting the recovery of cognitive function soon after stroke by differential modeling with logarithmic and linear regression. This study included two rounds of data collection comprising 57 stroke patients enrolled in the first round for the purpose of identifying the time course of cognitive recovery in the early-phase group data, and 43 stroke patients in the second round for the purpose of ensuring that the correlation of the early-phase group data applied to the prediction of each individual's degree of cognitive recovery. In the first round, Mini-Mental State Examination (MMSE) scores were assessed 3 times during hospitalization, and the scores were regressed on the logarithm and linear of time. In the second round, calculations of MMSE scores were made for the first two scoring times after admission to tailor the structures of logarithmic and linear regression formulae to fit an individual's degree of functional recovery. The time course of early-phase recovery for cognitive functions resembled both logarithmic and linear functions. However, MMSE scores sampled at two baseline points based on logarithmic regression modeling could estimate prediction of cognitive recovery more accurately than could linear regression modeling (logarithmic modeling, R(2) = 0.676, PLogarithmic modeling based on MMSE scores could accurately predict the recovery of cognitive function soon after the occurrence of stroke. This logarithmic modeling with mathematical procedures is simple enough to be adopted in daily clinical practice.
A national-scale model of linear features improves predictions of farmland biodiversity.
Sullivan, Martin J P; Pearce-Higgins, James W; Newson, Stuart E; Scholefield, Paul; Brereton, Tom; Oliver, Tom H
2017-12-01
Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse-scale environmental variables such as the area of broad land-cover types. Fine-scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large-scale datasets of their extent prevents their inclusion in large-scale modelling studies.We assessed whether a novel spatial dataset mapping linear and woody-linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively.Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national-scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri-environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.
Prediction of surface cracks from thick-walled pressurized vessels with ASME code
Thieme, W.
1983-01-01
The ASME-Code, Section XI, Appendix A 'Analysis of flow indications' is still non-mandatory for the pressure components of nuclear power plants. It is certainly difficult to take realistic account of the many factors influencing crack propagation while making life predictions. The accuracy of the US guideline is analysed, and its possible applications are roughly outlined. (orig./IHOE) [de
A Predictive Coding Account of Psychotic Symptoms in Autism Spectrum Disorder
van Schalkwyk, Gerrit I.; Volkmar, Fred R.; Corlett, Philip R.
2017-01-01
The co-occurrence of psychotic and autism spectrum disorder (ASD) symptoms represents an important clinical challenge. Here we consider this problem in the context of a computational psychiatry approach that has been applied to both conditions--predictive coding. Some symptoms of schizophrenia have been explained in terms of a failure of top-down…
Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.
Zhang, Wen; Chen, Yanlin; Li, Dingfang
2017-11-25
Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.
Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.
Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu
2016-08-01
This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.
Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling.
Edelman, Eric R; van Kuijk, Sander M J; Hamaekers, Ankie E W; de Korte, Marcel J M; van Merode, Godefridus G; Buhre, Wolfgang F F A
2017-01-01
For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT) per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT) and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA) physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT). We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT). TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related benefits.
Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling
Eric R. Edelman
2017-06-01
Full Text Available For efficient utilization of operating rooms (ORs, accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT. We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT. TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related
Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna
2017-11-01
The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard syllables are faster and more robust when the preceding word context predicts the ending of a familiar word. For unfamiliar, novel word forms, however, word-expectancy violation generates a prediction error response, the strength of which significantly correlates with children's vocabulary scores at 12 months. These results suggest that predictive coding may accelerate word recognition and support early learning of novel words, including not only the learning of heard word forms but also their mapping to meanings. Prediction error may mediate learning via attention, since infants' attention allocation to the entire learning situation in natural environments could account for the link between prediction error and the understanding of word meanings. On the whole, the present results on predictive coding support the view that principles of brain function reported across domains in humans and non-human animals apply to language and its development in the infant brain. A video abstract of this article can be viewed at: http://hy.fi/unitube/video/e1cbb495-41d8-462e-8660-0864a1abd02c. [Correction added on 27 January 2017, after first online publication: The video abstract link was added.]. © 2016 John Wiley & Sons Ltd.
Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling.
Kawashima, Issaku; Kumano, Hiroaki
2017-01-01
Mind-wandering (MW), task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG) variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR) to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.
Predicting musically induced emotions from physiological inputs: Linear and neural network models
Frank A. Russo
2013-08-01
Full Text Available Listening to music often leads to physiological responses. Do these physiological responses contain sufficient information to infer emotion induced in the listener? The current study explores this question by attempting to predict judgments of 'felt' emotion from physiological responses alone using linear and neural network models. We measured five channels of peripheral physiology from 20 participants – heart rate, respiration, galvanic skin response, and activity in corrugator supercilii and zygomaticus major facial muscles. Using valence and arousal (VA dimensions, participants rated their felt emotion after listening to each of 12 classical music excerpts. After extracting features from the five channels, we examined their correlation with VA ratings, and then performed multiple linear regression to see if a linear relationship between the physiological responses could account for the ratings. Although linear models predicted a significant amount of variance in arousal ratings, they were unable to do so with valence ratings. We then used a neural network to provide a nonlinear account of the ratings. The network was trained on the mean ratings of eight of the 12 excerpts and tested on the remainder. Performance of the neural network confirms that physiological responses alone can be used to predict musically induced emotion. The nonlinear model derived from the neural network was more accurate than linear models derived from multiple linear regression, particularly along the valence dimension. A secondary analysis allowed us to quantify the relative contributions of inputs to the nonlinear model. The study represents a novel approach to understanding the complex relationship between physiological responses and musically induced emotion.
Prediction of Mind-Wandering with Electroencephalogram and Non-linear Regression Modeling
Issaku Kawashima
2017-07-01
Full Text Available Mind-wandering (MW, task-unrelated thought, has been examined by researchers in an increasing number of articles using models to predict whether subjects are in MW, using numerous physiological variables. However, these models are not applicable in general situations. Moreover, they output only binary classification. The current study suggests that the combination of electroencephalogram (EEG variables and non-linear regression modeling can be a good indicator of MW intensity. We recorded EEGs of 50 subjects during the performance of a Sustained Attention to Response Task, including a thought sampling probe that inquired the focus of attention. We calculated the power and coherence value and prepared 35 patterns of variable combinations and applied Support Vector machine Regression (SVR to them. Finally, we chose four SVR models: two of them non-linear models and the others linear models; two of the four models are composed of a limited number of electrodes to satisfy model usefulness. Examination using the held-out data indicated that all models had robust predictive precision and provided significantly better estimations than a linear regression model using single electrode EEG variables. Furthermore, in limited electrode condition, non-linear SVR model showed significantly better precision than linear SVR model. The method proposed in this study helps investigations into MW in various little-examined situations. Further, by measuring MW with a high temporal resolution EEG, unclear aspects of MW, such as time series variation, are expected to be revealed. Furthermore, our suggestion that a few electrodes can also predict MW contributes to the development of neuro-feedback studies.
MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing
Lindgreen, Stinus; Gardner, Paul P; Krogh, Anders
2007-01-01
function that considers sequence conservation, covariation and basepairing probabilities. The results show that the method is very competitive to similar programs available today, both in terms of accuracy and computational efficiency. AVAILABILITY: Source code available from http://mastr.binf.ku.dk/......MOTIVATION: As more non-coding RNAs are discovered, the importance of methods for RNA analysis increases. Since the structure of ncRNA is intimately tied to the function of the molecule, programs for RNA structure prediction are necessary tools in this growing field of research. Furthermore......, it is known that RNA structure is often evolutionarily more conserved than sequence. However, few existing methods are capable of simultaneously considering multiple sequence alignment and structure prediction. RESULT: We present a novel solution to the problem of simultaneous structure prediction...
Peng, Hui; Lan, Chaowang; Liu, Yuansheng; Liu, Tao; Blumenstein, Michael; Li, Jinyan
2017-10-03
Disease-related protein-coding genes have been widely studied, but disease-related non-coding genes remain largely unknown. This work introduces a new vector to represent diseases, and applies the newly vectorized data for a positive-unlabeled learning algorithm to predict and rank disease-related long non-coding RNA (lncRNA) genes. This novel vector representation for diseases consists of two sub-vectors, one is composed of 45 elements, characterizing the information entropies of the disease genes distribution over 45 chromosome substructures. This idea is supported by our observation that some substructures (e.g., the chromosome 6 p-arm) are highly preferred by disease-related protein coding genes, while some (e.g., the 21 p-arm) are not favored at all. The second sub-vector is 30-dimensional, characterizing the distribution of disease gene enriched KEGG pathways in comparison with our manually created pathway groups. The second sub-vector complements with the first one to differentiate between various diseases. Our prediction method outperforms the state-of-the-art methods on benchmark datasets for prioritizing disease related lncRNA genes. The method also works well when only the sequence information of an lncRNA gene is known, or even when a given disease has no currently recognized long non-coding genes.
Peter eVuust
2014-10-01
Full Text Available Musical rhythm, consisting of apparently abstract intervals of accented temporal events, has a remarkable capacity to move our minds and bodies. How does the cognitive system enable our experiences of rhythmically complex music? In this paper, we describe some common forms of rhythmic complexity in music and propose the theory of predictive coding as a framework for understanding how rhythm and rhythmic complexity are processed in the brain. We also consider why we feel so compelled by rhythmic tension in music. First, we consider theories of rhythm and meter perception, which provide hierarchical and computational approaches to modeling. Second, we present the theory of predictive coding, which posits a hierarchical organization of brain responses reflecting fundamental, survival-related mechanisms associated with predicting future events. According to this theory, perception and learning is manifested through the brain’s Bayesian minimization of the error between the input to the brain and the brain’s prior expectations. Third, we develop a predictive coding model of musical rhythm, in which rhythm perception is conceptualized as an interaction between what is heard (‘rhythm’ and the brain’s anticipatory structuring of music (‘meter’. Finally, we review empirical studies of the neural and behavioral effects of syncopation, polyrhythm and groove, and propose how these studies can be seen as special cases of the predictive coding theory. We argue that musical rhythm exploits the brain’s general principles of prediction and propose that pleasure and desire for sensorimotor synchronization from musical rhythm may be a result of such mechanisms.
Xiaoli Liu
2018-01-01
Full Text Available Alzheimer’s disease (AD has been not only the substantial financial burden to the health care system but also the emotional burden to patients and their families. Predicting cognitive performance of subjects from their magnetic resonance imaging (MRI measures and identifying relevant imaging biomarkers are important research topics in the study of Alzheimer’s disease. Recently, the multitask learning (MTL methods with sparsity-inducing norm (e.g., l2,1-norm have been widely studied to select the discriminative feature subset from MRI features by incorporating inherent correlations among multiple clinical cognitive measures. However, these previous works formulate the prediction tasks as a linear regression problem. The major limitation is that they assumed a linear relationship between the MRI features and the cognitive outcomes. Some multikernel-based MTL methods have been proposed and shown better generalization ability due to the nonlinear advantage. We quantify the power of existing linear and nonlinear MTL methods by evaluating their performance on cognitive score prediction of Alzheimer’s disease. Moreover, we extend the traditional l2,1-norm to a more general lql1-norm (q≥1. Experiments on the Alzheimer’s Disease Neuroimaging Initiative database showed that the nonlinear l2,1lq-MKMTL method not only achieved better prediction performance than the state-of-the-art competitive methods but also effectively fused the multimodality data.
Ernst, Floris; Schweikard, Achim
2008-01-01
Forecasting of respiration motion in image-guided radiotherapy requires algorithms that can accurately and efficiently predict target location. Improved methods for respiratory motion forecasting were developed and tested. MULIN, a new family of prediction algorithms based on linear expansions of the prediction error, was developed and tested. Computer-generated data with a prediction horizon of 150 ms was used for testing in simulation experiments. MULIN was compared to Least Mean Squares-based predictors (LMS; normalized LMS, nLMS; wavelet-based multiscale autoregression, wLMS) and a multi-frequency Extended Kalman Filter (EKF) approach. The in vivo performance of the algorithms was tested on data sets of patients who underwent radiotherapy. The new MULIN methods are highly competitive, outperforming the LMS and the EKF prediction algorithms in real-world settings and performing similarly to optimized nLMS and wLMS prediction algorithms. On simulated, periodic data the MULIN algorithms are outperformed only by the EKF approach due to its inherent advantage in predicting periodic signals. In the presence of noise, the MULIN methods significantly outperform all other algorithms. The MULIN family of algorithms is a feasible tool for the prediction of respiratory motion, performing as well as or better than conventional algorithms while requiring significantly lower computational complexity. The MULIN algorithms are of special importance wherever high-speed prediction is required. (orig.)
Ernst, Floris; Schweikard, Achim [University of Luebeck, Institute for Robotics and Cognitive Systems, Luebeck (Germany)
2008-06-15
Forecasting of respiration motion in image-guided radiotherapy requires algorithms that can accurately and efficiently predict target location. Improved methods for respiratory motion forecasting were developed and tested. MULIN, a new family of prediction algorithms based on linear expansions of the prediction error, was developed and tested. Computer-generated data with a prediction horizon of 150 ms was used for testing in simulation experiments. MULIN was compared to Least Mean Squares-based predictors (LMS; normalized LMS, nLMS; wavelet-based multiscale autoregression, wLMS) and a multi-frequency Extended Kalman Filter (EKF) approach. The in vivo performance of the algorithms was tested on data sets of patients who underwent radiotherapy. The new MULIN methods are highly competitive, outperforming the LMS and the EKF prediction algorithms in real-world settings and performing similarly to optimized nLMS and wLMS prediction algorithms. On simulated, periodic data the MULIN algorithms are outperformed only by the EKF approach due to its inherent advantage in predicting periodic signals. In the presence of noise, the MULIN methods significantly outperform all other algorithms. The MULIN family of algorithms is a feasible tool for the prediction of respiratory motion, performing as well as or better than conventional algorithms while requiring significantly lower computational complexity. The MULIN algorithms are of special importance wherever high-speed prediction is required. (orig.)
Petitgrand, S.
1980-01-01
A large number of fuel rods have been irradiated in the small power plant BR3. Many of them have been examined in hot cells after irradiation, giving thus valuable experimental information. On the other hand a thermomechanical code, named RESTA, has been developed by the C.E.A. to describe and predict the behaviour of a fuel pin in a PWR environment and in stationary conditions. The models used in that code derive chiefly from the C.E.A.'s own experience and are briefly reviewed in this paper. The comparison between prediction and experience has been performed for four power history classes: (1) moderate (average linear rating approximately equal to 20 kw m -1 ) and short (approximately equal to 300 days) rating, (2) moderate (approximately equal to 20 kw m -1 ) and long (approximately equal to 600 days) rating, (3) high (25-30 kw m -1 ) and long (approximately equal to 600 days) rating and (4) very high (30-40 kw m -1 ) and long (approximately equal to 600 days) rating. Satisfactory agreement has been found between experimental and calculated results in all cases, concerning fuel structural change, fission gas release, pellet-clad interaction as well as clad permanent strain. (author)
A Chip-Level BSOR-Based Linear GSIC Multiuser Detector for Long-Code CDMA Systems
M. Benyoucef
2008-01-01
Full Text Available We introduce a chip-level linear group-wise successive interference cancellation (GSIC multiuser structure that is asymptotically equivalent to block successive over-relaxation (BSOR iteration, which is known to outperform the conventional block Gauss-Seidel iteration by an order of magnitude in terms of convergence speed. The main advantage of the proposed scheme is that it uses directly the spreading codes instead of the cross-correlation matrix and thus does not require the calculation of the cross-correlation matrix (requires 2NK2 floating point operations (flops, where N is the processing gain and K is the number of users which reduces significantly the overall computational complexity. Thus it is suitable for long-code CDMA systems such as IS-95 and UMTS where the cross-correlation matrix is changing every symbol. We study the convergence behavior of the proposed scheme using two approaches and prove that it converges to the decorrelator detector if the over-relaxation factor is in the interval ]0, 2[. Simulation results are in excellent agreement with theory.
A Chip-Level BSOR-Based Linear GSIC Multiuser Detector for Long-Code CDMA Systems
Benyoucef M
2007-01-01
Full Text Available We introduce a chip-level linear group-wise successive interference cancellation (GSIC multiuser structure that is asymptotically equivalent to block successive over-relaxation (BSOR iteration, which is known to outperform the conventional block Gauss-Seidel iteration by an order of magnitude in terms of convergence speed. The main advantage of the proposed scheme is that it uses directly the spreading codes instead of the cross-correlation matrix and thus does not require the calculation of the cross-correlation matrix (requires floating point operations (flops, where is the processing gain and is the number of users which reduces significantly the overall computational complexity. Thus it is suitable for long-code CDMA systems such as IS-95 and UMTS where the cross-correlation matrix is changing every symbol. We study the convergence behavior of the proposed scheme using two approaches and prove that it converges to the decorrelator detector if the over-relaxation factor is in the interval ]0, 2[. Simulation results are in excellent agreement with theory.
Vadlamani, Srinath; Kruger, Scott; Austin, Travis
2008-01-01
Extended magnetohydrodynamic (MHD) codes are used to model the large, slow-growing instabilities that are projected to limit the performance of International Thermonuclear Experimental Reactor (ITER). The multiscale nature of the extended MHD equations requires an implicit approach. The current linear solvers needed for the implicit algorithm scale poorly because the resultant matrices are so ill-conditioned. A new solver is needed, especially one that scales to the petascale. The most successful scalable parallel processor solvers to date are multigrid solvers. Applying multigrid techniques to a set of equations whose fundamental modes are dispersive waves is a promising solution to CEMM problems. For the Phase 1, we implemented multigrid preconditioners from the HYPRE project of the Center for Applied Scientific Computing at LLNL via PETSc of the DOE SciDAC TOPS for the real matrix systems of the extended MHD code NIMROD which is a one of the primary modeling codes of the OFES-funded Center for Extended Magnetohydrodynamic Modeling (CEMM) SciDAC. We implemented the multigrid solvers on the fusion test problem that allows for real matrix systems with success, and in the process learned about the details of NIMROD data structures and the difficulties of inverting NIMROD operators. The further success of this project will allow for efficient usage of future petascale computers at the National Leadership Facilities: Oak Ridge National Laboratory, Argonne National Laboratory, and National Energy Research Scientific Computing Center. The project will be a collaborative effort between computational plasma physicists and applied mathematicians at Tech-X Corporation, applied mathematicians Front Range Scientific Computations, Inc. (who are collaborators on the HYPRE project), and other computational plasma physicists involved with the CEMM project.
Malatara, G; Kappas, K [Medical Physics Department, Faculty of Medicine, University of Patras, 265 00 Patras (Greece); Sphiris, N [Ethnodata S.A., Athens (Greece)
1994-12-31
In this work, a Monte Carlo EGS4 code was used to simulate radiation transport through linear accelerators to produce and score energy spectra and angular distributions of 6, 12, 15 and 25 MeV bremsstrahlung photons exiting from different accelerator treatment heads. The energy spectra was used as input for a convolution method program to calculate the tissue-maximum ratio in water. 100.000 histories are recorded in the scoring plane for each simulation. The validity of the Monte Carlo simulation and the precision to the calculated spectra have been verified experimentally and were in good agreement. We believe that the accurate simulation of the different components of the linear accelerator head is very important for the precision of the results. The results of the Monte Carlo and the Convolution Method can be compared with experimental data for verification and they are powerful and practical tools to generate accurate spectra and dosimetric data. (authors). 10 refs,5 figs, 2 tabs.
Sokoler, Leo Emil; Standardi, Laura; Edlund, Kristian
2014-01-01
This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input...... limits, input rate limits, and soft output limits. The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm...... is significantly faster than both state-of-the-art linear programming solvers, and a structure exploiting implementation of the alternating direction method of multipliers. It is also demonstrated that the control strategy presented in this paper can be tuned using a weighted ℓ1-regularization term...
Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network.
Gilra, Aditya; Gerstner, Wulfram
2017-11-27
The brain needs to predict how the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dynamics using local, online and stable learning rules is unclear. Here, we present a supervised learning scheme for the feedforward and recurrent connections in a network of heterogeneous spiking neurons. The error in the output is fed back through fixed random connections with a negative gain, causing the network to follow the desired dynamics. The rule for Feedback-based Online Local Learning Of Weights (FOLLOW) is local in the sense that weight changes depend on the presynaptic activity and the error signal projected onto the postsynaptic neuron. We provide examples of learning linear, non-linear and chaotic dynamics, as well as the dynamics of a two-link arm. Under reasonable approximations, we show, using the Lyapunov method, that FOLLOW learning is uniformly stable, with the error going to zero asymptotically.
Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine
Santoso, Noviyanti; Wibowo, Wahyu
2018-03-01
A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.
Prediction of Complex Human Traits Using the Genomic Best Linear Unbiased Predictor
de los Campos, Gustavo; Vazquez, Ana I; Fernando, Rohan
2013-01-01
Despite important advances from Genome Wide Association Studies (GWAS), for most complex human traits and diseases, a sizable proportion of genetic variance remains unexplained and prediction accuracy (PA) is usually low. Evidence suggests that PA can be improved using Whole-Genome Regression (WGR......) models where phenotypes are regressed on hundreds of thousands of variants simultaneously. The Genomic Best Linear Unbiased Prediction G-BLUP, a ridge-regression type method) is a commonly used WGR method and has shown good predictive performance when applied to plant and animal breeding populations....... However, breeding and human populations differ greatly in a number of factors that can affect the predictive performance of G-BLUP. Using theory, simulations, and real data analysis, we study the erformance of G-BLUP when applied to data from related and unrelated human subjects. Under perfect linkage...
Avval Zhila Mohajeri
2015-01-01
Full Text Available This paper deals with developing a linear quantitative structure-activity relationship (QSAR model for predicting the RSK inhibition activity of some new compounds. A dataset consisting of 62 pyrazino [1,2-α] indole, diazepino [1,2-α] indole, and imidazole derivatives with known inhibitory activities was used. Multiple linear regressions (MLR technique combined with the stepwise (SW and the genetic algorithm (GA methods as variable selection tools was employed. For more checking stability, robustness and predictability of the proposed models, internal and external validation techniques were used. Comparison of the results obtained, indicate that the GA-MLR model is superior to the SW-MLR model and that it isapplicable for designing novel RSK inhibitors.
The application of sparse linear prediction dictionary to compressive sensing in speech signals
YOU Hanxu
2016-04-01
Full Text Available Appling compressive sensing (CS,which theoretically guarantees that signal sampling and signal compression can be achieved simultaneously,into audio and speech signal processing is one of the most popular research topics in recent years.In this paper,K-SVD algorithm was employed to learn a sparse linear prediction dictionary regarding as the sparse basis of underlying speech signals.Compressed signals was obtained by applying random Gaussian matrix to sample original speech frames.Orthogonal matching pursuit (OMP and compressive sampling matching pursuit (CoSaMP were adopted to recovery original signals from compressed one.Numbers of experiments were carried out to investigate the impact of speech frames length,compression ratios,sparse basis and reconstruction algorithms on CS performance.Results show that sparse linear prediction dictionary can advance the performance of speech signals reconstruction compared with discrete cosine transform (DCT matrix.
Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik
2015-01-01
In this paper, we compare the performance of an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) to a linear tracking Model Predictive Controller (MPC) for a spray drying plant. We find in this simulation study, that the economic performance of the two controllers are almost...... equal. We evaluate the economic performance with an industrially recorded disturbance scenario, where unmeasured disturbances and model mismatch are present. The state of the spray dryer, used in the E-NMPC and MPC, is estimated using Kalman Filters with noise covariances estimated by a maximum...
Tewarie, P.; Bright, M.G.; Hillebrand, A.; Robson, S.E.; Gascoyne, L.E.; Morris, P.G.; Meier, J.; Van Mieghem, P.; Brookes, M.J.
2016-01-01
Understanding the electrophysiological basis of resting state networks (RSNs) in the human brain is a critical step towards elucidating how inter-areal connectivity supports healthy brain function. In recent years, the relationship between RSNs (typically measured using haemodynamic signals) and electrophysiology has been explored using functional Magnetic Resonance Imaging (fMRI) and magnetoencephalography (MEG). Significant progress has been made, with similar spatial structure observable in both modalities. However, there is a pressing need to understand this relationship beyond simple visual similarity of RSN patterns. Here, we introduce a mathematical model to predict fMRI-based RSNs using MEG. Our unique model, based upon a multivariate Taylor series, incorporates both phase and amplitude based MEG connectivity metrics, as well as linear and non-linear interactions within and between neural oscillations measured in multiple frequency bands. We show that including non-linear interactions, multiple frequency bands and cross-frequency terms significantly improves fMRI network prediction. This shows that fMRI connectivity is not only the result of direct electrophysiological connections, but is also driven by the overlap of connectivity profiles between separate regions. Our results indicate that a complete understanding of the electrophysiological basis of RSNs goes beyond simple frequency-specific analysis, and further exploration of non-linear and cross-frequency interactions will shed new light on distributed network connectivity, and its perturbation in pathology. PMID:26827811
Ling, Ru; Liu, Jiawang
2011-12-01
To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.
MULTIPLE LINEAR REGRESSION ANALYSIS FOR PREDICTION OF BOILER LOSSES AND BOILER EFFICIENCY
Chayalakshmi C.L
2018-01-01
MULTIPLE LINEAR REGRESSION ANALYSIS FOR PREDICTION OF BOILER LOSSES AND BOILER EFFICIENCY ABSTRACT Calculation of boiler efficiency is essential if its parameters need to be controlled for either maintaining or enhancing its efficiency. But determination of boiler efficiency using conventional method is time consuming and very expensive. Hence, it is not recommended to find boiler efficiency frequently. The work presented in this paper deals with establishing the statistical mo...
Integrating piecewise linear representation and ensemble neural network for stock price prediction
Asaduzzaman, Md.; Shahjahan, Md.; Ahmed, Fatema Johera; Islam, Md. Monirul; Murase, Kazuyuki
2014-01-01
Stock Prices are considered to be very dynamic and susceptible to quick changes because of the underlying nature of the financial domain, and in part because of the interchange between known parameters and unknown factors. Of late, several researchers have used Piecewise Linear Representation (PLR) to predict the stock market pricing. However, some improvements are needed to avoid the appropriate threshold of the trading decision, choosing the input index as well as improving the overall perf...
Validation of the ORIGEN-S code for predicting radionuclide inventories in used CANDU Fuel
Tait, J.C.; Gauld, I.; Kerr, A.H.
1994-10-01
The safety assessment being conducted by AECL Research for the concept of deep geological disposal of used CANDU UO 2 fuel requires the calculation of radionuclide inventories in the fuel to provide source terms for radionuclide release. This report discusses the validation of selected actinide and fission-product inventories calculated using the ORIGEN-S code coupled with the WIMS-AECL lattice code, using data from analytical measurements of radioisotope inventories in Pickering CANDU reactor fuel. The recent processing of new ENDF/B-VI cross-section data has allowed the ORIGEN-S calculations to be performed using the most up-to-date nuclear data available. The results indicate that the code is reliably predicting actinide and the majority of fission-product inventories to within the analytical uncertainty. 38 refs., 4 figs., 5 tabs
Modification V to the computer code, STRETCH, for predicting coated-particle behavior
Valentine, K.H.
1975-04-01
Several modifications have been made to the stress analysis code, STRETCH, in an attempt to improve agreement between the calculated and observed behavior of pyrocarbon-coated fuel particles during irradiation in a reactor environment. Specific areas of the code that have been modified are the neutron-induced densification model and the neutron-induced creep calculation. Also, the capability for modeling surface temperature variations has been added. HFIR Target experiments HT-12 through HT-15 have been simulated with the modified code, and the neutron-fluence vs particle-failure predictions compare favorably with the experimental results. Listings of the modified FORTRAN IV main source program and additional FORTRAN IV functions are provided along with instructions for supplying the additional input data. (U.S.)
Validation of the ORIGEN-S code for predicting radionuclide inventories in used CANDU fuel
Tait, J.C.; Gauld, I.; Kerr, A.H.
1995-01-01
The safety assessment being conducted by AECL Research for the concept of deep geological disposal of used CANDU UO 2 fuel requires the calculation of radionuclide inventories in the fuel to provide source terms for radionuclide release. This report discusses the validation of selected actinide and fission-product inventories calculated using the ORIGEN-S code coupled with the WIMS-AECL lattice code, using data from analytical measurements of radioisotope inventories in Pickering CANDU reactor fuel. The recent processing of new ENDF/B-VI cross-section data has allowed the ORIGEN-S calculations to be performed using the most up-to-date nuclear data available. The results indicate that the code is reliably predicting actinide and the majority of fission-product inventories to within the analytical uncertainty. ((orig.))
Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.
Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W
2014-11-26
Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.
Use of a commercial heat transfer code to predict horizontally oriented spent fuel rod temperatures
Wix, S.D.; Koski, J.A.
1992-01-01
Radioactive spent fuel assemblies are a source of hazardous waste that will have to be dealt with in the near future. It is anticipated that the spent fuel assemblies will be transported to disposal sites in spent fuel transportation casks. In order to design a reliable and safe transportation cask, the maximum cladding temperature of the spent fuel rod arrays must be calculated. The maximum rod temperature is a limiting factor in the amount of spent fuel that can be loaded in a transportation cask. The scope of this work is to demonstrate that reasonable and conservative spent fuel rod temperature predictions can be made using commercially available thermal analysis codes. The demonstration is accomplished by a comparison between numerical temperature predictions, with a commercially available thermal analysis code, and experimental temperature data for electrical rod heaters simulating a horizontally oriented spent fuel rod bundle
Experiment predictions of LOFT reflood behavior using the RELAP4/MOD6 code
Lin, J.C.; Kee, E.J.; Grush, W.H.; White, J.R.
1978-01-01
The RELAP4/MOD6 computer code was used to predict the thermal-hydraulic transient for Loss-of-Fluid Test (LOFT) Loss-of-Coolant Accident (LOCA) experiments L2-2, L2-3, and L2-4. This analysis will aid in the development and assessment of analytical models used to analyze the LOCA performance of commercial power reactors. Prior to performing experiments in the LOFT facility, the experiments are modeled in counterpart tests performed in the nonnuclear Semiscale MOD 1 facility. A comparison of the analytical results with Semiscale data will verify the analytical capability of the RELAP4 code to predict the thermal-hydraulic behavior of the Semiscale LOFT counterpart tests. The analytical model and the results of analyses for the reflood portion of the LOFT LOCA experiments are described. These results are compared with the data from Semiscale
A Cerebellar Framework for Predictive Coding and Homeostatic Regulation in Depressive Disorder.
Schutter, Dennis J L G
2016-02-01
Depressive disorder is associated with abnormalities in the processing of reward and punishment signals and disturbances in homeostatic regulation. These abnormalities are proposed to impair error minimization routines for reducing uncertainty. Several lines of research point towards a role of the cerebellum in reward- and punishment-related predictive coding and homeostatic regulatory function in depressive disorder. Available functional and anatomical evidence suggests that in addition to the cortico-limbic networks, the cerebellum is part of the dysfunctional brain circuit in depressive disorder as well. It is proposed that impaired cerebellar function contributes to abnormalities in predictive coding and homeostatic dysregulation in depressive disorder. Further research on the role of the cerebellum in depressive disorder may further extend our knowledge on the functional and neural mechanisms of depressive disorder and development of novel antidepressant treatments strategies targeting the cerebellum.
Quantifying the predictive consequences of model error with linear subspace analysis
White, Jeremy T.; Doherty, John E.; Hughes, Joseph D.
2014-01-01
All computer models are simplified and imperfect simulators of complex natural systems. The discrepancy arising from simplification induces bias in model predictions, which may be amplified by the process of model calibration. This paper presents a new method to identify and quantify the predictive consequences of calibrating a simplified computer model. The method is based on linear theory, and it scales efficiently to the large numbers of parameters and observations characteristic of groundwater and petroleum reservoir models. The method is applied to a range of predictions made with a synthetic integrated surface-water/groundwater model with thousands of parameters. Several different observation processing strategies and parameterization/regularization approaches are examined in detail, including use of the Karhunen-Loève parameter transformation. Predictive bias arising from model error is shown to be prediction specific and often invisible to the modeler. The amount of calibration-induced bias is influenced by several factors, including how expert knowledge is applied in the design of parameterization schemes, the number of parameters adjusted during calibration, how observations and model-generated counterparts are processed, and the level of fit with observations achieved through calibration. Failure to properly implement any of these factors in a prediction-specific manner may increase the potential for predictive bias in ways that are not visible to the calibration and uncertainty analysis process.
Tayal, M.
1987-08-15
Arrays of tubes are used in many engineered structures, such as in nuclear fuel bundles and in steam generators. The tubes can bend (bow) due to in-service temperatures and loads. Assessments of bowing of nuclear fuel elements can help demonstrate the integrity of fuel and of surrounding components, as a function of operating conditions such as channel power. The BOW code calculates the bending of composite beams such as fuel elements, due to gradients of temperature and due to hydraulic forces. The deflections and rotations are calculated in both lateral directions, for given conditions of temperatures. Wet and dry operation of the sheath can be simulated. Bow accounts for the following physical phenomena: circumferential and axial variations in the temperatures of the sheath and of the pellet; cracking of pellets; grip and slip between the pellets and the sheath; hydraulic drag; restraints from endplates, from neighbouring elements, and from the pressure-tube; gravity; concentric or eccentric welds between endcap and endplate; neutron flux gradients; and variations of material properties with temperature. The code is based on fundamental principles of mechanics. The governing equations are solved numerically using the finite element method. Several comparisons with closed-form equations show that the solutions of BOW are accurate. BOW`s predictions for initial in-reactor bow are also consistent with two post-irradiation measurements.
Prediction of detonation and JWL eos parameters of energetic materials using EXPLO5 computer code
Peter, Xolani
2016-09-01
Full Text Available Ballistic Organization Cape Town, South Africa 27-29 September 2016 1 PREDICTION OF DETONATION AND JWL EOS PARAMETERS OF ENERGETIC MATERIALS USING EXPLO5 COMPUTER CODE X. Peter*, Z. Jiba, M. Olivier, I.M. Snyman, F.J. Mostert and T.J. Sono.... Nowadays many numerical methods and programs are being used for carrying out thermodynamic calculations of the detonation parameters of condensed explosives, for example a BKW Fortran (Mader, 1967), Ruby (Cowperthwaite and Zwisler, 1974) TIGER...
Linear filters as a method of real-time prediction of geomagnetic activity
McPherron, R.L.; Baker, D.N.; Bargatze, L.F.
1985-01-01
Important factors controlling geomagnetic activity include the solar wind velocity, the strength of the interplanetary magnetic field (IMF), and the field orientation. Because these quantities change so much in transit through the solar wind, real-time monitoring immediately upstream of the earth provides the best input for any technique of real-time prediction. One such technique is linear prediction filtering which utilizes past histories of the input and output of a linear system to create a time-invariant filter characterizing the system. Problems of nonlinearity or temporal changes of the system can be handled by appropriate choice of input parameters and piecewise approximation in various ranges of the input. We have created prediction filters for all the standard magnetic indices and tested their efficiency. The filters show that the initial response of the magnetosphere to a southward turning of the IMF peaks in 20 minutes and then again in 55 minutes. After a northward turning, auroral zone indices and the midlatitude ASYM index return to background within 2 hours, while Dst decays exponentially with a time constant of about 8 hours. This paper describes a simple, real-time system utilizing these filters which could predict a substantial fraction of the variation in magnetic activity indices 20 to 50 minutes in advance
Prediction of the HBS width and Xe concentration in grain matrix by the INFRA code
Yang, Yong Sik; Lee, Chan Bok; Kim, Dae Ho; Kim, Young Min
2004-01-01
Formation of a HBS(High Burnup Structure) is an important phenomenon for the high burnup fuel performance and safety. For the prediction of the HBS(so called 'rim microstructure') proposed rim microstructure formation model, which is a function of the fuel temperature, grain size and fission rate, was inserted into the high burnup fuel performance code INFRA. During the past decades, various examinations have been performed to find the HBS formation mechanism and define HBS characteristics. In the HBEP(High Burnup Effects Program), several rods were examined by EPMA analysis to measure HBS width and these results were re-measured by improved technology including XRF and detail microstructure examination. Recently, very high burnup(∼100MWd/kgU) fuel examination results were reported by Manzel et al., and EPMA analysis results have been released. Using the measured EPMA analysis data, HBS formation prediction model of INFRA code are verified. HBS width prediction results are compared with measured ones and Xe concentration profile is compared with measured EPMA data. Calculated HBS width shows good agreement with measured data in a reasonable error range. Though, there are some difference in transition region and central region due to model limitation and fission gas release prediction error respectively, however, predicted Xe concentration in the fully developed HBS region shows a good agreement with the measured data. (Author)
IAMBUS, a computer code for the design and performance prediction of fast breeder fuel rods
Toebbe, H.
1990-05-01
IAMBUS is a computer code for the thermal and mechanical design, in-pile performance prediction and post-irradiation analysis of fast breeder fuel rods. The code deals with steady, non-steady and transient operating conditions and enables to predict in-pile behavior of fuel rods in power reactors as well as in experimental rigs. Great effort went into the development of a realistic account of non-steady fuel rod operating conditions. The main emphasis is placed on characterizing the mechanical interaction taking place between the cladding tube and the fuel as a result of contact pressure and friction forces, with due consideration of axial and radial crack configuration within the fuel as well as the gradual transition at the elastic/plastic interface in respect to fuel behavior. IAMBUS can be readily adapted to various fuel and cladding materials. The specific models and material correlations of the reference version deal with the actual in-pile behavior and physical properties of the KNK II and SNR 300 related fuel rod design, confirmed by comparison of the fuel performance model with post-irradiation data. The comparison comprises steady, non-steady and transient irradiation experiments within the German/Belgian fuel rod irradiation program. The code is further validated by comparison of model predictions with post-irradiation data of standard fuel and breeder rods of Phenix and PFR as well as selected LWR fuel rods in non-steady operating conditions
Information-Theoretic Evidence for Predictive Coding in the Face-Processing System.
Brodski-Guerniero, Alla; Paasch, Georg-Friedrich; Wollstadt, Patricia; Özdemir, Ipek; Lizier, Joseph T; Wibral, Michael
2017-08-23
Predictive coding suggests that the brain infers the causes of its sensations by combining sensory evidence with internal predictions based on available prior knowledge. However, the neurophysiological correlates of (pre)activated prior knowledge serving these predictions are still unknown. Based on the idea that such preactivated prior knowledge must be maintained until needed, we measured the amount of maintained information in neural signals via the active information storage (AIS) measure. AIS was calculated on whole-brain beamformer-reconstructed source time courses from MEG recordings of 52 human subjects during the baseline of a Mooney face/house detection task. Preactivation of prior knowledge for faces showed as α-band-related and β-band-related AIS increases in content-specific areas; these AIS increases were behaviorally relevant in the brain's fusiform face area. Further, AIS allowed decoding of the cued category on a trial-by-trial basis. Our results support accounts indicating that activated prior knowledge and the corresponding predictions are signaled in low-frequency activity (information our eyes/retina and other sensory organs receive from the outside world, but strongly depends also on information already present in our brains, such as prior knowledge about specific situations or objects. A currently popular theory in neuroscience, predictive coding theory, suggests that this prior knowledge is used by the brain to form internal predictions about upcoming sensory information. However, neurophysiological evidence for this hypothesis is rare, mostly because this kind of evidence requires strong a priori assumptions about the specific predictions the brain makes and the brain areas involved. Using a novel, assumption-free approach, we find that face-related prior knowledge and the derived predictions are represented in low-frequency brain activity. Copyright © 2017 the authors 0270-6474/17/378273-11$15.00/0.
Linear Model-Based Predictive Control of the LHC 1.8 K Cryogenic Loop
Blanco-Viñuela, E; De Prada-Moraga, C
1999-01-01
The LHC accelerator will employ 1800 superconducting magnets (for guidance and focusing of the particle beams) in a pressurized superfluid helium bath at 1.9 K. This temperature is a severely constrained control parameter in order to avoid the transition from the superconducting to the normal state. Cryogenic processes are difficult to regulate due to their highly non-linear physical parameters (heat capacity, thermal conductance, etc.) and undesirable peculiarities like non self-regulating process, inverse response and variable dead time. To reduce the requirements on either temperature sensor or cryogenic system performance, various control strategies have been investigated on a reduced-scale LHC prototype built at CERN (String Test). Model Based Predictive Control (MBPC) is a regulation algorithm based on the explicit use of a process model to forecast the plant output over a certain prediction horizon. This predicted controlled variable is used in an on-line optimization procedure that minimizes an approp...
Mariana Santos Matos Cavalca
2012-01-01
Full Text Available One of the main advantages of predictive control approaches is the capability of dealing explicitly with constraints on the manipulated and output variables. However, if the predictive control formulation does not consider model uncertainties, then the constraint satisfaction may be compromised. A solution for this inconvenience is to use robust model predictive control (RMPC strategies based on linear matrix inequalities (LMIs. However, LMI-based RMPC formulations typically consider only symmetric constraints. This paper proposes a method based on pseudoreferences to treat asymmetric output constraints in integrating SISO systems. Such technique guarantees robust constraint satisfaction and convergence of the state to the desired equilibrium point. A case study using numerical simulation indicates that satisfactory results can be achieved.
Assessment of Prediction Capabilities of COCOSYS and CFX Code for Simplified Containment
Jia Zhu
2016-01-01
Full Text Available The acceptable accuracy for simulation of severe accident scenarios in containments of nuclear power plants is required to investigate the consequences of severe accidents and effectiveness of potential counter measures. For this purpose, the actual capability of CFX tool and COCOSYS code is assessed in prototypical geometries for simplified physical process-plume (due to a heat source under adiabatic and convection boundary condition, respectively. Results of the comparison under adiabatic boundary condition show that good agreement is obtained among the analytical solution, COCOSYS prediction, and CFX prediction for zone temperature. The general trend of the temperature distribution along the vertical direction predicted by COCOSYS agrees with the CFX prediction except in dome, and this phenomenon is predicted well by CFX and failed to be reproduced by COCOSYS. Both COCOSYS and CFX indicate that there is no temperature stratification inside dome. CFX prediction shows that temperature stratification area occurs beneath the dome and away from the heat source. Temperature stratification area under adiabatic boundary condition is bigger than that under convection boundary condition. The results indicate that the average temperature inside containment predicted with COCOSYS model is overestimated under adiabatic boundary condition, while it is underestimated under convection boundary condition compared to CFX prediction.
Madarang, Krish J; Kang, Joo-Hyon
2014-06-01
Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days (ADD), have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency's Storm Water Management Model (SWMM). The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid (TSS) discharge loads and event mean concentrations (EMC) were extracted. From these data, linear regression models were developed. R(2) and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data. Copyright © 2014 The Research Centre for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.
Luiz Augusto da Cruz Meleiro
2005-06-01
Full Text Available In this work a MIMO non-linear predictive controller was developed for an extractive alcoholic fermentation process. The internal model of the controller was represented by two MISO Functional Link Networks (FLNs, identified using simulated data generated from a deterministic mathematical model whose kinetic parameters were determined experimentally. The FLN structure presents as advantages fast training and guaranteed convergence, since the estimation of the weights is a linear optimization problem. Besides, the elimination of non-significant weights generates parsimonious models, which allows for fast execution in an MPC-based algorithm. The proposed algorithm showed good potential in identification and control of non-linear processes.Neste trabalho um controlador preditivo não linear multivariável foi desenvolvido para um processo de fermentação alcoólica extrativa. O modelo interno do controlador foi representado por duas redes do tipo Functional Link (FLN, identificadas usando dados de simulação gerados a partir de um modelo validado experimentalmente. A estrutura FLN apresenta como vantagem o treinamento rápido e convergência garantida, já que a estimação dos seus pesos é um problema de otimização linear. Além disso, a eliminação de pesos não significativos gera modelos parsimoniosos, o que permite a rápida execução em algoritmos de controle preditivo baseado em modelo. Os resultados mostram que o algoritmo proposto tem grande potencial para identificação e controle de processos não lineares.
Magnified Neural Envelope Coding Predicts Deficits in Speech Perception in Noise.
Millman, Rebecca E; Mattys, Sven L; Gouws, André D; Prendergast, Garreth
2017-08-09
Verbal communication in noisy backgrounds is challenging. Understanding speech in background noise that fluctuates in intensity over time is particularly difficult for hearing-impaired listeners with a sensorineural hearing loss (SNHL). The reduction in fast-acting cochlear compression associated with SNHL exaggerates the perceived fluctuations in intensity in amplitude-modulated sounds. SNHL-induced changes in the coding of amplitude-modulated sounds may have a detrimental effect on the ability of SNHL listeners to understand speech in the presence of modulated background noise. To date, direct evidence for a link between magnified envelope coding and deficits in speech identification in modulated noise has been absent. Here, magnetoencephalography was used to quantify the effects of SNHL on phase locking to the temporal envelope of modulated noise (envelope coding) in human auditory cortex. Our results show that SNHL enhances the amplitude of envelope coding in posteromedial auditory cortex, whereas it enhances the fidelity of envelope coding in posteromedial and posterolateral auditory cortex. This dissociation was more evident in the right hemisphere, demonstrating functional lateralization in enhanced envelope coding in SNHL listeners. However, enhanced envelope coding was not perceptually beneficial. Our results also show that both hearing thresholds and, to a lesser extent, magnified cortical envelope coding in left posteromedial auditory cortex predict speech identification in modulated background noise. We propose a framework in which magnified envelope coding in posteromedial auditory cortex disrupts the segregation of speech from background noise, leading to deficits in speech perception in modulated background noise. SIGNIFICANCE STATEMENT People with hearing loss struggle to follow conversations in noisy environments. Background noise that fluctuates in intensity over time poses a particular challenge. Using magnetoencephalography, we demonstrate
Goriely, S.; Hilaire, S.; Koning, A.J.
2008-01-01
Nuclear reaction rates for astrophysics applications are traditionally determined on the basis of Hauser-Feshbach reaction codes, like MOST. These codes use simplified schemes to calculate the capture reaction cross section on a given target nucleus, not only in its ground state but also on the different thermally populated states of the stellar plasma at a given temperature. Such schemes include a number of approximations that have never been tested, such as an approximate width fluctuation correction, the neglect of delayed particle emission during the electromagnetic decay cascade or the absence of the pre-equilibrium contribution at increasing incident energies. New developments have been brought to the reaction code TALYS to estimate the Maxwellian-averaged reaction rates of astrophysics relevance. These new developments give us the possibility to calculate with an improved accuracy the reaction cross sections and the corresponding astrophysics rates. The TALYS predictions for the thermonuclear rates of astrophysics relevance are presented and compared with those obtained with the MOST code on the basis of the same nuclear ingredients for nuclear structure properties, optical model potential, nuclear level densities and γ-ray strength. It is shown that, in particular, the pre-equilibrium process significantly influences the astrophysics rates of exotic neutron-rich nuclei. The reciprocity theorem traditionally used in astrophysics to determine photo-rates is also shown no to be valid for exotic nuclei. The predictions obtained with different nuclear inputs are also analyzed to provide an estimate of the theoretical uncertainties still affecting the reaction rate prediction far away from the experimentally known regions. (authors)
Lee, Eunjee; Zhu, Hongtu; Kong, Dehan; Wang, Yalin; Giovanello, Kelly Sullivan; Ibrahim, Joseph G
2015-12-01
The aim of this paper is to develop a Bayesian functional linear Cox regression model (BFLCRM) with both functional and scalar covariates. This new development is motivated by establishing the likelihood of conversion to Alzheimer's disease (AD) in 346 patients with mild cognitive impairment (MCI) enrolled in the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI-1) and the early markers of conversion. These 346 MCI patients were followed over 48 months, with 161 MCI participants progressing to AD at 48 months. The functional linear Cox regression model was used to establish that functional covariates including hippocampus surface morphology and scalar covariates including brain MRI volumes, cognitive performance (ADAS-Cog), and APOE status can accurately predict time to onset of AD. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFLCRM.
Zhang, Langwen; Xie, Wei; Wang, Jingcheng
2017-11-01
In this work, synthesis of robust distributed model predictive control (MPC) is presented for a class of linear systems subject to structured time-varying uncertainties. By decomposing a global system into smaller dimensional subsystems, a set of distributed MPC controllers, instead of a centralised controller, are designed. To ensure the robust stability of the closed-loop system with respect to model uncertainties, distributed state feedback laws are obtained by solving a min-max optimisation problem. The design of robust distributed MPC is then transformed into solving a minimisation optimisation problem with linear matrix inequality constraints. An iterative online algorithm with adjustable maximum iteration is proposed to coordinate the distributed controllers to achieve a global performance. The simulation results show the effectiveness of the proposed robust distributed MPC algorithm.
Predictive IP controller for robust position control of linear servo system.
Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi
2016-07-01
Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Sun, Lei; Jin, Hong-Yu; Tian, Run-Tao; Wang, Ming-Juan; Liu, Li-Na; Ye, Liu-Ping; Zuo, Tian-Tian; Ma, Shuang-Cheng
2017-01-01
Analysis of related substances in pharmaceutical chemicals and multi-components in traditional Chinese medicines needs bulk of reference substances to identify the chromatographic peaks accurately. But the reference substances are costly. Thus, the relative retention (RR) method has been widely adopted in pharmacopoeias and literatures for characterizing HPLC behaviors of those reference substances unavailable. The problem is it is difficult to reproduce the RR on different columns due to the error between measured retention time (t R ) and predicted t R in some cases. Therefore, it is useful to develop an alternative and simple method for prediction of t R accurately. In the present study, based on the thermodynamic theory of HPLC, a method named linear calibration using two reference substances (LCTRS) was proposed. The method includes three steps, procedure of two points prediction, procedure of validation by multiple points regression and sequential matching. The t R of compounds on a HPLC column can be calculated by standard retention time and linear relationship. The method was validated in two medicines on 30 columns. It was demonstrated that, LCTRS method is simple, but more accurate and more robust on different HPLC columns than RR method. Hence quality standards using LCTRS method are easy to reproduce in different laboratories with lower cost of reference substances.
Adachi, Daiki; Nishiguchi, Shu; Fukutani, Naoto; Hotta, Takayuki; Tashiro, Yuto; Morino, Saori; Shirooka, Hidehiko; Nozaki, Yuma; Hirata, Hinako; Yamaguchi, Moe; Yorozu, Ayanori; Takahashi, Masaki; Aoyama, Tomoki
2017-05-01
The purpose of this study was to investigate which spatial and temporal parameters of the Timed Up and Go (TUG) test are associated with motor function in elderly individuals. This study included 99 community-dwelling women aged 72.9 ± 6.3 years. Step length, step width, single support time, variability of the aforementioned parameters, gait velocity, cadence, reaction time from starting signal to first step, and minimum distance between the foot and a marker placed to 3 in front of the chair were measured using our analysis system. The 10-m walk test, five times sit-to-stand (FTSTS) test, and one-leg standing (OLS) test were used to assess motor function. Stepwise multivariate linear regression analysis was used to determine which TUG test parameters were associated with each motor function test. Finally, we calculated a predictive model for each motor function test using each regression coefficient. In stepwise linear regression analysis, step length and cadence were significantly associated with the 10-m walk test, FTSTS and OLS test. Reaction time was associated with the FTSTS test, and step width was associated with the OLS test. Each predictive model showed a strong correlation with the 10-m walk test and OLS test (P motor function test. Moreover, the TUG test time regarded as the lower extremity function and mobility has strong predictive ability in each motor function test. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.
Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong
2011-01-21
Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.
Drzewiecki, Wojciech
2016-12-01
In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels) was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques. The results proved that in case of sub-pixel evaluation the most accurate prediction of change may not necessarily be based on the most accurate individual assessments. When single methods are considered, based on obtained results Cubist algorithm may be advised for Landsat based mapping of imperviousness for single dates. However, Random Forest may be endorsed when the most reliable evaluation of imperviousness change is the primary goal. It gave lower accuracies for individual assessments, but better prediction of change due to more correlated errors of individual predictions. Heterogeneous model ensembles performed for individual time points assessments at least as well as the best individual models. In case of imperviousness change assessment the ensembles always outperformed single model approaches. It means that it is possible to improve the accuracy of sub-pixel imperviousness change assessment using ensembles of heterogeneous non-linear regression models.
Predicting recycling behaviour: Comparison of a linear regression model and a fuzzy logic model.
Vesely, Stepan; Klöckner, Christian A; Dohnal, Mirko
2016-03-01
In this paper we demonstrate that fuzzy logic can provide a better tool for predicting recycling behaviour than the customarily used linear regression. To show this, we take a set of empirical data on recycling behaviour (N=664), which we randomly divide into two halves. The first half is used to estimate a linear regression model of recycling behaviour, and to develop a fuzzy logic model of recycling behaviour. As the first comparison, the fit of both models to the data included in estimation of the models (N=332) is evaluated. As the second comparison, predictive accuracy of both models for "new" cases (hold-out data not included in building the models, N=332) is assessed. In both cases, the fuzzy logic model significantly outperforms the regression model in terms of fit. To conclude, when accurate predictions of recycling and possibly other environmental behaviours are needed, fuzzy logic modelling seems to be a promising technique. Copyright © 2015 Elsevier Ltd. All rights reserved.
The solution of linear systems of equations with a structural analysis code on the NAS CRAY-2
Poole, Eugene L.; Overman, Andrea L.
1988-01-01
Two methods for solving linear systems of equations on the NAS Cray-2 are described. One is a direct method; the other is an iterative method. Both methods exploit the architecture of the Cray-2, particularly the vectorization, and are aimed at structural analysis applications. To demonstrate and evaluate the methods, they were installed in a finite element structural analysis code denoted the Computational Structural Mechanics (CSM) Testbed. A description of the techniques used to integrate the two solvers into the Testbed is given. Storage schemes, memory requirements, operation counts, and reformatting procedures are discussed. Finally, results from the new methods are compared with results from the initial Testbed sparse Choleski equation solver for three structural analysis problems. The new direct solvers described achieve the highest computational rates of the methods compared. The new iterative methods are not able to achieve as high computation rates as the vectorized direct solvers but are best for well conditioned problems which require fewer iterations to converge to the solution.
Smith, Paul F; Ganesh, Siva; Liu, Ping
2013-10-30
Regression is a common statistical tool for prediction in neuroscience. However, linear regression is by far the most common form of regression used, with regression trees receiving comparatively little attention. In this study, the results of conventional multiple linear regression (MLR) were compared with those of random forest regression (RFR), in the prediction of the concentrations of 9 neurochemicals in the vestibular nucleus complex and cerebellum that are part of the l-arginine biochemical pathway (agmatine, putrescine, spermidine, spermine, l-arginine, l-ornithine, l-citrulline, glutamate and γ-aminobutyric acid (GABA)). The R(2) values for the MLRs were higher than the proportion of variance explained values for the RFRs: 6/9 of them were ≥ 0.70 compared to 4/9 for RFRs. Even the variables that had the lowest R(2) values for the MLRs, e.g. ornithine (0.50) and glutamate (0.61), had much lower proportion of variance explained values for the RFRs (0.27 and 0.49, respectively). The RSE values for the MLRs were lower than those for the RFRs in all but two cases. In general, MLRs seemed to be superior to the RFRs in terms of predictive value and error. In the case of this data set, MLR appeared to be superior to RFR in terms of its explanatory value and error. This result suggests that MLR may have advantages over RFR for prediction in neuroscience with this kind of data set, but that RFR can still have good predictive value in some cases. Copyright © 2013 Elsevier B.V. All rights reserved.
Philipp Sterzer
2016-10-01
Full Text Available Current theories in the framework of hierarchical predictive coding propose that positive symptoms of schizophrenia, such as delusions and hallucinations, arise from an alteration in Bayesian inference, the term inference referring to a process by which learned predictions are used to infer probable causes of sensory data. However, for one particularly striking and frequent symptom of schizophrenia, thought insertion, no plausible account has been proposed in terms of the predictive-coding framework. Here we propose that thought insertion is due to an altered experience of thoughts as coming from nowhere, as is already indicated by the early 20th century phenomenological accounts by the early Heidelberg School of psychiatry. These accounts identified thought insertion as one of the self-disturbances (from German: Ichstörungen of schizophrenia and used mescaline as a model-psychosis in healthy individuals to explore the possible mechanisms. The early Heidelberg School (Gruhle, Mayer-Gross, Beringer first named and defined the self-disturbances, and proposed that thought insertion involves a disruption of the inner connectedness of thoughts and experiences, and a becoming sensory of those thoughts experienced as inserted. This account offers a novel way to integrate the phenomenology of thought insertion with the predictive coding framework. We argue that the altered experience of thoughts may be caused by a reduced precision of context-dependent predictions, relative to sensory precision. According to the principles of Bayesian inference, this reduced precision leads to increased prediction-error signals evoked by the neural activity that encodes thoughts. Thus, in analogy with the prediction-error related aberrant salience of external events that has been proposed previously, internal events such as thoughts (including volitions, emotions and memories can also be associated with increased prediction-error signaling and are thus imbued with
2012-08-01
Activities within the frame of the IAEA's Technical Working Group on Advanced Technologies for HWRs (TWG-HWR) are conducted in a project within the IAEA's subprogramme on nuclear power reactor technology development. The objective of the activities on HWRs is to foster, within the frame of the TWG-HWR, information exchange and cooperative research on technology development for current and future HWRs, with an emphasis on safety, economics and fuel resource sustainability. One of the activities recommended by the TWG-HWR was an international standard problem exercise entitled Intercomparison and Validation of Computer Codes for Thermalhydraulics Safety Analyses. Intercomparison and validation of computer codes used in different countries for thermalhydraulics safety analyses will enhance the confidence in the predictions made by these codes. However, the intercomparison and validation exercise needs a set of reliable experimental data. Two RD-14M small break loss of coolant accident (SBLOCA) tests, simulating HWR LOCA behaviour, conducted by Atomic Energy of Canada Ltd (AECL), were selected for this validation project. This report provides a comparison of the results obtained from eight participating organizations from six countries (Argentina, Canada, China, India, Republic of Korea, and Romania), utilizing four different computer codes (ATMIKA, CATHENA, MARS-KS, and RELAP5). General conclusions are reached and recommendations made.
Rotor Wake/Stator Interaction Noise Prediction Code Technical Documentation and User's Manual
Topol, David A.; Mathews, Douglas C.
2010-01-01
This report documents the improvements and enhancements made by Pratt & Whitney to two NASA programs which together will calculate noise from a rotor wake/stator interaction. The code is a combination of subroutines from two NASA programs with many new features added by Pratt & Whitney. To do a calculation V072 first uses a semi-empirical wake prediction to calculate the rotor wake characteristics at the stator leading edge. Results from the wake model are then automatically input into a rotor wake/stator interaction analytical noise prediction routine which calculates inlet aft sound power levels for the blade-passage-frequency tones and their harmonics, along with the complex radial mode amplitudes. The code allows for a noise calculation to be performed for a compressor rotor wake/stator interaction, a fan wake/FEGV interaction, or a fan wake/core stator interaction. This report is split into two parts, the first part discusses the technical documentation of the program as improved by Pratt & Whitney. The second part is a user's manual which describes how input files are created and how the code is run.
Stekelenburg, Jeroen J; Vroomen, Jean
2012-01-01
In many natural audiovisual events (e.g., a clap of the two hands), the visual signal precedes the sound and thus allows observers to predict when, where, and which sound will occur. Previous studies have reported that there are distinct neural correlates of temporal (when) versus phonetic/semantic (which) content on audiovisual integration. Here we examined the effect of visual prediction of auditory location (where) in audiovisual biological motion stimuli by varying the spatial congruency between the auditory and visual parts. Visual stimuli were presented centrally, whereas auditory stimuli were presented either centrally or at 90° azimuth. Typical sub-additive amplitude reductions (AV - V audiovisual interaction was also found at 40-60 ms (P50) in the spatially congruent condition, while no effect of congruency was found on the suppression of the P2. This indicates that visual prediction of auditory location can be coded very early in auditory processing.
Towards Automated Binding Affinity Prediction Using an Iterative Linear Interaction Energy Approach
C. Ruben Vosmeer
2014-01-01
Full Text Available Binding affinity prediction of potential drugs to target and off-target proteins is an essential asset in drug development. These predictions require the calculation of binding free energies. In such calculations, it is a major challenge to properly account for both the dynamic nature of the protein and the possible variety of ligand-binding orientations, while keeping computational costs tractable. Recently, an iterative Linear Interaction Energy (LIE approach was introduced, in which results from multiple simulations of a protein-ligand complex are combined into a single binding free energy using a Boltzmann weighting-based scheme. This method was shown to reach experimental accuracy for flexible proteins while retaining the computational efficiency of the general LIE approach. Here, we show that the iterative LIE approach can be used to predict binding affinities in an automated way. A workflow was designed using preselected protein conformations, automated ligand docking and clustering, and a (semi-automated molecular dynamics simulation setup. We show that using this workflow, binding affinities of aryloxypropanolamines to the malleable Cytochrome P450 2D6 enzyme can be predicted without a priori knowledge of dominant protein-ligand conformations. In addition, we provide an outlook for an approach to assess the quality of the LIE predictions, based on simulation outcomes only.
Linear genetic programming application for successive-station monthly streamflow prediction
Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit
2014-09-01
In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.
A study on the prediction capability of GOTHIC and HYCA3D code for local hydrogen concentrations
Choi, Y. S.; Lee, W. J.; Lee, J. J.; Park, K. C.
2002-01-01
In this study the prediction capability of GOTHIC and HYCA3D code for local hydrogen concentrations was verified with experimental results. Among the experiments, executed by SNU and other organization inside and outside of the country, the fast transient and the obstacle cases are selected. In case of large subcompartment both the code show good agreement with the experimental data. But in case of small and complex geometry or fast transient the results of GOTHIC code have the large difference from experimental ones. This represents that GOTHIC code is unsuitable for these cases. On the contrary HTCA3D code agrees well with all the experimental data
The Dangers of Estimating V˙O2max Using Linear, Nonexercise Prediction Models.
Nevill, Alan M; Cooke, Carlton B
2017-05-01
This study aimed to compare the accuracy and goodness of fit of two competing models (linear vs allometric) when estimating V˙O2max (mL·kg·min) using nonexercise prediction models. The two competing models were fitted to the V˙O2max (mL·kg·min) data taken from two previously published studies. Study 1 (the Allied Dunbar National Fitness Survey) recruited 1732 randomly selected healthy participants, 16 yr and older, from 30 English parliamentary constituencies. Estimates of V˙O2max were obtained using a progressive incremental test on a motorized treadmill. In study 2, maximal oxygen uptake was measured directly during a fatigue limited treadmill test in older men (n = 152) and women (n = 146) 55 to 86 yr old. In both studies, the quality of fit associated with estimating V˙O2max (mL·kg·min) was superior using allometric rather than linear (additive) models based on all criteria (R, maximum log-likelihood, and Akaike information criteria). Results suggest that linear models will systematically overestimate V˙O2max for participants in their 20s and underestimate V˙O2max for participants in their 60s and older. The residuals saved from the linear models were neither normally distributed nor independent of the predicted values nor age. This will probably explain the absence of a key quadratic age term in the linear models, crucially identified using allometric models. Not only does the curvilinear age decline within an exponential function follow a more realistic age decline (the right-hand side of a bell-shaped curve), but the allometric models identified either a stature-to-body mass ratio (study 1) or a fat-free mass-to-body mass ratio (study 2), both associated with leanness when estimating V˙O2max. Adopting allometric models will provide more accurate predictions of V˙O2max (mL·kg·min) using plausible, biologically sound, and interpretable models.
Schwab, J. R.; Povinelli, L. A.
1984-01-01
A comparison of the secondary flows computed by the viscous Kreskovsky-Briley-McDonald code and the inviscid Denton code with benchmark experimental data for turning duct is presented. The viscous code is a fully parabolized space-marching Navier-Stokes solver while the inviscid code is a time-marching Euler solver. The experimental data were collected by Taylor, Whitelaw, and Yianneskis with a laser Doppler velocimeter system in a 90 deg turning duct of square cross-section. The agreement between the viscous and inviscid computations was generally very good for the streamwise primary velocity and the radial secondary velocity, except at the walls, where slip conditions were specified for the inviscid code. The agreement between both the computations and the experimental data was not as close, especially at the 60.0 deg and 77.5 deg angular positions within the duct. This disagreement was attributed to incomplete modelling of the vortex development near the suction surface.
Montoya Andrade, Dan-El; Villa Jaén, Antonio de la; García Santana, Agustín
2014-01-01
Highlights: • We considered the linear generator copper losses in the proposed MPC strategy. • We maximized the power transferred to the generator side power converter. • The proposed MPC increases the useful average power injected into the grid. • The stress level of the PTO system can be reduced by the proposed MPC. - Abstract: The amount of energy that a wave energy converter can extract depends strongly on the control strategy applied to the power take-off system. It is well known that, ideally, the reactive control allows for maximum energy extraction from waves. However, the reactive control is intrinsically noncausal in practice and requires some kind of causal approach to be applied. Moreover, this strategy does not consider physical constraints and this could be a problem because the system could achieve unacceptable dynamic values. These, and other control techniques have focused on the wave energy extraction problem in order to maximize the energy absorbed by the power take-off device without considering the possible losses in intermediate devices. In this sense, a reactive control that considers the linear generator copper losses has been recently proposed to increase the useful power injected into the grid. Among the control techniques that have emerged recently, the model predictive control represents a promising strategy. This approach performs an optimization process on a time prediction horizon incorporating dynamic constraints associated with the physical features of the power take-off system. This paper proposes a model predictive control technique that considers the copper losses in the control optimization process of point absorbers with direct drive linear generators. This proposal makes the most of reactive control as it considers the copper losses, and it makes the most of the model predictive control, as it considers the system constraints. This means that the useful power transferred from the linear generator to the power
Prediction of linear B-cell epitopes of hepatitis C virus for vaccine development
2015-01-01
Background High genetic heterogeneity in the hepatitis C virus (HCV) is the major challenge of the development of an effective vaccine. Existing studies for developing HCV vaccines have mainly focused on T-cell immune response. However, identification of linear B-cell epitopes that can stimulate B-cell response is one of the major tasks of peptide-based vaccine development. Owing to the variability in B-cell epitope length, the prediction of B-cell epitopes is much more complex than that of T-cell epitopes. Furthermore, the motifs of linear B-cell epitopes in different pathogens are quite different (e. g. HCV and hepatitis B virus). To cope with this challenge, this work aims to propose an HCV-customized sequence-based prediction method to identify B-cell epitopes of HCV. Results This work establishes an experimentally verified dataset comprising the B-cell response of HCV dataset consisting of 774 linear B-cell epitopes and 774 non B-cell epitopes from the Immune Epitope Database. An interpretable rule mining system of B-cell epitopes (IRMS-BE) is proposed to select informative physicochemical properties (PCPs) and then extracts several if-then rule-based knowledge for identifying B-cell epitopes. A web server Bcell-HCV was implemented using an SVM with the 34 informative PCPs, which achieved a training accuracy of 79.7% and test accuracy of 70.7% better than the SVM-based methods for identifying B-cell epitopes of HCV and the two general-purpose methods. This work performs advanced analysis of the 34 informative properties, and the results indicate that the most effective property is the alpha-helix structure of epitopes, which influences the connection between host cells and the E2 proteins of HCV. Furthermore, 12 interpretable rules are acquired from top-five PCPs and achieve a sensitivity of 75.6% and specificity of 71.3%. Finally, a conserved promising vaccine candidate, PDREMVLYQE, is identified for inclusion in a vaccine against HCV. Conclusions This work
Longge Zhang
2013-01-01
Full Text Available Two automatic robust model predictive control strategies are presented for uncertain polytopic linear plants with input and output constraints. A sequence of nested geometric proportion asymptotically stable ellipsoids and controllers is constructed offline first. Then the feedback controllers are automatically selected with the receding horizon online in the first strategy. Finally, a modified automatic offline robust MPC approach is constructed to improve the closed system's performance. The new proposed strategies not only reduce the conservatism but also decrease the online computation. Numerical examples are given to illustrate their effectiveness.
Morales, Esteban; de Leon, John Mark S; Abdollahi, Niloufar; Yu, Fei; Nouri-Mahdavi, Kouros; Caprioli, Joseph
2016-03-01
The study was conducted to evaluate threshold smoothing algorithms to enhance prediction of the rates of visual field (VF) worsening in glaucoma. We studied 798 patients with primary open-angle glaucoma and 6 or more years of follow-up who underwent 8 or more VF examinations. Thresholds at each VF location for the first 4 years or first half of the follow-up time (whichever was greater) were smoothed with clusters defined by the nearest neighbor (NN), Garway-Heath, Glaucoma Hemifield Test (GHT), and weighting by the correlation of rates at all other VF locations. Thresholds were regressed with a pointwise exponential regression (PER) model and a pointwise linear regression (PLR) model. Smaller root mean square error (RMSE) values of the differences between the observed and the predicted thresholds at last two follow-ups indicated better model predictions. The mean (SD) follow-up times for the smoothing and prediction phase were 5.3 (1.5) and 10.5 (3.9) years. The mean RMSE values for the PER and PLR models were unsmoothed data, 6.09 and 6.55; NN, 3.40 and 3.42; Garway-Heath, 3.47 and 3.48; GHT, 3.57 and 3.74; and correlation of rates, 3.59 and 3.64. Smoothed VF data predicted better than unsmoothed data. Nearest neighbor provided the best predictions; PER also predicted consistently more accurately than PLR. Smoothing algorithms should be used when forecasting VF results with PER or PLR. The application of smoothing algorithms on VF data can improve forecasting in VF points to assist in treatment decisions.
MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.
2005-01-01
Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.
Flexible non-linear predictive models for large-scale wind turbine diagnostics
Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole
2017-01-01
We demonstrate how flexible non-linear models can provide accurate and robust predictions on turbine component temperature sensor data using data-driven principles and only a minimum of system modeling. The merits of different model architectures are evaluated using data from a large set...... of turbines operating under diverse conditions. We then go on to test the predictive models in a diagnostic setting, where the output of the models are used to detect mechanical faults in rotor bearings. Using retrospective data from 22 actual rotor bearing failures, the fault detection performance...... of the models are quantified using a structured framework that provides the metrics required for evaluating the performance in a fleet wide monitoring setup. It is demonstrated that faults are identified with high accuracy up to 45 days before a warning from the hard-threshold warning system....
Dynamics and control of quadcopter using linear model predictive control approach
Islam, M.; Okasha, M.; Idres, M. M.
2017-12-01
This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.
TBM performance prediction in Yucca Mountain welded tuff from linear cutter tests
Gertsch, R.; Ozdemir, L.; Gertsch, L.
1992-01-01
This paper discusses performance prediction which were developed for tunnel boring machines operating in welded tuff for the construction of the experimental study facility and the potential nuclear waste repository at Yucca Mountain. The predictions were based on test data obtained from an extensive series of linear cutting tests performed on samples of Topopah String welded tuff from the Yucca Mountain Project site. Using the cutter force, spacing, and penetration data from the experimental program, the thrust, torque, power, and rate of penetration were estimated for a 25 ft diameter tunnel boring machine (TBM) operating in welded tuff. The result show that the Topopah Spring welded tuff (TSw2) can be excavated at relatively high rates of advance with state-of-the-art TBMs. The result also show, however, that the TBM torque and power requirements will be higher than estimated based on rock physical properties and past tunneling experience in rock formations of similar strength
Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari
2018-01-01
Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg
[Symbol: see text]2 Optimized predictive image coding with [Symbol: see text]∞ bound.
Chuah, Sceuchin; Dumitrescu, Sorina; Wu, Xiaolin
2013-12-01
In many scientific, medical, and defense applications of image/video compression, an [Symbol: see text]∞ error bound is required. However, pure[Symbol: see text]∞-optimized image coding, colloquially known as near-lossless image coding, is prone to structured errors such as contours and speckles if the bit rate is not sufficiently high; moreover, most of the previous [Symbol: see text]∞-based image coding methods suffer from poor rate control. In contrast, the [Symbol: see text]2 error metric aims for average fidelity and hence preserves the subtlety of smooth waveforms better than the ∞ error metric and it offers fine granularity in rate control, but pure [Symbol: see text]2-based image coding methods (e.g., JPEG 2000) cannot bound individual errors as the [Symbol: see text]∞-based methods can. This paper presents a new compression approach to retain the benefits and circumvent the pitfalls of the two error metrics. A common approach of near-lossless image coding is to embed into a DPCM prediction loop a uniform scalar quantizer of residual errors. The said uniform scalar quantizer is replaced, in the proposed new approach, by a set of context-based [Symbol: see text]2-optimized quantizers. The optimization criterion is to minimize a weighted sum of the [Symbol: see text]2 distortion and the entropy while maintaining a strict [Symbol: see text]∞ error bound. The resulting method obtains good rate-distortion performance in both [Symbol: see text]2 and [Symbol: see text]∞ metrics and also increases the rate granularity. Compared with JPEG 2000, the new method not only guarantees lower [Symbol: see text]∞ error for all bit rates, but also it achieves higher PSNR for relatively high bit rates.
An adaptive mode-driven spatiotemporal motion vector prediction for wavelet video coding
Zhao, Fan; Liu, Guizhong; Qi, Yong
2010-07-01
The three-dimensional subband/wavelet codecs use 5/3 filters rather than Haar filters for the motion compensation temporal filtering (MCTF) to improve the coding gain. In order to curb the increased motion vector rate, an adaptive motion mode driven spatiotemporal motion vector prediction (AMDST-MVP) scheme is proposed. First, by making use of the direction histograms of four motion vector fields resulting from the initial spatial motion vector prediction (SMVP), the motion mode of the current GOP is determined according to whether the fast or complex motion exists in the current GOP. Then the GOP-level MVP scheme is thereby determined by either the S-MVP or the AMDST-MVP, namely, AMDST-MVP is the combination of S-MVP and temporal-MVP (T-MVP). If the latter is adopted, the motion vector difference (MVD) between the neighboring MV fields and the S-MVP resulting MV of the current block is employed to decide whether or not the MV of co-located block in the previous frame is used for prediction the current block. Experimental results show that AMDST-MVP not only can improve the coding efficiency but also reduce the number of computation complexity.
Wilson, S. R.; Close, M. E.; Abraham, P.
2018-01-01
Diffuse nitrate losses from agricultural land pollute groundwater resources worldwide, but can be attenuated under reducing subsurface conditions. In New Zealand, the ability to predict where groundwater denitrification occurs is important for understanding the linkage between land use and discharges of nitrate-bearing groundwater to streams. This study assesses the application of linear discriminant analysis (LDA) for predicting groundwater redox status for Southland, a major dairy farming region in New Zealand. Data cases were developed by assigning a redox status to samples derived from a regional groundwater quality database. Pre-existing regional-scale geospatial databases were used as training variables for the discriminant functions. The predictive accuracy of the discriminant functions was slightly improved by optimising the thresholds between sample depth classes. The models predict 23% of the region as being reducing at shallow depths (water table, and low-permeability clastic sediments. The coastal plains are an area of widespread groundwater discharge, and the soil and hydrology characteristics require the land to be artificially drained to render the land suitable for farming. For the improvement of water quality in coastal areas, it is therefore important that land and water management efforts focus on understanding hydrological bypassing that may occur via artificial drainage systems.
Hong Junjie, E-mail: hongjjie@mail.sysu.edu.cn [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China); Li Liyi, E-mail: liliyi@hit.edu.cn [Dept. Electrical Engineering, Harbin Institute of Technology, Harbin 150000 (China); Zong Zhijian; Liu Zhongtu [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China)
2011-10-15
Highlights: {yields} The structure of the permanent magnet linear synchronous motor (SW-PMLSM) is new. {yields} A new current control method CEVPC is employed in this motor. {yields} The sectional power supply method is different to the others and effective. {yields} The performance gets worse with voltage and current limitations. - Abstract: To include features such as greater thrust density, higher efficiency without reducing the thrust stability, this paper proposes a section winding permanent magnet linear synchronous motor (SW-PMLSM), whose iron core is continuous, whereas winding is divided. The discrete system model of the motor is derived. With the definition of the current error vector and selection of the value function, the theory of the current error vector based prediction control (CEVPC) for the motor currents is explained clearly. According to the winding section feature, the motion region of the mover is divided into five zones, in which the implementation of the current predictive control method is proposed. Finally, the experimental platform is constructed and experiments are carried out. The results show: the current control effect has good dynamic response, and the thrust on the mover remains constant basically.
A review of model predictive control: moving from linear to nonlinear design methods
Nandong, J.; Samyudia, Y.; Tade, M.O.
2006-01-01
Linear model predictive control (LMPC) has now been considered as an industrial control standard in process industry. Its extension to nonlinear cases however has not yet gained wide acceptance due to many reasons, e.g. excessively heavy computational load and effort, thus, preventing its practical implementation in real-time control. The application of nonlinear MPC (NMPC) is advantageous for processes with strong nonlinearity or when the operating points are frequently moved from one set point to another due to, for instance, changes in market demands. Much effort has been dedicated towards improving the computational efficiency of NMPC as well as its stability analysis. This paper provides a review on alternative ways of extending linear MPC to the nonlinear one. We also highlight the critical issues pertinent to the applications of NMPC and discuss possible solutions to address these issues. In addition, we outline the future research trend in the area of model predictive control by emphasizing on the potential applications of multi-scale process model within NMPC
Using NCAP to predict RFI effects in linear bipolar integrated circuits
Fang, T.-F.; Whalen, J. J.; Chen, G. K. C.
1980-11-01
Applications of the Nonlinear Circuit Analysis Program (NCAP) to calculate RFI effects in electronic circuits containing discrete semiconductor devices have been reported upon previously. The objective of this paper is to demonstrate that the computer program NCAP also can be used to calcuate RFI effects in linear bipolar integrated circuits (IC's). The IC's reported upon are the microA741 operational amplifier (op amp) which is one of the most widely used IC's, and a differential pair which is a basic building block in many linear IC's. The microA741 op amp was used as the active component in a unity-gain buffer amplifier. The differential pair was used in a broad-band cascode amplifier circuit. The computer program NCAP was used to predict how amplitude-modulated RF signals are demodulated in the IC's to cause undesired low-frequency responses. The predicted and measured results for radio frequencies in the 0.050-60-MHz range are in good agreement.
Robust entry guidance using linear covariance-based model predictive control
Jianjun Luo
2017-02-01
Full Text Available For atmospheric entry vehicles, guidance design can be accomplished by solving an optimal issue using optimal control theories. However, traditional design methods generally focus on the nominal performance and do not include considerations of the robustness in the design process. This paper proposes a linear covariance-based model predictive control method for robust entry guidance design. Firstly, linear covariance analysis is employed to directly incorporate the robustness into the guidance design. The closed-loop covariance with the feedback updated control command is initially formulated to provide the expected errors of the nominal state variables in the presence of uncertainties. Then, the closed-loop covariance is innovatively used as a component of the cost function to guarantee the robustness to reduce its sensitivity to uncertainties. After that, the models predictive control is used to solve the optimal problem, and the control commands (bank angles are calculated. Finally, a series of simulations for different missions have been completed to demonstrate the high performance in precision and the robustness with respect to initial perturbations as well as uncertainties in the entry process. The 3σ confidence region results in the presence of uncertainties which show that the robustness of the guidance has been improved, and the errors of the state variables are decreased by approximately 35%.
Li, Chuan; Han, Lei; Ma, Chun-Wai; Lai, Suk-King; Lai, Chun-Hong; Shum, Daisy Kwok Yan; Chan, Ying-Shing
2013-07-01
Using sinusoidal oscillations of linear acceleration along both the horizontal and vertical planes to stimulate otolith organs in the inner ear, we charted the postnatal time at which responsive neurons in the rat inferior olive (IO) first showed Fos expression, an indicator of neuronal recruitment into the otolith circuit. Neurons in subnucleus dorsomedial cell column (DMCC) were activated by vertical stimulation as early as P9 and by horizontal (interaural) stimulation as early as P11. By P13, neurons in the β subnucleus of IO (IOβ) became responsive to horizontal stimulation along the interaural and antero-posterior directions. By P21, neurons in the rostral IOβ became also responsive to vertical stimulation, but those in the caudal IOβ remained responsive only to horizontal stimulation. Nearly all functionally activated neurons in DMCC and IOβ were immunopositive for the NR1 subunit of the NMDA receptor and the GluR2/3 subunit of the AMPA receptor. In situ hybridization studies further indicated abundant mRNA signals of the glutamate receptor subunits by the end of the second postnatal week. This is reinforced by whole-cell patch-clamp data in which glutamate receptor-mediated miniature excitatory postsynaptic currents of rostral IOβ neurons showed postnatal increase in amplitude, reaching the adult level by P14. Further, these neurons exhibited subthreshold oscillations in membrane potential as from P14. Taken together, our results support that ionotropic glutamate receptors in the IO enable postnatal coding of gravity-related information and that the rostral IOβ is the only IO subnucleus that encodes spatial orientations in 3-D.
Predicting Fuel Ignition Quality Using 1H NMR Spectroscopy and Multiple Linear Regression
Abdul Jameel, Abdul Gani
2016-09-14
An improved model for the prediction of ignition quality of hydrocarbon fuels has been developed using 1H nuclear magnetic resonance (NMR) spectroscopy and multiple linear regression (MLR) modeling. Cetane number (CN) and derived cetane number (DCN) of 71 pure hydrocarbons and 54 hydrocarbon blends were utilized as a data set to study the relationship between ignition quality and molecular structure. CN and DCN are functional equivalents and collectively referred to as D/CN, herein. The effect of molecular weight and weight percent of structural parameters such as paraffinic CH3 groups, paraffinic CH2 groups, paraffinic CH groups, olefinic CH–CH2 groups, naphthenic CH–CH2 groups, and aromatic C–CH groups on D/CN was studied. A particular emphasis on the effect of branching (i.e., methyl substitution) on the D/CN was studied, and a new parameter denoted as the branching index (BI) was introduced to quantify this effect. A new formula was developed to calculate the BI of hydrocarbon fuels using 1H NMR spectroscopy. Multiple linear regression (MLR) modeling was used to develop an empirical relationship between D/CN and the eight structural parameters. This was then used to predict the DCN of many hydrocarbon fuels. The developed model has a high correlation coefficient (R2 = 0.97) and was validated with experimentally measured DCN of twenty-two real fuel mixtures (e.g., gasolines and diesels) and fifty-nine blends of known composition, and the predicted values matched well with the experimental data.
From structure prediction to genomic screens for novel non-coding RNAs
Gorodkin, Jan; Hofacker, Ivo L.
2011-01-01
Abstract: Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction....... This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early...... upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other....
CCFL in hot legs and steam generators and its prediction with the CATHARE code
Geffraye, G.; Bazin, P.; Pichon, P.
1995-01-01
This paper presents a study about the Counter-Current Flow Limitation (CCFL) prediction in hot legs and steam generators (SG) in both system test facilities and pressurized water reactors. Experimental data are analyzed, particularly the recent MHYRESA test data. Geometrical and scale effects on the flooding behavior are shown. The CATHARE code modelling problems concerning the CCFL prediction are discussed. A method which gives the user the possibility of controlling the flooding limit at a given location is developed. In order to minimize the user effect, a methodology is proposed to the user in case of a calculation with a counter-current flow between the upper plenum and the SF U-tubes. The following questions have to be made clear for the user: when to use the CATHARE CCFL option, which correlation to use, and where to locate the flooding limit
The effect of turbulent mixing models on the predictions of subchannel codes
Tapucu, A.; Teyssedou, A.; Tye, P.; Troche, N.
1994-01-01
In this paper, the predictions of the COBRA-IV and ASSERT-4 subchannel codes have been compared with experimental data on void fraction, mass flow rate, and pressure drop obtained for two interconnected subchannels. COBRA-IV is based on a one-dimensional separated flow model with the turbulent intersubchannel mixing formulated as an extension of the single-phase mixing model, i.e. fluctuating equal mass exchange. ASSERT-4 is based on a drift flux model with the turbulent mixing modelled by assuming an exchange of equal volumes with different densities thus allowing a net fluctuating transverse mass flux from one subchannel to the other. This feature is implemented in the constitutive relationship for the relative velocity required by the conservation equations. It is observed that the predictions of ASSERT-4 follow the experimental trends better than COBRA-IV; therefore the approach of equal volume exchange constitutes an improvement over that of the equal mass exchange. ((orig.))
CCFL in hot legs and steam generators and its prediction with the CATHARE code
Geffraye, G.; Bazin, P.; Pichon, P. [CEA/DRN/STR, Grenoble (France)
1995-09-01
This paper presents a study about the Counter-Current Flow Limitation (CCFL) prediction in hot legs and steam generators (SG) in both system test facilities and pressurized water reactors. Experimental data are analyzed, particularly the recent MHYRESA test data. Geometrical and scale effects on the flooding behavior are shown. The CATHARE code modelling problems concerning the CCFL prediction are discussed. A method which gives the user the possibility of controlling the flooding limit at a given location is developed. In order to minimize the user effect, a methodology is proposed to the user in case of a calculation with a counter-current flow between the upper plenum and the SF U-tubes. The following questions have to be made clear for the user: when to use the CATHARE CCFL option, which correlation to use, and where to locate the flooding limit.
High Angular Momentum Halo Gas: A Feedback and Code-independent Prediction of LCDM
Stewart, Kyle R.; Maller, Ariyeh H.; Oñorbe, Jose; Bullock, James S.; Joung, M. Ryan; Devriendt, Julien; Ceverino, Daniel; Kereš, Dušan; Hopkins, Philip F.; Faucher-Giguère, Claude-André
2017-07-01
We investigate angular momentum acquisition in Milky Way-sized galaxies by comparing five high resolution zoom-in simulations, each implementing identical cosmological initial conditions but utilizing different hydrodynamic codes: Enzo, Art, Ramses, Arepo, and Gizmo-PSPH. Each code implements a distinct set of feedback and star formation prescriptions. We find that while many galaxy and halo properties vary between the different codes (and feedback prescriptions), there is qualitative agreement on the process of angular momentum acquisition in the galaxy’s halo. In all simulations, cold filamentary gas accretion to the halo results in ˜4 times more specific angular momentum in cold halo gas (λ cold ≳ 0.1) than in the dark matter halo. At z > 1, this inflow takes the form of inspiraling cold streams that are co-directional in the halo of the galaxy and are fueled, aligned, and kinematically connected to filamentary gas infall along the cosmic web. Due to the qualitative agreement among disparate simulations, we conclude that the buildup of high angular momentum halo gas and the presence of these inspiraling cold streams are robust predictions of Lambda Cold Dark Matter galaxy formation, though the detailed morphology of these streams is significantly less certain. A growing body of observational evidence suggests that this process is borne out in the real universe.
High Angular Momentum Halo Gas: A Feedback and Code-independent Prediction of LCDM
Stewart, Kyle R. [Department of Mathematical Sciences, California Baptist University, 8432 Magnolia Ave., Riverside, CA 92504 (United States); Maller, Ariyeh H. [Department of Physics, New York City College of Technology, 300 Jay St., Brooklyn, NY 11201 (United States); Oñorbe, Jose [Max-Planck-Institut für Astronomie, Königstuhl 17, D-69117 Heidelberg (Germany); Bullock, James S. [Center for Cosmology, Department of Physics and Astronomy, The University of California at Irvine, Irvine, CA 92697 (United States); Joung, M. Ryan [Department of Astronomy, Columbia University, New York, NY 10027 (United States); Devriendt, Julien [Department of Physics, University of Oxford, The Denys Wilkinson Building, Keble Rd., Oxford OX1 3RH (United Kingdom); Ceverino, Daniel [Zentrum für Astronomie der Universität Heidelberg, Institut für Theoretische Astrophysik, Albert-Ueberle-Str. 2, D-69120 Heidelberg (Germany); Kereš, Dušan [Department of Physics, Center for Astrophysics and Space Sciences, University of California at San Diego, 9500 Gilman Dr., La Jolla, CA 92093 (United States); Hopkins, Philip F. [California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125 (United States); Faucher-Giguère, Claude-André [Department of Physics and Astronomy and CIERA, Northwestern University, 2145 Sheridan Rd., Evanston, IL 60208 (United States)
2017-07-01
We investigate angular momentum acquisition in Milky Way-sized galaxies by comparing five high resolution zoom-in simulations, each implementing identical cosmological initial conditions but utilizing different hydrodynamic codes: Enzo, Art, Ramses, Arepo, and Gizmo-PSPH. Each code implements a distinct set of feedback and star formation prescriptions. We find that while many galaxy and halo properties vary between the different codes (and feedback prescriptions), there is qualitative agreement on the process of angular momentum acquisition in the galaxy’s halo. In all simulations, cold filamentary gas accretion to the halo results in ∼4 times more specific angular momentum in cold halo gas ( λ {sub cold} ≳ 0.1) than in the dark matter halo. At z > 1, this inflow takes the form of inspiraling cold streams that are co-directional in the halo of the galaxy and are fueled, aligned, and kinematically connected to filamentary gas infall along the cosmic web. Due to the qualitative agreement among disparate simulations, we conclude that the buildup of high angular momentum halo gas and the presence of these inspiraling cold streams are robust predictions of Lambda Cold Dark Matter galaxy formation, though the detailed morphology of these streams is significantly less certain. A growing body of observational evidence suggests that this process is borne out in the real universe.
Zounemat-Kermani, Mohammad
2012-08-01
In this study, the ability of two models of multi linear regression (MLR) and Levenberg-Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash-Sutcliffe efficiency coefficient ( {| {{{Log}}({{NS}})} |} ) were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.
Kiran Sree Pokkuluri
2014-01-01
Full Text Available Protein coding and promoter region predictions are very important challenges of bioinformatics (Attwood and Teresa, 2000. The identification of these regions plays a crucial role in understanding the genes. Many novel computational and mathematical methods are introduced as well as existing methods that are getting refined for predicting both of the regions separately; still there is a scope for improvement. We propose a classifier that is built with MACA (multiple attractor cellular automata and MCC (modified clonal classifier to predict both regions with a single classifier. The proposed classifier is trained and tested with Fickett and Tung (1992 datasets for protein coding region prediction for DNA sequences of lengths 54, 108, and 162. This classifier is trained and tested with MMCRI datasets for protein coding region prediction for DNA sequences of lengths 252 and 354. The proposed classifier is trained and tested with promoter sequences from DBTSS (Yamashita et al., 2006 dataset and nonpromoters from EID (Saxonov et al., 2000 and UTRdb (Pesole et al., 2002 datasets. The proposed model can predict both regions with an average accuracy of 90.5% for promoter and 89.6% for protein coding region predictions. The specificity and sensitivity values of promoter and protein coding region predictions are 0.89 and 0.92, respectively.
Wosnik, Martin [Univ. of New Hampshire, Durham, NH (United States). Center for Ocean Renewable Energy; Bachant, Pete [Univ. of New Hampshire, Durham, NH (United States). Center for Ocean Renewable Energy; Neary, Vincent Sinclair [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Murphy, Andrew W. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2016-09-01
CACTUS, developed by Sandia National Laboratories, is an open-source code for the design and analysis of wind and hydrokinetic turbines. While it has undergone extensive validation for both vertical axis and horizontal axis wind turbines, and it has been demonstrated to accurately predict the performance of horizontal (axial-flow) hydrokinetic turbines, its ability to predict the performance of crossflow hydrokinetic turbines has yet to be tested. The present study addresses this problem by comparing the predicted performance curves derived from CACTUS simulations of the U.S. Department of Energy’s 1:6 scale reference model crossflow turbine to those derived by experimental measurements in a tow tank using the same model turbine at the University of New Hampshire. It shows that CACTUS cannot accurately predict the performance of this crossflow turbine, raising concerns on its application to crossflow hydrokinetic turbines generally. The lack of quality data on NACA 0021 foil aerodynamic (hydrodynamic) characteristics over the wide range of angles of attack (AoA) and Reynolds numbers is identified as the main cause for poor model prediction. A comparison of several different NACA 0021 foil data sources, derived using both physical and numerical modeling experiments, indicates significant discrepancies at the high AoA experienced by foils on crossflow turbines. Users of CACTUS for crossflow hydrokinetic turbines are, therefore, advised to limit its application to higher tip speed ratios (lower AoA), and to carefully verify the reliability and accuracy of their foil data. Accurate empirical data on the aerodynamic characteristics of the foil is the greatest limitation to predicting performance for crossflow turbines with semi-empirical models like CACTUS. Future improvements of CACTUS for crossflow turbine performance prediction will require the development of accurate foil aerodynamic characteristic data sets within the appropriate ranges of Reynolds numbers and AoA.
Sokoler, Leo Emil; Frison, Gianluca; Edlund, Kristian
2013-01-01
In this paper, we develop an efficient interior-point method (IPM) for the linear programs arising in economic model predictive control of linear systems. The novelty of our algorithm is that it combines a homogeneous and self-dual model, and a specialized Riccati iteration procedure. We test...
Hunt, Jonathan J; Dayan, Peter; Goodhill, Geoffrey J
2013-01-01
Receptive fields acquired through unsupervised learning of sparse representations of natural scenes have similar properties to primary visual cortex (V1) simple cell receptive fields. However, what drives in vivo development of receptive fields remains controversial. The strongest evidence for the importance of sensory experience in visual development comes from receptive field changes in animals reared with abnormal visual input. However, most sparse coding accounts have considered only normal visual input and the development of monocular receptive fields. Here, we applied three sparse coding models to binocular receptive field development across six abnormal rearing conditions. In every condition, the changes in receptive field properties previously observed experimentally were matched to a similar and highly faithful degree by all the models, suggesting that early sensory development can indeed be understood in terms of an impetus towards sparsity. As previously predicted in the literature, we found that asymmetries in inter-ocular correlation across orientations lead to orientation-specific binocular receptive fields. Finally we used our models to design a novel stimulus that, if present during rearing, is predicted by the sparsity principle to lead robustly to radically abnormal receptive fields.
C. Makendran
2015-01-01
Full Text Available Prediction models for low volume village roads in India are developed to evaluate the progression of different types of distress such as roughness, cracking, and potholes. Even though the Government of India is investing huge quantum of money on road construction every year, poor control over the quality of road construction and its subsequent maintenance is leading to the faster road deterioration. In this regard, it is essential that scientific maintenance procedures are to be evolved on the basis of performance of low volume flexible pavements. Considering the above, an attempt has been made in this research endeavor to develop prediction models to understand the progression of roughness, cracking, and potholes in flexible pavements exposed to least or nil routine maintenance. Distress data were collected from the low volume rural roads covering about 173 stretches spread across Tamil Nadu state in India. Based on the above collected data, distress prediction models have been developed using multiple linear regression analysis. Further, the models have been validated using independent field data. It can be concluded that the models developed in this study can serve as useful tools for the practicing engineers maintaining flexible pavements on low volume roads.
Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa
2015-11-03
Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.
Bunyamin, Muhammad Afif; Yap, Keem Siah; Aziz, Nur Liyana Afiqah Abdul; Tiong, Sheih Kiong; Wong, Shen Yuong; Kamal, Md Fauzan
2013-01-01
This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). The LR is one of the approaches that model the relationship between an output dependant variable, y, with one or more explanatory variables or inputs which denoted as x. It is able to estimate unknown model parameters from inputs data. On the other hand, GA is used to search for the optimal solution until specific criteria is met causing termination. These results include providing good solutions as compared to one optimal solution for complex problems. Thus, GA is widely used as feature selection. By combining the LR and GA (GA-LR), this new technique is able to select the most important input features as well as giving more accurate prediction by minimizing the prediction errors. This new technique is able to produce more consistent of gas emission estimation, which may help in reducing population to the environment. In this paper, the study's interest is focused on nitrous oxides (NOx) prediction. The results of the experiment are encouraging.
Plasma burn-through simulations using the DYON code and predictions for ITER
Kim, Hyun-Tae; Sips, A C C; De Vries, P C
2013-01-01
This paper will discuss simulations of the full ionization process (i.e. plasma burn-through), fundamental to creating high temperature plasma. By means of an applied electric field, the gas is partially ionized by the electron avalanche process. In order for the electron temperature to increase, the remaining neutrals need to be fully ionized in the plasma burn-through phase, as radiation is the main contribution to the electron power loss. The radiated power loss can be significantly affected by impurities resulting from interaction with the plasma facing components. The DYON code is a plasma burn-through simulator developed at Joint European Torus (JET) (Kim et al and EFDA-JET Contributors 2012 Nucl. Fusion 52 103016, Kim, Sips and EFDA-JET Contributors 2013 Nucl. Fusion 53 083024). The dynamic evolution of the plasma temperature and plasma densities including the impurity content is calculated in a self-consistent way using plasma wall interaction models. The recent installation of a beryllium wall at JET enabled validation of the plasma burn-through model in the presence of new, metallic plasma facing components. The simulation results of the plasma burn-through phase show a consistent good agreement against experiments at JET, and explain differences observed during plasma initiation with the old carbon plasma facing components. In the International Thermonuclear Experimental Reactor (ITER), the allowable toroidal electric field is restricted to 0.35 (V m −1 ), which is significantly lower compared to the typical value (∼1 (V m −1 )) used in the present devices. The limitation on toroidal electric field also reduces the range of other operation parameters during plasma formation in ITER. Thus, predictive simulations of plasma burn-through in ITER using validated model is of crucial importance. This paper provides an overview of the DYON code and the validation, together with new predictive simulations for ITER using the DYON code. (paper)
Yock, Adam D; Rao, Arvind; Dong, Lei; Beadle, Beth M; Garden, Adam S; Kudchadker, Rajat J; Court, Laurence E
2014-05-01
The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: -11.6%-23.8%) and 14.6% (range: -7.3%-27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: -6.8%-40.3%) and 13.1% (range: -1.5%-52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: -11.1%-20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography images and facilitate improved treatment management.
Tömösközi, Máté; Fitzek, Frank; Roetter, Daniel Enrique Lucani
2014-01-01
Video surveillance and similar real-time applications on wireless networks require increased reliability and high performance of the underlying transmission layer. Classical solutions, such as Reed-Solomon codes, increase the reliability, but typically have the negative side-effect of additional ...
A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes
Martin, Rodney Alexander
2009-01-01
In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I
Real-time detection of musical onsets with linear prediction and sinusoidal modeling
Glover, John; Lazzarini, Victor; Timoney, Joseph
2011-12-01
Real-time musical note onset detection plays a vital role in many audio analysis processes, such as score following, beat detection and various sound synthesis by analysis methods. This article provides a review of some of the most commonly used techniques for real-time onset detection. We suggest ways to improve these techniques by incorporating linear prediction as well as presenting a novel algorithm for real-time onset detection using sinusoidal modelling. We provide comprehensive results for both the detection accuracy and the computational performance of all of the described techniques, evaluated using Modal, our new open source library for musical onset detection, which comes with a free database of samples with hand-labelled note onsets.
Bayesian techniques for fatigue life prediction and for inference in linear time dependent PDEs
Scavino, Marco
2016-01-08
In this talk we introduce first the main characteristics of a systematic statistical approach to model calibration, model selection and model ranking when stress-life data are drawn from a collection of records of fatigue experiments. Focusing on Bayesian prediction assessment, we consider fatigue-limit models and random fatigue-limit models under different a priori assumptions. In the second part of the talk, we present a hierarchical Bayesian technique for the inference of the coefficients of time dependent linear PDEs, under the assumption that noisy measurements are available in both the interior of a domain of interest and from boundary conditions. We present a computational technique based on the marginalization of the contribution of the boundary parameters and apply it to inverse heat conduction problems.
Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan
2016-12-02
In the postgenomic era, the number of unreviewed protein sequences is remarkably larger and grows tremendously faster than that of reviewed ones. However, existing methods for protein subchloroplast localization often ignore the information from these unlabeled proteins. This paper proposes a multi-label predictor based on ensemble linear neighborhood propagation (LNP), namely, LNP-Chlo, which leverages hybrid sequence-based feature information from both labeled and unlabeled proteins for predicting localization of both single- and multi-label chloroplast proteins. Experimental results on a stringent benchmark dataset and a novel independent dataset suggest that LNP-Chlo performs at least 6% (absolute) better than state-of-the-art predictors. This paper also demonstrates that ensemble LNP significantly outperforms LNP based on individual features. For readers' convenience, the online Web server LNP-Chlo is freely available at http://bioinfo.eie.polyu.edu.hk/LNPChloServer/ .
Hariharan, M; Chee, Lim Sin; Yaacob, Sazali
2012-06-01
Acoustic analysis of infant cry signals has been proven to be an excellent tool in the area of automatic detection of pathological status of an infant. This paper investigates the application of parameter weighting for linear prediction cepstral coefficients (LPCCs) to provide the robust representation of infant cry signals. Three classes of infant cry signals were considered such as normal cry signals, cry signals from deaf babies and babies with asphyxia. A Probabilistic Neural Network (PNN) is suggested to classify the infant cry signals into normal and pathological cries. PNN is trained with different spread factor or smoothing parameter to obtain better classification accuracy. The experimental results demonstrate that the suggested features and classification algorithms give very promising classification accuracy of above 98% and it expounds that the suggested method can be used to help medical professionals for diagnosing pathological status of an infant from cry signals.
Rachid Darnag
2017-02-01
Full Text Available Support vector machines (SVM represent one of the most promising Machine Learning (ML tools that can be applied to develop a predictive quantitative structure–activity relationship (QSAR models using molecular descriptors. Multiple linear regression (MLR and artificial neural networks (ANNs were also utilized to construct quantitative linear and non linear models to compare with the results obtained by SVM. The prediction results are in good agreement with the experimental value of HIV activity; also, the results reveal the superiority of the SVM over MLR and ANN model. The contribution of each descriptor to the structure–activity relationships was evaluated.
The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.
Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun
2017-01-01
Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.
Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei
2017-12-21
In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.
Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control
Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.
1997-01-01
One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.
Predictive inference for best linear combination of biomarkers subject to limits of detection.
Coolen-Maturi, Tahani
2017-08-15
Measuring the accuracy of diagnostic tests is crucial in many application areas including medicine, machine learning and credit scoring. The receiver operating characteristic (ROC) curve is a useful tool to assess the ability of a diagnostic test to discriminate between two classes or groups. In practice, multiple diagnostic tests or biomarkers are combined to improve diagnostic accuracy. Often, biomarker measurements are undetectable either below or above the so-called limits of detection (LoD). In this paper, nonparametric predictive inference (NPI) for best linear combination of two or more biomarkers subject to limits of detection is presented. NPI is a frequentist statistical method that is explicitly aimed at using few modelling assumptions, enabled through the use of lower and upper probabilities to quantify uncertainty. The NPI lower and upper bounds for the ROC curve subject to limits of detection are derived, where the objective function to maximize is the area under the ROC curve. In addition, the paper discusses the effect of restriction on the linear combination's coefficients on the analysis. Examples are provided to illustrate the proposed method. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
AUTHOR|(SzGeCERN)673023; Blanco Viñuela, Enrique
In each of eight arcs of the 27 km circumference Large Hadron Collider (LHC), 2.5 km long strings of super-conducting magnets are cooled with superfluid Helium II at 1.9 K. The temperature stabilisation is a challenging control problem due to complex non-linear dynamics of the magnets temperature and presence of multiple operational constraints. Strong nonlinearities and variable dead-times of the dynamics originate at strongly heat-flux dependent effective heat conductivity of superfluid that varies three orders of magnitude over the range of possible operational conditions. In order to improve the temperature stabilisation, a proof of concept on-line economic output-feedback Non-linear Model Predictive Controller (NMPC) is presented in this thesis. The controller is based on a novel complex first-principles distributed parameters numerical model of the temperature dynamics over a 214 m long sub-sector of the LHC that is characterized by very low computational cost of simulation needed in real-time optimizat...
Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders
2015-01-01
We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...
Yokoyama, Kenji; Ishikawa, Makoto
2000-04-01
The linear heat rates of the power-to-melt (PTM) tests, performed with B5D-1 and B5D-2 subassemblies on the Experimental Fast Reactor 'JOYO', are evaluated with the continuous energy Monte-Carlo code, MVP. We can apply a whole core model to MVP, but it takes very long time for the calculation. Therefore, judging from the structure of B5D subassembly, we used the MVP code to calculate the radial distribution of linear heat rate and used the deterministic method to calculate the axial distribution. We also derived the formulas for this method. Furthermore, we evaluated the error of the linear heat rate, by evaluating the experimental error of the reactor power, the statistical error of Monte-Carlo method, the calculational model error of the deterministic method and so on. On the other hand, we also evaluated the burnup rate of the B5D assembly and compared with the measured value in the post-irradiation test. The main results are following: B5D-1 (B5101, F613632, core center). Linear heat rate: 600 W/cm±2.2%. Burnup rate: 0.977. B5D-2 (B5214, G80124, core center). Linear heat rate: 641 W/cm±2.2%. Burnup rate: 0.886. (author)
Mamdani-Fuzzy Modeling Approach for Quality Prediction of Non-Linear Laser Lathing Process
Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.
2018-03-01
Lathing is a process to fashioning stock materials into desired cylindrical shapes which usually performed by traditional lathe machine. But, the recent rapid advancements in engineering materials and precision demand gives a great challenge to the traditional method. The main drawback of conventional lathe is its mechanical contact which brings to the undesirable tool wear, heat affected zone, finishing, and dimensional accuracy especially taper quality in machining of stock with high length to diameter ratio. Therefore, a novel approach has been devised to investigate in transforming a 2D flatbed CO2 laser cutting machine into 3D laser lathing capability as an alternative solution. Three significant design parameters were selected for this experiment, namely cutting speed, spinning speed, and depth of cut. Total of 24 experiments were performed with eight (8) sequential runs where they were then replicated three (3) times. The experimental results were then used to establish Mamdani - Fuzzy predictive model where it yields the accuracy of more than 95%. Thus, the proposed Mamdani - Fuzzy modelling approach is found very much suitable and practical for quality prediction of non-linear laser lathing process for cylindrical stocks of 10mm diameter.
Gertsch, R.; Ozdemir, L.
1992-09-01
The performances of mechanical excavators are predicted for excavations in welded tuff. Emphasis is given to tunnel boring machine evaluations based on linear cutting machine test data obtained on samples of Topopah Spring welded tuff. The tests involve measurement of forces as cutters are applied to the rock surface at certain spacing and penetrations. Two disc and two point-attack cutters representing currently available technology are thus evaluated. The performance predictions based on these direct experimental measurements are believed to be more accurate than any previous values for mechanical excavation of welded tuff. The calculations of performance are predicated on minimizing the amount of energy required to excavate the welded tuff. Specific energy decreases with increasing spacing and penetration, and reaches its lowest at the widest spacing and deepest penetration used in this test program. Using the force, spacing, and penetration data from this experimental program, the thrust, torque, power, and rate of penetration are calculated for several types of mechanical excavators. The results of this study show that the candidate excavators will require higher torque and power than heretofore estimated
Chaos and loss of predictability in the periodically kicked linear oscillator
Luna-Acosta, G.A.; Cantoral, E.
1989-01-01
Chernikov et.al. [2] have discovered new features in the dynamics of a periodically kicked LHO x'' + ω 0 2 x = ( K/ k 0 T 2 ) sin (k 0 x) x Σ n δ (t / T - n). They report that its phase space motion under exact resonance (p ω 0 = (2 π / T) q; p, q integers), and with initial conditions on the separatrix of the average Hamiltonian , accelerates unboundedly along a fractal stochastic web with q-fold symmetry. Here we investigate with numerical experiments the effects of small deviations from exact resonance on the diffusion and symmetry patterns. We show graphically that the stochastic webs are (topologically) unstable and thus the unbounded motion becomes considerably truncated. Moreover, we analyze numerically and analytically a simpler (integrable) version. We give its exact closed-form solution in complex numbers, realize that it accelerates unboundedly only when ω 0 = (2 π/T) q (q = ± 1,2,...), and show that for small uncertainties in these frequencies, total predictability is lost as time evolves. That is, trajectories of a set of systems, initially described by close neighboring points in phase space strongly diverge in a non-linear way. The great loss of predictability in the integrable model is due to the combination of translational and rotational symmetries, inherent in these systems. (Author)
TRM performance prediction in Yucca Mountain welded tuff from linear cutter tests
Gertsch, R.; Ozdemir, L.; Gertsch, L.
1992-01-01
Performance predictions were developed for tunnel boring machines operating in welded tuff for the construction of the experimental study facility and the potential nuclear waste repository at Yucca Mountain. The predictions were based on test data obtained from an extensive series of linear cutting tests performed on samples of Topopah Spring welded tuff from the Yucca Mountain Project site. Using the cutter force, spacing, and penetration data from the experimental program, the thrust, torque, power, and rate of penetration were estimated for a 25 ft diameter tunnel boring machine (TBM) operating in welded tuff. Guidelines were developed for the optimal design of the TBM cutterhead to achieve high production rates at the lowest possible excavation costs. The results show that the Topopah Spring welded tuff (TSw2) can be excavated at relatively high rates of advance with state-of-the-art TBMs. The results also show, however, that the TBM torque and power requirements will be higher than estimated based on rock physical properties and past tunneling experience in rock formations of similar strength
Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian
2018-05-12
Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.
Chaos and loss of predictability in the periodically kicked linear oscillator
Luna-Acosta, G A [Universidad Autonoma de Puebla (Mexico). Inst. de Ciencias; Cantoral, E [Universidad Autonoma de Puebla (Mexico). Escuela de Fisica
1989-01-01
Chernikov et.al. [2] have discovered new features in the dynamics of a periodically kicked LHO x'' + [omega] [sub 0] [sup 2] x = ( K/ k[sub 0] T [sup 2]) sin (k[sub 0] x) x [Sigma][sub n] [delta] (t / T - n). They report that its phase space motion under exact resonance (p [omega] [sub 0] = (2 [pi] / T) q; p, q integers), and with initial conditions on the separatrix of the average Hamiltonian , accelerates unboundedly along a fractal stochastic web with q-fold symmetry. Here we investigate with numerical experiments the effects of small deviations from exact resonance on the diffusion and symmetry patterns. We show graphically that the stochastic webs are (topologically) unstable and thus the unbounded motion becomes considerably truncated. Moreover, we analyze numerically and analytically a simpler (integrable) version. We give its exact closed-form solution in complex numbers, realize that it accelerates unboundedly only when [omega][sub 0] = (2 [pi]/T) q (q = [+-] 1,2,...), and show that for small uncertainties in these frequencies, total predictability is lost as time evolves. That is, trajectories of a set of systems, initially described by close neighboring points in phase space strongly diverge in a non-linear way. The great loss of predictability in the integrable model is due to the combination of translational and rotational symmetries, inherent in these systems. (Author).
Jeroen eStekelenburg
2012-05-01
Full Text Available In many natural audiovisual events (e.g., a clap of the two hands, the visual signal precedes the sound and thus allows observers to predict when, where, and which sound will occur. Previous studies have already reported that there are distinct neural correlates of temporal (when versus phonetic/semantic (which content on audiovisual integration. Here we examined the effect of visual prediction of auditory location (where in audiovisual biological motion stimuli by varying the spatial congruency between the auditory and visual part of the audiovisual stimulus. Visual stimuli were presented centrally, whereas auditory stimuli were presented either centrally or at 90° azimuth. Typical subadditive amplitude reductions (AV – V < A were found for the auditory N1 and P2 for spatially congruent and incongruent conditions. The new finding is that the N1 suppression was larger for spatially congruent stimuli. A very early audiovisual interaction was also found at 30-50 ms in the spatially congruent condition, while no effect of congruency was found on the suppression of the P2. This indicates that visual prediction of auditory location can be coded very early in auditory processing.
The Interaction between Interoceptive and Action States within a Framework of Predictive Coding
Marshall, Amanda C.; Gentsch, Antje; Schütz-Bosbach, Simone
2018-01-01
The notion of predictive coding assumes that perception is an iterative process between prior knowledge and sensory feedback. To date, this perspective has been primarily applied to exteroceptive perception as well as action and its associated phenomenological experiences such as agency. More recently, this predictive, inferential framework has been theoretically extended to interoception. This idea postulates that subjective feeling states are generated by top–down inferences made about internal and external causes of interoceptive afferents. While the processing of motor signals for action control and the emergence of selfhood have been studied extensively, the contributions of interoceptive input and especially the potential interaction of motor and interoceptive signals remain largely unaddressed. Here, we argue for a specific functional relation between motor and interoceptive awareness. Specifically, we implicate interoceptive predictions in the generation of subjective motor-related feeling states. Furthermore, we propose a distinction between reflexive and pre-reflexive modes of agentic action control and suggest that interoceptive input may affect each differently. Finally, we advocate the necessity of continuous interoceptive input for conscious forms of agentic action control. We conclude by discussing further research contributions that would allow for a fuller understanding of the interaction between agency and interoceptive awareness. PMID:29515495
Predicting stem borer density in maize using RapidEye data and generalized linear models
Abdel-Rahman, Elfatih M.; Landmann, Tobias; Kyalo, Richard; Ong'amo, George; Mwalusepo, Sizah; Sulieman, Saad; Ru, Bruno Le
2017-05-01
Average maize yield in eastern Africa is 2.03 t ha-1 as compared to global average of 6.06 t ha-1 due to biotic and abiotic constraints. Amongst the biotic production constraints in Africa, stem borers are the most injurious. In eastern Africa, maize yield losses due to stem borers are currently estimated between 12% and 21% of the total production. The objective of the present study was to explore the possibility of RapidEye spectral data to assess stem borer larva densities in maize fields in two study sites in Kenya. RapidEye images were acquired for the Bomet (western Kenya) test site on the 9th of December 2014 and on 27th of January 2015, and for Machakos (eastern Kenya) a RapidEye image was acquired on the 3rd of January 2015. Five RapidEye spectral bands as well as 30 spectral vegetation indices (SVIs) were utilized to predict per field maize stem borer larva densities using generalized linear models (GLMs), assuming Poisson ('Po') and negative binomial ('NB') distributions. Root mean square error (RMSE) and ratio prediction to deviation (RPD) statistics were used to assess the models performance using a leave-one-out cross-validation approach. The Zero-inflated NB ('ZINB') models outperformed the 'NB' models and stem borer larva densities could only be predicted during the mid growing season in December and early January in both study sites, respectively (RMSE = 0.69-1.06 and RPD = 8.25-19.57). Overall, all models performed similar when all the 30 SVIs (non-nested) and only the significant (nested) SVIs were used. The models developed could improve decision making regarding controlling maize stem borers within integrated pest management (IPM) interventions.
Wang, J; Wang, F; Liu, Y; Xu, J; Lin, H; Jia, B; Zuo, W; Jiang, Y; Hu, L; Lin, F
2016-01-01
Overweight individuals are at higher risk for developing type II diabetes than the general population. We conducted this study to analyze the correlation between blood glucose and biochemical parameters, and developed a blood glucose prediction model tailored to overweight patients. A total of 346 overweight Chinese people patients ages 18-81 years were involved in this study. Their levels of fasting glucose (fs-GLU), blood lipids, and hepatic and renal functions were measured and analyzed by multiple linear regression (MLR). Based the MLR results, we developed a back propagation artificial neural network (BP-ANN) model by selecting tansig as the transfer function of the hidden layers nodes, and purelin for the output layer nodes, with training goal of 0.5×10(-5). There was significant correlation between fs-GLU with age, BMI, and blood biochemical indexes (P<0.05). The results of MLR analysis indicated that age, fasting alanine transaminase (fs-ALT), blood urea nitrogen (fs-BUN), total protein (fs-TP), uric acid (fs-BUN), and BMI are 6 independent variables related to fs-GLU. Based on these parameters, the BP-ANN model was performed well and reached high prediction accuracy when training 1 000 epoch (R=0.9987). The level of fs-GLU was predictable using the proposed BP-ANN model based on 6 related parameters (age, fs-ALT, fs-BUN, fs-TP, fs-UA and BMI) in overweight patients. © Georg Thieme Verlag KG Stuttgart · New York.
Integrating genomics and proteomics data to predict drug effects using binary linear programming.
Ji, Zhiwei; Su, Jing; Liu, Chenglin; Wang, Hongyan; Huang, Deshuang; Zhou, Xiaobo
2014-01-01
The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be
Yakubu, A.; Oluremi, O. I. A.; Ekpo, E. I.
2018-03-01
There is an increasing use of robust analytical algorithms in the prediction of heat stress. The present investigation therefore, was carried out to forecast heat stress index (HSI) in Sasso laying hens. One hundred and sixty seven records on the thermo-physiological parameters of the birds were utilized. They were reared on deep litter and battery cage systems. Data were collected when the birds were 42- and 52-week of age. The independent variables fitted were housing system, age of birds, rectal temperature (RT), pulse rate (PR), and respiratory rate (RR). The response variable was HSI. Data were analyzed using automatic linear modeling (ALM) and artificial neural network (ANN) procedures. The ALM model building method involved Forward Stepwise using the F Statistic criterion. As regards ANN, multilayer perceptron (MLP) with back-propagation network was used. The ANN network was trained with 90% of the data set while 10% were dedicated to testing for model validation. RR and PR were the two parameters of utmost importance in the prediction of HSI. However, the fractional importance of RR was higher than that of PR in both ALM (0.947 versus 0.053) and ANN (0.677 versus 0.274) models. The two models also predicted HSI effectively with high degree of accuracy [r = 0.980, R 2 = 0.961, adjusted R 2 = 0.961, and RMSE = 0.05168 (ALM); r = 0.983, R 2 = 0.966; adjusted R 2 = 0.966, and RMSE = 0.04806 (ANN)]. The present information may be exploited in the development of a heat stress chart based largely on RR. This may aid detection of thermal discomfort in a poultry house under tropical and subtropical conditions.
Dual-Source Linear Energy Prediction (LINE-P) Model in the Context of WSNs.
Ahmed, Faisal; Tamberg, Gert; Le Moullec, Yannick; Annus, Paul
2017-07-20
Energy harvesting technologies such as miniature power solar panels and micro wind turbines are increasingly used to help power wireless sensor network nodes. However, a major drawback of energy harvesting is its varying and intermittent characteristic, which can negatively affect the quality of service. This calls for careful design and operation of the nodes, possibly by means of, e.g., dynamic duty cycling and/or dynamic frequency and voltage scaling. In this context, various energy prediction models have been proposed in the literature; however, they are typically compute-intensive or only suitable for a single type of energy source. In this paper, we propose Linear Energy Prediction "LINE-P", a lightweight, yet relatively accurate model based on approximation and sampling theory; LINE-P is suitable for dual-source energy harvesting. Simulations and comparisons against existing similar models have been conducted with low and medium resolutions (i.e., 60 and 22 min intervals/24 h) for the solar energy source (low variations) and with high resolutions (15 min intervals/24 h) for the wind energy source. The results show that the accuracy of the solar-based and wind-based predictions is up to approximately 98% and 96%, respectively, while requiring a lower complexity and memory than the other models. For the cases where LINE-P's accuracy is lower than that of other approaches, it still has the advantage of lower computing requirements, making it more suitable for embedded implementation, e.g., in wireless sensor network coordinator nodes or gateways.
Shandilya Sharad
2012-10-01
.6% and 60.9%, respectively. Conclusion We report the development and first-use of a nontraditional non-linear method of analyzing the VF ECG signal, yielding high predictive accuracies of defibrillation success. Furthermore, incorporation of features from the PetCO2 signal noticeably increased model robustness. These predictive capabilities should further improve with the availability of a larger database.
Positive predictive value of peptic ulcer diagnosis codes in the Danish National Patient Registry.
Viborg, Søren; Søgaard, Kirstine Kobberøe; Jepsen, Peter
2017-01-01
Diagnoses of peptic ulcer are registered in the Danish National Patient Registry (DNPR) for administrative as well as research purposes, but it is unknown whether the coding validity depends on the location of the ulcer. To validate the International Classification of Diseases, 10 th revision diagnosis codes of peptic ulcer in the DNPR by estimating positive predictive values (PPVs) for gastric and duodenal ulcer diagnoses. We identified all patients registered with a hospital discharge diagnosis of peptic ulcer from Aarhus University Hospital, Denmark, in 1995-2006. Among them, we randomly selected 200 who had an outpatient gastroscopy at the time of ulcer diagnosis. We reviewed the findings from these gastroscopies to confirm the presence of peptic ulcer and its location. We calculated PPVs and corresponding 95% confidence intervals (CIs) of gastric and duodenal ulcer diagnoses, using descriptions from the gastroscopic examinations as standard reference. In total, 182 records (91%) were available for review. The overall PPV of peptic ulcer diagnoses in DNPR was 95.6% (95% CI 91.5-98.1), with PPVs of 90.3% (95% CI 82.4-95.5) for gastric ulcer diagnoses, and 94.4% (95% CI 87.4-98.2) for duodenal ulcer diagnoses. PPVs were constant over time. The PPV of uncomplicated peptic ulcer diagnoses in the DNPR is high, and the location of the ulcers is registered correctly in most cases, indicating that the diagnoses are useful for research purposes.
Predicting holland occupational codes by means of paq job dimension scores
R. P. Van Der Merwe
1990-06-01
Full Text Available A study was conducted on how to obtain Holland's codes for South African occupations practically and economically by deducing them from information on the nature of the occupation (as derived by means of the Position Analysis Questionnaire. A discriminant analysis revealed that on the basis of the PAQ information the occupations could be distinguished clearly according to the main orientations of their American codes. Regression equations were also developed to predict the mean Self-Directed Search scores of the occupations on the basis of their PAQ information. Opsomming Ondersoek is ingestel om Holland se kodes vir Suid- Afrikaanse beroepe op 'n praktiese en ekonomiese wyse te bekom deur hulle van inligting oor die aard van die beroep (soos verkry met behulp van die Position Analysis Questionnaire af te lei. 'n Diskriminantontleding het getoon dat die beroepe op grond van die PAQ-inligting duidelik volgens die hoofberoepsgroepe van hulle Amerikaanse kodes onderskei kan word. Verder is regressievergelykings ontwikkel om beroepe se gemiddelde Self-Directed Search-tellings op grond van hulle PAQ-inligting te voorspel.
Predicting tritium movement and inventory in fusion reactor subsystems using the TMAP code
Jones, J.L.; Merrill, B.J.; Holland, D.F.
1985-01-01
The Fusion Safety Program of EG and G Idaho, Inc. at the Idaho National Engineering Laboratory (INEL) is developing a safety analysis code called TMAP (Tritium Migration Analysis Program) to analyze tritium loss from fusion systems during normal and off-normal conditions. TMAP is a one-dimensional code that calculated tritium movement and inventories in a system of interconnected enclosures and wall structures. These wall structures can include composite materials with bulk trapping of the permeating tritium on impurities or radiation induced dislocations within the material. The thermal response of a structure can be modeled to provide temperature information required for tritium movement calculations. Chemical reactions and hydrogen isotope movement can also be included in the calculations. TWAP was used to analyze the movement of tritium implanted into a proposed limiter/first wall structure design. This structure was composed of composite layers of vanadium and stainless steel. Included in these calculations was the effect of contrasting material tritium solubility at the composite interface. In addition, TMAP was used to investigate the rate of tritium cleanup after an accidental release into the atmosphere of a reactor building. Tritium retention and release from surfaces and conversion to the oxide form was predicted
Predictive Coding and Multisensory Integration: An Attentional Account of the Multisensory Mind
Durk eTalsma
2015-03-01
Full Text Available Multisensory integration involves a host of different cognitive processes, occurring at different stages of sensory processing. Here I argue that, despite recent insights suggesting that multisensory interactions can occur at very early latencies, the actual integration of individual sensory traces into an internally consistent mental representation is dependent on both top-down and bottom-up processes. Moreover, I argue that this integration is not limited to just sensory inputs, but that internal cognitive processes also shape the resulting mental representation. Studies showing that memory recall is affected by the initial multisensory context in which the stimuli were presented will be discussed, as well as several studies showing that mental imagery can affect multisensory illusions. This empirical evidence will be discussed from a predictive coding perspective, in which a central top-down attentional process is proposed to play a central role in coordinating the integration of all these inputs into a coherent mental representation.
Behaviors of impurity in ITER and DEMOs using BALDUR integrated predictive modeling code
Onjun, Thawatchai; Buangam, Wannapa; Wisitsorasak, Apiwat
2015-01-01
The behaviors of impurity are investigated using self-consistent modeling of 1.5D BALDUR integrated predictive modeling code, in which theory-based models are used for both core and edge region. In these simulations, a combination of NCLASS neoclassical transport and Multi-mode (MMM95) anomalous transport model is used to compute a core transport. The boundary is taken to be at the top of the pedestal, where the pedestal values are described using a theory-based pedestal model. This pedestal temperature model is based on a combination of magnetic and flow shear stabilization pedestal width scaling and an infinite-n ballooning pressure gradient model. The time evolution of plasma current, temperature and density profiles is carried out for ITER and DEMOs plasmas. As a result, the impurity behaviors such as impurity accumulation and impurity transport can be investigated. (author)
A 3D-CFD code for accurate prediction of fluid flows and fluid forces in seals
Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.
1994-01-01
Current and future turbomachinery requires advanced seal configurations to control leakage, inhibit mixing of incompatible fluids and to control the rotodynamic response. In recognition of a deficiency in the existing predictive methodology for seals, a seven year effort was established in 1990 by NASA's Office of Aeronautics Exploration and Technology, under the Earth-to-Orbit Propulsion program, to develop validated Computational Fluid Dynamics (CFD) concepts, codes and analyses for seals. The effort will provide NASA and the U.S. Aerospace Industry with advanced CFD scientific codes and industrial codes for analyzing and designing turbomachinery seals. An advanced 3D CFD cylindrical seal code has been developed, incorporating state-of-the-art computational methodology for flow analysis in straight, tapered and stepped seals. Relevant computational features of the code include: stationary/rotating coordinates, cylindrical and general Body Fitted Coordinates (BFC) systems, high order differencing schemes, colocated variable arrangement, advanced turbulence models, incompressible/compressible flows, and moving grids. This paper presents the current status of code development, code demonstration for predicting rotordynamic coefficients, numerical parametric study of entrance loss coefficients for generic annular seals, and plans for code extensions to labyrinth, damping, and other seal configurations.
Anaf, J.; Chalhoub, E.S.
1988-12-01
The NJOY and LINEAR/RECENT/GROUPIE calculational procedures for the resolved and unresolved resonance contributions and background cross sections are evaluated. Elastic scattering, fission and capture multigroup cross sections generated by these codes and the previously validated ETOG-3Q, ETOG-3, FLANGE-II and XLACS are compared. Constant weighting function and zero Kelvin temperature are considered. Discrepancies are presented and analysed. (author) [pt
Anaf, J.; Chalhoub, E.S.
1991-01-01
The NJOY and LINEAR/RECENT/GROUPIE calculational procedures for the resolved and unresolved resonance contributions and background cross sections are evaluated. Elastic scattering, fission and capture multigroup cross sections generated by these codes and the previously validated ETOG-3Q, ETOG-3, FLANGE-II and XLACS are compared. Constant weighting function and zero Kelvin temperature are considered. Discrepancies are presented and analyzed. (author)
Ferlaino, Michael; Rogers, Mark F; Shihab, Hashem A; Mort, Matthew; Cooper, David N; Gaunt, Tom R; Campbell, Colin
2017-10-06
Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome. We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome. Our method exploits various genomic annotations in addition to sequence data. When validated on benchmark data, FATHMM-indel significantly outperforms CADD and GAVIN, state of the art models in assessing the pathogenic impact of non-coding variants. FATHMM-indel is available via a web server at indels.biocompute.org.uk. FATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome.
Assessment of void fraction prediction using the RETRAN-3d and CORETRAN-01/VIPRE-02 codes
Aounallah, Y.; Coddington, P.; Gantner, U.
2000-01-01
A review of wide-range void fraction correlations against an extensive database has been undertaken to identify the correlations best suited for nuclear safety applications. Only those based on the drift-flux model have been considered. The survey confirmed the application range of the Chexal-Lellouche correlation, and the database was also used to obtain new parameters for the Inoue drift-flux correlation, which was also found suitable. A void fraction validation study has also been undertaken for the codes RETRAN-3D and CORETRAN-01/VIPRE-02 at the assembly and sub-assembly levels. The study showed the impact of the RETRAN-03 user options on the predicted void fraction, and the RETRAN-3D limitation at very low fluid velocity. At the sub-assembly level, CORETRAN-01/VIPRE-02 substantially underestimates the void in regions with low power-to-flow ratios. Otherwise, a generally good predictive performance was obtained with both RETRAN-3D and CORETRAN-01/VIPRE-02. (authors)
Assessment of void fraction prediction using the RETRAN-3d and CORETRAN-01/VIPRE-02 codes
Aounallah, Y.; Coddington, P.; Gantner, U
2000-07-01
A review of wide-range void fraction correlations against an extensive database has been undertaken to identify the correlations best suited for nuclear safety applications. Only those based on the drift-flux model have been considered. The survey confirmed the application range of the Chexal-Lellouche correlation, and the database was also used to obtain new parameters for the Inoue drift-flux correlation, which was also found suitable. A void fraction validation study has also been undertaken for the codes RETRAN-3D and CORETRAN-01/VIPRE-02 at the assembly and sub-assembly levels. The study showed the impact of the RETRAN-03 user options on the predicted void fraction, and the RETRAN-3D limitation at very low fluid velocity. At the sub-assembly level, CORETRAN-01/VIPRE-02 substantially underestimates the void in regions with low power-to-flow ratios. Otherwise, a generally good predictive performance was obtained with both RETRAN-3D and CORETRAN-01/VIPRE-02. (authors)
From structure prediction to genomic screens for novel non-coding RNAs.
Gorodkin, Jan; Hofacker, Ivo L
2011-08-01
Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.
Near-fault earthquake ground motion prediction by a high-performance spectral element numerical code
Paolucci, Roberto; Stupazzini, Marco
2008-01-01
Near-fault effects have been widely recognised to produce specific features of earthquake ground motion, that cannot be reliably predicted by 1D seismic wave propagation modelling, used as a standard in engineering applications. These features may have a relevant impact on the structural response, especially in the nonlinear range, that is hard to predict and to be put in a design format, due to the scarcity of significant earthquake records and of reliable numerical simulations. In this contribution a pilot study is presented for the evaluation of seismic ground-motions in the near-fault region, based on a high-performance numerical code for 3D seismic wave propagation analyses, including the seismic fault, the wave propagation path and the near-surface geological or topographical irregularity. For this purpose, the software package GeoELSE is adopted, based on the spectral element method. The set-up of the numerical benchmark of 3D ground motion simulation in the valley of Grenoble (French Alps) is chosen to study the effect of the complex interaction between basin geometry and radiation mechanism on the variability of earthquake ground motion
Xing, Yafei; Macq, Benoit
2017-11-01
With the emergence of clinical prototypes and first patient acquisitions for proton therapy, the research on prompt gamma imaging is aiming at making most use of the prompt gamma data for in vivo estimation of any shift from expected Bragg peak (BP). The simple problem of matching the measured prompt gamma profile of each pencil beam with a reference simulation from the treatment plan is actually made complex by uncertainties which can translate into distortions during treatment. We will illustrate this challenge and demonstrate the robustness of a predictive linear model we proposed for BP shift estimation based on principal component analysis (PCA) method. It considered the first clinical knife-edge slit camera design in use with anthropomorphic phantom CT data. Particularly, 4115 error scenarios were simulated for the learning model. PCA was applied to the training input randomly chosen from 500 scenarios for eliminating data collinearities. A total variance of 99.95% was used for representing the testing input from 3615 scenarios. This model improved the BP shift estimation by an average of 63+/-19% in a range between -2.5% and 86%, comparing to our previous profile shift (PS) method. The robustness of our method was demonstrated by a comparative study conducted by applying 1000 times Poisson noise to each profile. 67% cases obtained by the learning model had lower prediction errors than those obtained by PS method. The estimation accuracy ranged between 0.31 +/- 0.22 mm and 1.84 +/- 8.98 mm for the learning model, while for PS method it ranged between 0.3 +/- 0.25 mm and 20.71 +/- 8.38 mm.
Lin, Shu; Fossorier, Marc
1998-01-01
In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm.
Taleyarkhan, R.; Lahey, R.T. Jr.; McFarlane, A.F.; Podowski, M.Z.
1988-01-01
The NUFREQ-NPW code was modified and set up at Westinghouse, USA for mixed fuel type multi-channel core-wide stability analysis. The resulting code, NUFREQ-NPW, allows for variable axial power profiles between channel groups and can handle mixed fuel types. Various models incorporated into NUFREQ-NPW were systematically compared against the Westinghouse channel stability analysis code MAZDA-NF, for which the mathematical model was developed, in an entirely different manner. Excellent agreement was obtained which verified the thermal-hydraulic modeling and coding aspects. Detailed comparisons were also performed against nuclear-coupled reactor core stability data. All thirteen Peach Bottom-2 EOC-2/3 low flow stability tests were simulated. A key aspect for code qualification involved the development of a physically based empirical algorithm to correct for the effect of core inlet flow development on subcooled boiling. Various other modeling assumptions were tested and sensitivity studies performed. Good agreement was obtained between NUFREQ-NPW predictions and data. Moreover, predictions were generally on the conservative side. The results of detailed direct comparisons with experimental data using the NUFREQ-NPW code; have demonstrated that BWR core stability margins are conservatively predicted, and all data trends are captured with good accuracy. The methodology is thus suitable for BWR design and licensing purposes. 11 refs., 12 figs., 2 tabs
Wilkinson, Karl A; Hine, Nicholas D M; Skylaris, Chris-Kriton
2014-11-11
We present a hybrid MPI-OpenMP implementation of Linear-Scaling Density Functional Theory within the ONETEP code. We illustrate its performance on a range of high performance computing (HPC) platforms comprising shared-memory nodes with fast interconnect. Our work has focused on applying OpenMP parallelism to the routines which dominate the computational load, attempting where possible to parallelize different loops from those already parallelized within MPI. This includes 3D FFT box operations, sparse matrix algebra operations, calculation of integrals, and Ewald summation. While the underlying numerical methods are unchanged, these developments represent significant changes to the algorithms used within ONETEP to distribute the workload across CPU cores. The new hybrid code exhibits much-improved strong scaling relative to the MPI-only code and permits calculations with a much higher ratio of cores to atoms. These developments result in a significantly shorter time to solution than was possible using MPI alone and facilitate the application of the ONETEP code to systems larger than previously feasible. We illustrate this with benchmark calculations from an amyloid fibril trimer containing 41,907 atoms. We use the code to study the mechanism of delamination of cellulose nanofibrils when undergoing sonification, a process which is controlled by a large number of interactions that collectively determine the structural properties of the fibrils. Many energy evaluations were needed for these simulations, and as these systems comprise up to 21,276 atoms this would not have been feasible without the developments described here.
Vilches, M. [Servicio de Fisica y Proteccion Radiologica, Hospital Regional Universitario ' Virgen de las Nieves' , Avda. de las Fuerzas Armadas, 2, E-18014 Granada (Spain)], E-mail: mvilches@ugr.es; Garcia-Pareja, S. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' Carlos Haya' , Avda. Carlos Haya, s/n, E-29010 Malaga (Spain); Guerrero, R. [Servicio de Radiofisica, Hospital Universitario ' San Cecilio' , Avda. Dr. Oloriz, 16, E-18012 Granada (Spain); Anguiano, M.; Lallena, A.M. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)
2007-09-21
When a therapeutic electron linear accelerator is simulated using a Monte Carlo (MC) code, the tuning of the initial spectra and the renormalization of dose (e.g., to maximum axial dose) constitute a common practice. As a result, very similar depth dose curves are obtained for different MC codes. However, if renormalization is turned off, the results obtained with the various codes disagree noticeably. The aim of this work is to investigate in detail the reasons of this disagreement. We have found that the observed differences are due to non-negligible differences in the angular scattering of the electron beam in very thin slabs of dense material (primary foil) and thick slabs of very low density material (air). To gain insight, the effects of the angular scattering models considered in various MC codes on the dose distribution in a water phantom are discussed using very simple geometrical configurations for the LINAC. The MC codes PENELOPE 2003, PENELOPE 2005, GEANT4, GEANT3, EGSnrc and MCNPX have been used.
Vilches, M.; Garcia-Pareja, S.; Guerrero, R.; Anguiano, M.; Lallena, A.M.
2007-01-01
When a therapeutic electron linear accelerator is simulated using a Monte Carlo (MC) code, the tuning of the initial spectra and the renormalization of dose (e.g., to maximum axial dose) constitute a common practice. As a result, very similar depth dose curves are obtained for different MC codes. However, if renormalization is turned off, the results obtained with the various codes disagree noticeably. The aim of this work is to investigate in detail the reasons of this disagreement. We have found that the observed differences are due to non-negligible differences in the angular scattering of the electron beam in very thin slabs of dense material (primary foil) and thick slabs of very low density material (air). To gain insight, the effects of the angular scattering models considered in various MC codes on the dose distribution in a water phantom are discussed using very simple geometrical configurations for the LINAC. The MC codes PENELOPE 2003, PENELOPE 2005, GEANT4, GEANT3, EGSnrc and MCNPX have been used
Chen, K.F.; Olson, C.A.
1983-01-01
One reliable method that can be used to verify the solution scheme of a computer code is to compare the code prediction to a simplified problem for which an analytic solution can be derived. An analytic solution for the axial pressure drop as a function of the flow was obtained for the simplified problem of homogeneous equilibrium two-phase flow in a vertical, heated channel with a cosine axial heat flux shape. This analytic solution was then used to verify the predictions of the CONDOR computer code, which is used to evaluate the thermal-hydraulic performance of boiling water reactors. The results show excellent agreement between the analytic solution and CONDOR prediction
Beutler, D.E.; Halbleib, J.A.; Knott, D.P.
1989-01-01
This paper reports pulse-height distributions in two different types of Ge detectors measured for a variety of medium-energy x-ray bremsstrahlung spectra. These measurements have been compared to predictions using the integrated tiger series (ITS) Monte Carlo electron/photon transport code. In general, the authors find excellent agreement between experiments and predictions using no free parameters. These results demonstrate that the ITS codes can predict the combined bremsstrahlung production and energy deposition with good precision (within measurement uncertainties). The one region of disagreement observed occurs for low-energy (<50 keV) photons using low-energy bremsstrahlung spectra. In this case the ITS codes appear to underestimate the produced and/or absorbed radiation by almost an order of magnitude
Data Normalization to Accelerate Training for Linear Neural Net to Predict Tropical Cyclone Tracks
Jian Jin
2015-01-01
Full Text Available When pure linear neural network (PLNN is used to predict tropical cyclone tracks (TCTs in South China Sea, whether the data is normalized or not greatly affects the training process. In this paper, min.-max. method and normal distribution method, instead of standard normal distribution, are applied to TCT data before modeling. We propose the experimental schemes in which, with min.-max. method, the min.-max. value pair of each variable is mapped to (−1, 1 and (0, 1; with normal distribution method, each variable’s mean and standard deviation pair is set to (0, 1 and (100, 1. We present the following results: (1 data scaled to the similar intervals have similar effects, no matter the use of min.-max. or normal distribution method; (2 mapping data to around 0 gains much faster training speed than mapping them to the intervals far away from 0 or using unnormalized raw data, although all of them can approach the same lower level after certain steps from their training error curves. This could be useful to decide data normalization method when PLNN is used individually.
Wheel slip control with torque blending using linear and nonlinear model predictive control
Basrah, M. Sofian; Siampis, Efstathios; Velenis, Efstathios; Cao, Dongpu; Longo, Stefano
2017-11-01
Modern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.
A turbulent mixing Reynolds stress model fitted to match linear interaction analysis predictions
Griffond, J; Soulard, O; Souffland, D
2010-01-01
To predict the evolution of turbulent mixing zones developing in shock tube experiments with different gases, a turbulence model must be able to reliably evaluate the production due to the shock-turbulence interaction. In the limit of homogeneous weak turbulence, 'linear interaction analysis' (LIA) can be applied. This theory relies on Kovasznay's decomposition and allows the computation of waves transmitted or produced at the shock front. With assumptions about the composition of the upstream turbulent mixture, one can connect the second-order moments downstream from the shock front to those upstream through a transfer matrix, depending on shock strength. The purpose of this work is to provide a turbulence model that matches LIA results for the shock-turbulent mixture interaction. Reynolds stress models (RSMs) with additional equations for the density-velocity correlation and the density variance are considered here. The turbulent states upstream and downstream from the shock front calculated with these models can also be related through a transfer matrix, provided that the numerical implementation is based on a pseudo-pressure formulation. Then, the RSM should be modified in such a way that its transfer matrix matches the LIA one. Using the pseudo-pressure to introduce ad hoc production terms, we are able to obtain a close agreement between LIA and RSM matrices for any shock strength and thus improve the capabilities of the RSM.
Vullings, R; Sluijter, R J; Mischi, M; Bergmans, J W M; Peters, C H L; Oei, S G
2009-01-01
Monitoring the fetal heart rate (fHR) and fetal electrocardiogram (fECG) during pregnancy is important to support medical decision making. Before labor, the fHR is usually monitored using Doppler ultrasound. This method is inaccurate and therefore of limited clinical value. During labor, the fHR can be monitored more accurately using an invasive electrode; this method also enables monitoring of the fECG. Antenatally, the fECG and fHR can also be monitored using electrodes on the maternal abdomen. The signal-to-noise ratio of these recordings is, however, low, the maternal electrocardiogram (mECG) being the main interference. Existing techniques to remove the mECG from these non-invasive recordings are insufficiently accurate or do not provide all spatial information of the fECG. In this paper a new technique for mECG removal in antenatal abdominal recordings is presented. This technique operates by the linear prediction of each separate wave in the mECG. Its performance in mECG removal and fHR detection is evaluated by comparison with spatial filtering, adaptive filtering, template subtraction and independent component analysis techniques. The new technique outperforms the other techniques in both mECG removal and fHR detection (by more than 3%)
Vuust, Peter; Witek, Maria A. G.
2014-01-01
Musical rhythm, consisting of apparently abstract intervals of accented temporal events, has a remarkable capacity to move our minds and bodies. How does the cognitive system enable our experiences of rhythmically complex music? In this paper, we describe some common forms of rhythmic complexity in music and propose the theory of predictive coding (PC) as a framework for understanding how rhythm and rhythmic complexity are processed in the brain. We also consider why we feel so compelled by rhythmic tension in music. First, we consider theories of rhythm and meter perception, which provide hierarchical and computational approaches to modeling. Second, we present the theory of PC, which posits a hierarchical organization of brain responses reflecting fundamental, survival-related mechanisms associated with predicting future events. According to this theory, perception and learning is manifested through the brain’s Bayesian minimization of the error between the input to the brain and the brain’s prior expectations. Third, we develop a PC model of musical rhythm, in which rhythm perception is conceptualized as an interaction between what is heard (“rhythm”) and the brain’s anticipatory structuring of music (“meter”). Finally, we review empirical studies of the neural and behavioral effects of syncopation, polyrhythm and groove, and propose how these studies can be seen as special cases of the PC theory. We argue that musical rhythm exploits the brain’s general principles of prediction and propose that pleasure and desire for sensorimotor synchronization from musical rhythm may be a result of such mechanisms. PMID:25324813
Kim, T. W.; Park, G. H.
2014-12-01
Seasonal variation of aragonite saturation state (Ωarag) in the North Pacific Ocean (NPO) was investigated, using multiple linear regression (MLR) models produced from the PACIFICA (Pacific Ocean interior carbon) dataset. Data within depth ranges of 50-1200m were used to derive MLR models, and three parameters (potential temperature, nitrate, and apparent oxygen utilization (AOU)) were chosen as predictor variables because these parameters are associated with vertical mixing, DIC (dissolved inorganic carbon) removal and release which all affect Ωarag in water column directly or indirectly. The PACIFICA dataset was divided into 5° × 5° grids, and a MLR model was produced in each grid, giving total 145 independent MLR models over the NPO. Mean RMSE (root mean square error) and r2 (coefficient of determination) of all derived MLR models were approximately 0.09 and 0.96, respectively. Then the obtained MLR coefficients for each of predictor variables and an intercept were interpolated over the study area, thereby making possible to allocate MLR coefficients to data-sparse ocean regions. Predictability from the interpolated coefficients was evaluated using Hawaiian time-series data, and as a result mean residual between measured and predicted Ωarag values was approximately 0.08, which is less than the mean RMSE of our MLR models. The interpolated MLR coefficients were combined with seasonal climatology of World Ocean Atlas 2013 (1° × 1°) to produce seasonal Ωarag distributions over various depths. Large seasonal variability in Ωarag was manifested in the mid-latitude Western NPO (24-40°N, 130-180°E) and low-latitude Eastern NPO (0-12°N, 115-150°W). In the Western NPO, seasonal fluctuations of water column stratification appeared to be responsible for the seasonal variation in Ωarag (~ 0.5 at 50 m) because it closely followed temperature variations in a layer of 0-75 m. In contrast, remineralization of organic matter was the main cause for the seasonal
Simulation of transport in the ignited ITER with 1.5-D predictive code
Becker, G.
1995-01-01
The confinement in the bulk and scrape-off layer plasmas of the ITER EDA and CDA is investigated with special versions of the 1.5-D BALDUR predictive transport code for the case of peaked density profiles (C υ = 1.0). The code self-consistently computes 2-D equilibria and solves 1-D transport equations with empirical transport coefficients for the ohmic, L and ELMy H mode regimes. Self-sustained steady state thermonuclear burn is demonstrated for up to 500 s. It is shown to be compatible with the strong radiation losses for divertor heat load reduction caused by the seeded impurities iron, neon and argon. The corresponding global and local energy and particle transport are presented. The required radiation corrected energy confinement times of the EDA and CDA are found to be close to 4 s. In the reference cases, the steady state helium fraction is 7%. The fractions of iron, neon and argon needed for the prescribed radiative power loss are given. It is shown that high radiative losses from the confinement zone, mainly by bremsstrahlung, cannot be avoided. The radiation profiles of iron and argon are found to be the same, with two thirds of the total radiation being emitted from closed flux surfaces. Fuel dilution due to iron and argon is small. The neon radiation is more peripheral. But neon is found to cause high fuel dilution. The combined dilution effect by helium and neon conflicts with burn control, self-sustained burn and divertor power reduction. Raising the helium fraction above 10% leads to the same difficulties owing to fuel dilution. The high helium levels of the present EDA design are thus unacceptable. The bootstrap current has only a small impact on the current profile. The sawtooth dominated region is found to cover 35% of the plasma cross-section. Local stability analysis of ideal ballooning modes shows that the plasma is everywhere well below the stability limit. 23 refs, 34 figs, 3 tabs
Calabrese, R., E-mail: rolando.calabrese@enea.i [ENEA, Innovative Nuclear Reactors and Fuel Cycle Closure Division, via Martiri di Monte Sole 4, 40129 Bologna (Italy); Vettraino, F.; Artioli, C. [ENEA, Innovative Nuclear Reactors and Fuel Cycle Closure Division, via Martiri di Monte Sole 4, 40129 Bologna (Italy); Sobolev, V. [SCK.CEN, Belgian Nuclear Research Centre, Boeretang 200, B-2400 Mol (Belgium); Thetford, R. [Serco Technical and Assurance Services, 150 Harwell Business Centre, Didcot OX11 0QB (United Kingdom)
2010-06-15
. Presented results were used for testing newly-developed models installed in the TRANSURANUS code to deal with such innovative fuels and T91 steel cladding. Agreement among codes predictions was satisfactory for fuel and cladding temperatures, pellet-cladding gap and mechanical stresses.
A model for preemptive maintenance of medical linear accelerators—predictive maintenance
Able, Charles M.; Baydush, Alan H.; Nguyen, Callistus; Gersh, Jacob; Ndlovu, Alois; Rebo, Igor; Booth, Jeremy; Perez, Mario; Sintay, Benjamin; Munley, Michael T.
2016-01-01
Unscheduled accelerator downtime can negatively impact the quality of life of patients during their struggle against cancer. Currently digital data accumulated in the accelerator system is not being exploited in a systematic manner to assist in more efficient deployment of service engineering resources. The purpose of this study is to develop an effective process for detecting unexpected deviations in accelerator system operating parameters and/or performance that predicts component failure or system dysfunction and allows maintenance to be performed prior to the actuation of interlocks. The proposed predictive maintenance (PdM) model is as follows: 1) deliver a daily quality assurance (QA) treatment; 2) automatically transfer and interrogate the resulting log files; 3) once baselines are established, subject daily operating and performance values to statistical process control (SPC) analysis; 4) determine if any alarms have been triggered; and 5) alert facility and system service engineers. A robust volumetric modulated arc QA treatment is delivered to establish mean operating values and perform continuous sampling and monitoring using SPC methodology. Chart limits are calculated using a hybrid technique that includes the use of the standard SPC 3σ limits and an empirical factor based on the parameter/system specification. There are 7 accelerators currently under active surveillance. Currently 45 parameters plus each MLC leaf (120) are analyzed using Individual and Moving Range (I/MR) charts. The initial warning and alarm rule is as follows: warning (2 out of 3 consecutive values ≥ 2σ hybrid ) and alarm (2 out of 3 consecutive values or 3 out of 5 consecutive values ≥ 3σ hybrid ). A customized graphical user interface provides a means to review the SPC charts for each parameter and a visual color code to alert the reviewer of parameter status. Forty-five synthetic errors/changes were introduced to test the effectiveness of our initial chart limits. Forty
A model for preemptive maintenance of medical linear accelerators-predictive maintenance.
Able, Charles M; Baydush, Alan H; Nguyen, Callistus; Gersh, Jacob; Ndlovu, Alois; Rebo, Igor; Booth, Jeremy; Perez, Mario; Sintay, Benjamin; Munley, Michael T
2016-03-10
Unscheduled accelerator downtime can negatively impact the quality of life of patients during their struggle against cancer. Currently digital data accumulated in the accelerator system is not being exploited in a systematic manner to assist in more efficient deployment of service engineering resources. The purpose of this study is to develop an effective process for detecting unexpected deviations in accelerator system operating parameters and/or performance that predicts component failure or system dysfunction and allows maintenance to be performed prior to the actuation of interlocks. The proposed predictive maintenance (PdM) model is as follows: 1) deliver a daily quality assurance (QA) treatment; 2) automatically transfer and interrogate the resulting log files; 3) once baselines are established, subject daily operating and performance values to statistical process control (SPC) analysis; 4) determine if any alarms have been triggered; and 5) alert facility and system service engineers. A robust volumetric modulated arc QA treatment is delivered to establish mean operating values and perform continuous sampling and monitoring using SPC methodology. Chart limits are calculated using a hybrid technique that includes the use of the standard SPC 3σ limits and an empirical factor based on the parameter/system specification. There are 7 accelerators currently under active surveillance. Currently 45 parameters plus each MLC leaf (120) are analyzed using Individual and Moving Range (I/MR) charts. The initial warning and alarm rule is as follows: warning (2 out of 3 consecutive values ≥ 2σ hybrid) and alarm (2 out of 3 consecutive values or 3 out of 5 consecutive values ≥ 3σ hybrid). A customized graphical user interface provides a means to review the SPC charts for each parameter and a visual color code to alert the reviewer of parameter status. Forty-five synthetic errors/changes were introduced to test the effectiveness of our initial chart limits. Forty
Does the Holland Code Predict Job Satisfaction and Productivity in Clothing Factory Workers?
Heesacker, Martin; And Others
1988-01-01
Administered Self-Directed Search to sewing machine operators to determine Holland code, and assessed work productivity, job satisfaction, absenteeism, and insurance claims. Most workers were of the Social code. Social subjects were the most satisfied, Conventional and Realistic subjects next, and subjects of other codes less so. Productivity of…
Yock, Adam D.; Kudchadker, Rajat J.; Rao, Arvind; Dong, Lei; Beadle, Beth M.; Garden, Adam S.; Court, Laurence E.
2014-01-01
Purpose: The purpose of this work was to develop and evaluate the accuracy of several predictive models of variation in tumor volume throughout the course of radiation therapy. Methods: Nineteen patients with oropharyngeal cancers were imaged daily with CT-on-rails for image-guided alignment per an institutional protocol. The daily volumes of 35 tumors in these 19 patients were determined and used to generate (1) a linear model in which tumor volume changed at a constant rate, (2) a general linear model that utilized the power fit relationship between the daily and initial tumor volumes, and (3) a functional general linear model that identified and exploited the primary modes of variation between time series describing the changing tumor volumes. Primary and nodal tumor volumes were examined separately. The accuracy of these models in predicting daily tumor volumes were compared with those of static and linear reference models using leave-one-out cross-validation. Results: In predicting the daily volume of primary tumors, the general linear model and the functional general linear model were more accurate than the static reference model by 9.9% (range: −11.6%–23.8%) and 14.6% (range: −7.3%–27.5%), respectively, and were more accurate than the linear reference model by 14.2% (range: −6.8%–40.3%) and 13.1% (range: −1.5%–52.5%), respectively. In predicting the daily volume of nodal tumors, only the 14.4% (range: −11.1%–20.5%) improvement in accuracy of the functional general linear model compared to the static reference model was statistically significant. Conclusions: A general linear model and a functional general linear model trained on data from a small population of patients can predict the primary tumor volume throughout the course of radiation therapy with greater accuracy than standard reference models. These more accurate models may increase the prognostic value of information about the tumor garnered from pretreatment computed tomography
Dattoli, G.; Schiavi, A.; Migliorati, M.
2006-03-01
The coherent synchrotron radiation (CSR) is one of the main problems limiting the performance of high intensity electron accelerators. The complexity of the physical mechanisms underlying the onset of instabilities due to CSR demands for accurate descriptions, capable of including the large number of features of an actual accelerating device. A code devoted to the analysis of this type of problems should be fast and reliable, conditions that are usually hardly achieved at the same rime. In the past, codes based on Lie algebraic techniques , have been very efficient to treat transport problems in accelerators. The extension of these methods to the non-linear case is ideally suited to treat CSR instability problems. We report on the development of a numerical code, based on the solution of the Vlasov equation, with the inclusion of non-linear contribution due to wake field effects. The proposed solution method exploits an algebraic technique, using exponential operators. We show that the integration procedure is capable of reproducing the onset of an instability and the effects associated with bunching mechanisms leading to the growth of the instability itself. In addition, considerations on the threshold of the instability are also developed [it
Dattoli, G.; Migliorati, M.; Schiavi, A.
2007-01-01
The coherent synchrotron radiation (CSR) is one of the main problems limiting the performance of high-intensity electron accelerators. The complexity of the physical mechanisms underlying the onset of instabilities due to CSR demands for accurate descriptions, capable of including the large number of features of an actual accelerating device. A code devoted to the analysis of these types of problems should be fast and reliable, conditions that are usually hardly achieved at the same time. In the past, codes based on Lie algebraic techniques have been very efficient to treat transport problems in accelerators. The extension of these methods to the non-linear case is ideally suited to treat CSR instability problems. We report on the development of a numerical code, based on the solution of the Vlasov equation, with the inclusion of non-linear contribution due to wake field effects. The proposed solution method exploits an algebraic technique that uses the exponential operators. We show that the integration procedure is capable of reproducing the onset of instability and the effects associated with bunching mechanisms leading to the growth of the instability itself. In addition, considerations on the threshold of the instability are also developed
Marchese Robinson, Richard L; Palczewska, Anna; Palczewski, Jan; Kidley, Nathan
2017-08-28
The ability to interpret the predictions made by quantitative structure-activity relationships (QSARs) offers a number of advantages. While QSARs built using nonlinear modeling approaches, such as the popular Random Forest algorithm, might sometimes be more predictive than those built using linear modeling approaches, their predictions have been perceived as difficult to interpret. However, a growing number of approaches have been proposed for interpreting nonlinear QSAR models in general and Random Forest in particular. In the current work, we compare the performance of Random Forest to those of two widely used linear modeling approaches: linear Support Vector Machines (SVMs) (or Support Vector Regression (SVR)) and partial least-squares (PLS). We compare their performance in terms of their predictivity as well as the chemical interpretability of the predictions using novel scoring schemes for assessing heat map images of substructural contributions. We critically assess different approaches for interpreting Random Forest models as well as for obtaining predictions from the forest. We assess the models on a large number of widely employed public-domain benchmark data sets corresponding to regression and binary classification problems of relevance to hit identification and toxicology. We conclude that Random Forest typically yields comparable or possibly better predictive performance than the linear modeling approaches and that its predictions may also be interpreted in a chemically and biologically meaningful way. In contrast to earlier work looking at interpretation of nonlinear QSAR models, we directly compare two methodologically distinct approaches for interpreting Random Forest models. The approaches for interpreting Random Forest assessed in our article were implemented using open-source programs that we have made available to the community. These programs are the rfFC package ( https://r-forge.r-project.org/R/?group_id=1725 ) for the R statistical
Cardoso, F F; Tempelman, R J
2012-07-01
The objectives of this work were to assess alternative linear reaction norm (RN) models for genetic evaluation of Angus cattle in Brazil. That is, we investigated the interaction between genotypes and continuous descriptors of the environmental variation to examine evidence of genotype by environment interaction (G×E) in post-weaning BW gain (PWG) and to compare the environmental sensitivity of national and imported Angus sires. Data were collected by the Brazilian Angus Improvement Program from 1974 to 2005 and consisted of 63,098 records and a pedigree file with 95,896 animals. Six models were implemented using Bayesian inference and compared using the Deviance Information Criterion (DIC). The simplest model was M(1), a traditional animal model, which showed the largest DIC and hence the poorest fit when compared with the 4 alternative RN specifications accounting for G×E. In M(2), a 2-step procedure was implemented using the contemporary group posterior means of M(1) as the environmental gradient, ranging from -92.6 to +265.5 kg. Moreover, the benefits of jointly estimating all parameters in a 1-step approach were demonstrated by M(3). Additionally, we extended M(3) to allow for residual heteroskedasticity using an exponential function (M(4)) and the best fitting (smallest DIC) environmental classification model (M(5)) specification. Finally, M(6) added just heteroskedastic residual variance to M(1). Heritabilities were less at harsh environments and increased with the improvement of production conditions for all RN models. Rank correlations among genetic merit predictions obtained by M(1) and by the best fitting RN models M(3) (homoskedastic) and M(5) (heteroskedastic) at different environmental levels ranged from 0.79 and 0.81, suggesting biological importance of G×E in Brazilian Angus PWG. These results suggest that selection progress could be optimized by adopting environment-specific genetic merit predictions. The PWG environmental sensitivity of
From structure prediction to genomic screens for novel non-coding RNAs.
Jan Gorodkin
2011-08-01
Full Text Available Non-coding RNAs (ncRNAs are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs. A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.
Performance prediction of gas turbines by solving a system of non-linear equations
Kaikko, J
1998-09-01
This study presents a novel method for implementing the performance prediction of gas turbines from the component models. It is based on solving the non-linear set of equations that corresponds to the process equations, and the mass and energy balances for the engine. General models have been presented for determining the steady state operation of single components. Single and multiple shad arrangements have been examined with consideration also being given to heat regeneration and intercooling. Emphasis has been placed upon axial gas turbines of an industrial scale. Applying the models requires no information of the structural dimensions of the gas turbines. On comparison with the commonly applied component matching procedures, this method incorporates several advantages. The application of the models for providing results is facilitated as less attention needs to be paid to calculation sequences and routines. Solving the set of equations is based on zeroing co-ordinate functions that are directly derived from the modelling equations. Therefore, controlling the accuracy of the results is easy. This method gives more freedom for the selection of the modelling parameters since, unlike for the matching procedures, exchanging these criteria does not itself affect the algorithms. Implicit relationships between the variables are of no significance, thus increasing the freedom for the modelling equations as well. The mathematical models developed in this thesis will provide facilities to optimise the operation of any major gas turbine configuration with respect to the desired process parameters. The computational methods used in this study may also be adapted to any other modelling problems arising in industry. (orig.) 36 refs.
Ensemble prediction of floods – catchment non-linearity and forecast probabilities
C. Reszler
2007-07-01
Full Text Available Quantifying the uncertainty of flood forecasts by ensemble methods is becoming increasingly important for operational purposes. The aim of this paper is to examine how the ensemble distribution of precipitation forecasts propagates in the catchment system, and to interpret the flood forecast probabilities relative to the forecast errors. We use the 622 km2 Kamp catchment in Austria as an example where a comprehensive data set, including a 500 yr and a 1000 yr flood, is available. A spatially-distributed continuous rainfall-runoff model is used along with ensemble and deterministic precipitation forecasts that combine rain gauge data, radar data and the forecast fields of the ALADIN and ECMWF numerical weather prediction models. The analyses indicate that, for long lead times, the variability of the precipitation ensemble is amplified as it propagates through the catchment system as a result of non-linear catchment response. In contrast, for lead times shorter than the catchment lag time (e.g. 12 h and less, the variability of the precipitation ensemble is decreased as the forecasts are mainly controlled by observed upstream runoff and observed precipitation. Assuming that all ensemble members are equally likely, the statistical analyses for five flood events at the Kamp showed that the ensemble spread of the flood forecasts is always narrower than the distribution of the forecast errors. This is because the ensemble forecasts focus on the uncertainty in forecast precipitation as the dominant source of uncertainty, and other sources of uncertainty are not accounted for. However, a number of analyses, including Relative Operating Characteristic diagrams, indicate that the ensemble spread is a useful indicator to assess potential forecast errors for lead times larger than 12 h.
A Study of Performance in Low-Power Tokamak Reactor with Integrated Predictive Modeling Code
Pianroj, Y.; Onjun, T.; Suwanna, S.; Picha, R.; Poolyarat, N.
2009-07-01
Full text: A fusion hybrid or a small fusion power output with low power tokamak reactor is presented as another useful application of nuclear fusion. Such tokamak can be used for fuel breeding, high-level waste transmutation, hydrogen production at high temperature, and testing of nuclear fusion technology components. In this work, an investigation of the plasma performance in a small fusion power output design is carried out using the BALDUR predictive integrated modeling code. The simulations of the plasma performance in this design are carried out using the empirical-based Mixed Bohm/gyro Bohm (B/gB) model, whereas the pedestal temperature model is based on magnetic and flow shear (δ α ρ ζ 2 ) stabilization pedestal width scaling. The preliminary results using this core transport model show that the central ion and electron temperatures are rather pessimistic. To improve the performance, the optimization approach are carried out by varying some parameters, such as plasma current and power auxiliary heating, which results in some improvement of plasma performance
A General Linear Model (GLM) was used to evaluate the deviation of predicted values from expected values for a complex environmental model. For this demonstration, we used the default level interface of the Regional Mercury Cycling Model (R-MCM) to simulate epilimnetic total mer...
Wittek, Adam; Joldes, Grand; Couton, Mathieu; Warfield, Simon K; Miller, Karol
2010-12-01
Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer. Copyright © 2010 Elsevier Ltd. All rights reserved.
Gautier, B.; Raybaud, A.
1984-01-01
The French PWR reactors are now currently operating under load follow and frequency control. In order to demonstrate that these operating conditions were not able to increase the fuel failure rate, fuel rod behaviour calculations have been performed by E.D.F. with CYRANO 2 code. In parallel with these theoretical calculations, code predictions have been compared to experimental results. The paper presents some of the comparisons performed on 17x17 fuel irradiated in FESSENHEIM 2 up to 30 GWd/tU under base load operation and in the CAP reactor under load follow and frequency control conditions. It is shown that experimental results can be predicted with a reasonable accuracy by CYRANO 2 code. The experimental work was carried out under joint R and D programs by EDF, FRAGEMA, CEA, and WESTINGHOUSE (CAP program by French partners only). (author)
Espinosa P, G.; Estrada P, C.E.; Nunez C, A.; Amador G, R.
2001-01-01
The computer code ANESLI-1 developed by the CNSNS and UAM-I, has the main goal of making stability analysis of nuclear reactors of the BWR type, more specifically, the reactors of the U1 and U2 of the CNLV. However it can be used for another kind of applications. Its capacity of real time simulator, allows the prediction of operational transients, and conditions of dynamic steady states. ANESLI-1 was developed under a modular scheme, which allows to extend or/and to improve its scope. The lineal stability analysis predicts the instabilities produced by the wave density phenomenon. (Author)
Efficient Implementation of Solvers for Linear Model Predictive Control on Embedded Devices
Frison, Gianluca; Kwame Minde Kufoalor, D.; Imsland, Lars
2014-01-01
This paper proposes a novel approach for the efficient implementation of solvers for linear MPC on embedded devices. The main focus is to explain in detail the approach used to optimize the linear algebra for selected low-power embedded devices, and to show how the high-performance implementation...
Linear regressive model structures for estimation and prediction of compartmental diffusive systems
Vries, D; Keesman, K.J.; Zwart, Heiko J.
In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state space
Linear regressive model structures for estimation and prediction of compartmental diffusive systems
Vries, D.; Keesman, K.J.; Zwart, H.
2006-01-01
Abstract In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state
Aspinall, J.
1982-01-01
A computational method was developed which alleviates the need for lengthy parametric scans as part of a design process. The method makes use of a least squares algorithm to find the optimal value of a parameter vector. Optimal is defined in terms of a utility function prescribed by the user. The placement of the vertical field coils of a torsatron is such a non linear problem
Prediction of failures in linear systems with the use of tolerance ranges
Gadzhiev, Ch.M.
1993-01-01
The problem of predicting the technical state of an object can be stated in a general case as that of predicting potential failures on the basis of a quantitative evaluation of the predicted parameters in relation to the set of tolerances on these parameters. The main stages in the prediction are collecting and preparing source data on the prehistory of the predicted phenomenon, forming a mathematical model of this phenomenon, working out the algorithm for the prediction, and adopting a solution from the prediction results. The final two stages of prediction are considered in this article. The prediction algorithm is proposed based on construction of the tolerance range for the signal of error between output coordinates of the system and its mathematical model. A solution regarding possible occurrence of failure in the system is formulated as a result of comparison of the tolerance range and the found confidence interval. 5 refs
Choi, Ui-Min; Ma, Ke; Blaabjerg, Frede
2018-01-01
In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime ...... prediction of IGBT modules under power converter applications.......In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime...... model in respect to junction temperature swing duration. This model has been built based on 39 power cycling test results of 600-V 30-A three-phase-molded IGBT modules. Six tests are performed under three superimposed power cycling conditions using an advanced power cycling test setup. The experimental...
RELAP5/MOD2 code modifications to obtain better predictions for the once-through steam generator
Blanchat, T.; Hassan, Y.
1989-01-01
The steam generator is a major component in pressurized water reactors. Predicting the response of a steam generator during both steady-state and transient conditions is essential in studying the thermal-hydraulic behavior of a nuclear reactor coolant system. Therefore, many analytical and experimental efforts have been performed to investigate the thermal-hydraulic behavior of the steam generators during operational and accident transients. The objective of this study is to predict the behavior of the secondary side of the once-through steam generator (OTSG) using the RELAP5/MOD2 computer code. Steady-state conditions were predicted with the current version of the RELAP5/MOD2 code and compared with experimental plant data. The code predictions consistently underpredict the degree of superheat. A new interface friction model has been implemented in a modified version of RELAP5/MOD2. This modification, along with changes to the flow regime transition criteria and the heat transfer correlations, correctly predicts the degree of superheat and matches plant data
Agostinetti, P.; Palma, M. Dalla; Fantini, F.; Fellin, F.; Pasqualotto, R.
2011-01-01
The analytical interpretative models for calorimetric measurements currently available in the literature can consider close systems in steady-state and transient conditions, or open systems but only in steady-state conditions. The PCCE code (Predictive Code for Calorimetric Estimations), here presented, introduces some novelties. In fact, it can simulate with an analytical approach both the heated component and the cooling circuit, evaluating the heat fluxes due to conductive and convective processes both in steady-state and transient conditions. The main goal of this code is to model heating and cooling processes in actively cooled components of fusion experiments affected by high pulsed power loads, that are not easily analyzed with purely numerical approaches (like Finite Element Method or Computational Fluid Dynamics). A dedicated mathematical formulation, based on concentrated parameters, has been developed and is here described in detail. After a comparison and benchmark with the ANSYS commercial code, the PCCE code is applied to predict the calorimetric parameters in simple scenarios of the SPIDER experiment.
Multi codes and multi-scale analysis for void fraction prediction in hot channel for VVER-1000/V392
Hoang Minh Giang; Hoang Tan Hung; Nguyen Huu Tiep
2015-01-01
Recently, an approach of multi codes and multi-scale analysis is widely applied to study core thermal hydraulic behavior such as void fraction prediction. Better results are achieved by using multi codes or coupling codes such as PARCS and RELAP5. The advantage of multi-scale analysis is zooming of the interested part in the simulated domain for detail investigation. Therefore, in this study, the multi codes between MCNP5, RELAP5, CTF and also the multi-scale analysis based RELAP5 and CTF are applied to investigate void fraction in hot channel of VVER-1000/V392 reactor. Since VVER-1000/V392 reactor is a typical advanced reactor that can be considered as the base to develop later VVER-1200 reactor, then understanding core behavior in transient conditions is necessary in order to investigate VVER technology. It is shown that the item of near wall boiling, Γ w in RELAP5 proposed by Lahey mechanistic method may not give enough accuracy of void fraction prediction as smaller scale code as CTF. (author)
Augmented chaos-multiple linear regression approach for prediction of wave parameters
M.A. Ghorbani
2017-06-01
The inter-comparisons demonstrated that the Chaos-MLR and pure MLR models yield almost the same accuracy in predicting the significant wave heights and the zero-up-crossing wave periods. Whereas, the augmented Chaos-MLR model is performed better results in term of the prediction accuracy vis-a-vis the previous prediction applications of the same case study.
McDowell, J J; Wood, H M
1984-03-01
Eight human subjects pressed a lever on a range of variable-interval schedules for 0.25 cent to 35.0 cent per reinforcement. Herrnstein's hyperbola described seven of the eight subjects' response-rate data well. For all subjects, the y-asymptote of the hyperbola increased with increasing reinforcer magnitude and its reciprocal was a linear function of the reciprocal of reinforcer magnitude. These results confirm predictions made by linear system theory; they contradict formal properties of Herrnstein's account and of six other mathematical accounts of single-alternative responding.
Kim, J. Y.; Shin, C. H.; Kim, J. K.; Lee, J. K.; Park, Y. J.
2003-01-01
The variation transitions of the inventories for the liquid radwaste system and the radioactive gas have being released in containment, and their predictive values according to the operation histories of Yonggwang(YGN) 3 and 4 were analyzed by linear regression analysis methodology. The results show that the variation transitions of the inventories for those systems are linearly increasing according to the operation histories but the inventories released to the environment are considerably lower than the recommended values based on the FSAR suggestions. It is considered that some conservation were presented in the estimation methodology in preparing stage of FSAR
Zhang, Hua; Kurgan, Lukasz
2014-12-01
Knowledge of protein flexibility is vital for deciphering the corresponding functional mechanisms. This knowledge would help, for instance, in improving computational drug design and refinement in homology-based modeling. We propose a new predictor of the residue flexibility, which is expressed by B-factors, from protein chains that use local (in the chain) predicted (or native) relative solvent accessibility (RSA) and custom-derived amino acid (AA) alphabets. Our predictor is implemented as a two-stage linear regression model that uses RSA-based space in a local sequence window in the first stage and a reduced AA pair-based space in the second stage as the inputs. This method is easy to comprehend explicit linear form in both stages. Particle swarm optimization was used to find an optimal reduced AA alphabet to simplify the input space and improve the prediction performance. The average correlation coefficients between the native and predicted B-factors measured on a large benchmark dataset are improved from 0.65 to 0.67 when using the native RSA values and from 0.55 to 0.57 when using the predicted RSA values. Blind tests that were performed on two independent datasets show consistent improvements in the average correlation coefficients by a modest value of 0.02 for both native and predicted RSA-based predictions.
Jahandideh, Sepideh; Jahandideh, Samad; Asadabadi, Ebrahim Barzegari; Askarian, Mehrdad; Movahedi, Mohammad Mehdi; Hosseini, Somayyeh; Jahandideh, Mina
2009-01-01
Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R 2 were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R 2 confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.
Akimoto, Hajime; Ohnuki, Akira; Murao, Yoshio
1994-03-01
The REFLA/TRAC code is a best estimate code developed at Japan Atomic Energy Research Institute (JAERI) to provide advanced predictions of thermal hydraulic transient in light water reactors (LWRs). The REFLA/TRAC code uses the TRAC-PF1/MOD1 code as the framework of the code. The REFLA/TRAC code is expected to be used for the calibration of licensing codes, accident analysis, accident simulation of LWRs, and design of advanced LWRs. Several models have been implemented to the TRAC-PF1/MOD1 code at JAERI including reflood model, condensation model, interfacial and wall friction models, etc. These models have been verified using data from various separate effect tests. This report describes an assessment result of the REFLA/TRAC code, which was performed to assess the predictive capability for integral system behavior under large break loss of coolant accident (LBLOCA) using data from the LOFT L2-5 test. The assessment calculation confirmed that the REFLA/TRAC code can predict break mass flow rate, emergency core cooling water bypass and clad temperature excellently in the LOFT L2-5 test. The CPU time of the REFLA/TRAC code was about 1/3 of the TRAC-PF1/MOD1 code. The REFLA/TRAC code can perform stable and fast simulation of thermal hydraulic behavior in PWR LBLOCA with enough accuracy for practical use. (author)
Stull, Christopher J.; Williams, Brian J.; Unal, Cetin
2012-01-01
This report considers the problem of calibrating a numerical model to data from an experimental campaign (or series of experimental tests). The issue is that when an experimental campaign is proposed, only the input parameters associated with each experiment are known (i.e. outputs are not known because the experiments have yet to be conducted). Faced with such a situation, it would be beneficial from the standpoint of resource management to carefully consider the sequence in which the experiments are conducted. In this way, the resources available for experimental tests may be allocated in a way that best 'informs' the calibration of the numerical model. To address this concern, the authors propose decomposing the input design space of the experimental campaign into its principal components. Subsequently, the utility (to be explained) of each experimental test to the principal components of the input design space is used to formulate the sequence in which the experimental tests will be used for model calibration purposes. The results reported herein build on those presented and discussed in (1,2) wherein Verification and Validation and Uncertainty Quantification (VU) capabilities were applied to the nuclear fuel performance code LIFEIV. In addition to the raw results from the sequential calibration studies derived from the above, a description of the data within the context of the Predictive Maturity Index (PMI) will also be provided. The PMI (3,4) is a metric initiated and developed at Los Alamos National Laboratory to quantitatively describe the ability of a numerical model to make predictions in the absence of experimental data, where it is noted that 'predictions in the absence of experimental data' is not synonymous with extrapolation. This simply reflects the fact that resources do not exist such that each and every execution of the numerical model can be compared against experimental data. If such resources existed, the justification for numerical models
Conti, Caroline; Nunes, Paulo; Ducla Soares, Luís.
2013-09-01
Holoscopic imaging, also known as integral imaging, has been recently attracting the attention of the research community, as a promising glassless 3D technology due to its ability to create a more realistic depth illusion than the current stereoscopic or multiview solutions. However, in order to gradually introduce this technology into the consumer market and to efficiently deliver 3D holoscopic content to end-users, backward compatibility with legacy displays is essential. Consequently, to enable 3D holoscopic content to be delivered and presented on legacy displays, a display scalable 3D holoscopic coding approach is required. Hence, this paper presents a display scalable architecture for 3D holoscopic video coding with a three-layer approach, where each layer represents a different level of display scalability: Layer 0 - a single 2D view; Layer 1 - 3D stereo or multiview; and Layer 2 - the full 3D holoscopic content. In this context, a prediction method is proposed, which combines inter-layer prediction, aiming to exploit the existing redundancy between the multiview and the 3D holoscopic layers, with self-similarity compensated prediction (previously proposed by the authors for non-scalable 3D holoscopic video coding), aiming to exploit the spatial redundancy inherent to the 3D holoscopic enhancement layer. Experimental results show that the proposed combined prediction can improve significantly the rate-distortion performance of scalable 3D holoscopic video coding with respect to the authors' previously proposed solutions, where only inter-layer or only self-similarity prediction is used.
Hogendoorn, Hinze; Burkitt, Anthony N
2018-05-01
Due to the delays inherent in neuronal transmission, our awareness of sensory events necessarily lags behind the occurrence of those events in the world. If the visual system did not compensate for these delays, we would consistently mislocalize moving objects behind their actual position. Anticipatory mechanisms that might compensate for these delays have been reported in animals, and such mechanisms have also been hypothesized to underlie perceptual effects in humans such as the Flash-Lag Effect. However, to date no direct physiological evidence for anticipatory mechanisms has been found in humans. Here, we apply multivariate pattern classification to time-resolved EEG data to investigate anticipatory coding of object position in humans. By comparing the time-course of neural position representation for objects in both random and predictable apparent motion, we isolated anticipatory mechanisms that could compensate for neural delays when motion trajectories were predictable. As well as revealing an early neural position representation (lag 80-90 ms) that was unaffected by the predictability of the object's trajectory, we demonstrate a second neural position representation at 140-150 ms that was distinct from the first, and that was pre-activated ahead of the moving object when it moved on a predictable trajectory. The latency advantage for predictable motion was approximately 16 ± 2 ms. To our knowledge, this provides the first direct experimental neurophysiological evidence of anticipatory coding in human vision, revealing the time-course of predictive mechanisms without using a spatial proxy for time. The results are numerically consistent with earlier animal work, and suggest that current models of spatial predictive coding in visual cortex can be effectively extended into the temporal domain. Copyright © 2018 Elsevier Inc. All rights reserved.
Li, Hongjian; Leung, Kwong-Sak; Wong, Man-Hon; Ballester, Pedro J
2014-08-27
State-of-the-art protein-ligand docking methods are generally limited by the traditionally low accuracy of their scoring functions, which are used to predict binding affinity and thus vital for discriminating between active and inactive compounds. Despite intensive research over the years, classical scoring functions have reached a plateau in their predictive performance. These assume a predetermined additive functional form for some sophisticated numerical features, and use standard multivariate linear regression (MLR) on experimental data to derive the coefficients. In this study we show that such a simple functional form is detrimental for the prediction performance of a scoring function, and replacing linear regression by machine learning techniques like random forest (RF) can improve prediction performance. We investigate the conditions of applying RF under various contexts and find that given sufficient training samples RF manages to comprehensively capture the non-linearity between structural features and measured binding affinities. Incorporating more structural features and training with more samples can both boost RF performance. In addition, we analyze the importance of structural features to binding affinity prediction using the RF variable importance tool. Lastly, we use Cyscore, a top performing empirical scoring function, as a baseline for comparison study. Machine-learning scoring functions are fundamentally different from classical scoring functions because the former circumvents the fixed functional form relating structural features with binding affinities. RF, but not MLR, can effectively exploit more structural features and more training samples, leading to higher prediction performance. The future availability of more X-ray crystal structures will further widen the performance gap between RF-based and MLR-based scoring functions. This further stresses the importance of substituting RF for MLR in scoring function development.
Tye, P.; Teyssedou, A.; Troche, N.; Kiteley, J.
1996-01-01
One of the factors which is important in order to ensure the continued safe operation of nuclear reactors is the ability to accurately predict the 'Critical Heat Flux' (CHF) throughout the rod bundles in the fuel channel. One method currently used by the Canadian nuclear industry to predict the CHF in the fuel bundles of CANDU reactors is to use the ASSERT subchannel code to predict the local thermal-hydraulic conditions prevailing at each axial location in each subchannel in conjunction with appropriate correlations or the CHF look-up table. The successful application of the above methods depends greatly on the ability of ASSERT to accurately predict the local flow conditions throughout the fuel channel. In this paper, full range qualitative verification tests, using the ASSERT subchannel code are presented which show the influence of the void drift model on the predictions of the local subchannel quality. For typical cases using a 7 rod subset of a full 37 element rod bundle taken from the ASSERT validation database, it will be shown that the void drift term can significantly influence the calculated distribution of the quality in the rod bundle. In order to isolate, as much as possible, the influence of the void drift term this first numerical study is carried out with the rod bundle oriented both vertically and horizontally. Subsequently, additional numerical experiments will be presented which show the influence that the void drift model has on the predicted CHF locations. (author)
Taleyarkhan, R.; McFarlane, A.F.; Lahey, R.T. Jr.; Podowski, M.Z.
1988-01-01
The work described in this paper is focused on the development, verification and benchmarking of the NUFREQ-NPW code at Westinghouse, USA for best estimate prediction of multi-channel core stability margins in US BWRs. Various models incorporated into NUFREQ-NPW are systematically compared against the Westinghouse channel stability analysis code MAZDA, which the Mathematical Model was developed in an entirely different manner. The NUFREQ-NPW code is extensively benchmarked against experimental stability data with and without nuclear reactivity feedback. Detailed comparisons are next performed against nuclear-coupled core stability data. A physically based algorithm is developed to correct for the effect of flow development on subcooled boiling. Use of this algorithm (to be described in the full paper) captures the peak magnitude as well as the resonance frequency with good accuracy
Burr, T.L.
1994-04-01
This report is a primer on the analysis of both linear and nonlinear time series with applications in nuclear safeguards and nonproliferation. We analyze eight simulated and two real time series using both linear and nonlinear modeling techniques. The theoretical treatment is brief but references to pertinent theory are provided. Forecasting is our main goal. However, because our most common approach is to fit models to the data, we also emphasize checking model adequacy by analyzing forecast errors for serial correlation or nonconstant variance
Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David
2017-10-01
Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.
Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo
2017-09-01
Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.
Lash, Paul C
2006-01-01
.... The goal of this research is to compare the capabilities of three computational electromagnetic codes for use in production of RCS signature assessments at low frequencies in terms of performance...
Padula, William V; Gibbons, Robert D; Pronovost, Peter J; Hedeker, Donald; Mishra, Manish K; Makic, Mary Beth F; Bridges, John Fp; Wald, Heidi L; Valuck, Robert J; Ginensky, Adam J; Ursitti, Anthony; Venable, Laura Ruth; Epstein, Ziv; Meltzer, David O
2017-04-01
Hospital-acquired pressure ulcers (HAPUs) have a mortality rate of 11.6%, are costly to treat, and result in Medicare reimbursement penalties. Medicare codes HAPUs according to Agency for Healthcare Research and Quality Patient-Safety Indicator 3 (PSI-03), but they are sometimes inappropriately coded. The objective is to use electronic health records to predict pressure ulcers and to identify coding issues leading to penalties. We evaluated all hospitalized patient electronic medical records at an academic medical center data repository between 2011 and 2014. These data contained patient encounter level demographic variables, diagnoses, prescription drugs, and provider orders. HAPUs were defined by PSI-03: stages III, IV, or unstageable pressure ulcers not present on admission as a secondary diagnosis, excluding cases of paralysis. Random forests reduced data dimensionality. Multilevel logistic regression of patient encounters evaluated associations between covariates and HAPU incidence. The approach produced a sample population of 21 153 patients with 1549 PSI-03 cases. The greatest odds ratio (OR) of HAPU incidence was among patients diagnosed with spinal cord injury (ICD-9 907.2: OR = 14.3; P coded for paralysis, leading to a PSI-03 flag. Other high ORs included bed confinement (ICD-9 V49.84: OR = 3.1, P coded without paralysis, leading to PSI-03 flags. The resulting statistical model can be tested to predict HAPUs during hospitalization. Inappropriate coding of conditions leads to poor hospital performance measures and Medicare reimbursement penalties. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga
2006-08-01
A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.
Prediction Capability of SPACE Code about the Loop Seal Clearing on ATLAS SBLOCA
Bae, Sung Won; Lee, Jong Hyuk; Chung, Bub Dong; Kim, Kyung Doo [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2016-10-15
The most possible break size for loop seal reforming has been decided as 4 inch by the pre-calculation conducted by the RELAP5 and MARS. Many organizations have participated with various system analysis codes: for examples, RELAP5, MARS, TRACE. KAERI also anticipated with SPACE code. SPACE code has been developed for the use of design and safety analysis of nuclear thermal hydraulics system. KHNP and other organizations have collaborated during last 10 years. And it is currently under the certification procedures. SPACE has the capability to analyze the droplet field with full governing equation set: continuity, momentum, and energy. The SPACE code has been participated in PKL- 3 benchmark program for the international activity. The DSP-04 benchmark problem is also the application of SPACE as the domestic activities. The cold leg top slot break accident of APR1400 reactor has been modeled and surveyed by SPACE code. Benchmark experiment as a program of DSP-04 has been performed with ATLAS facility. The break size has been selected as 4 inch in APR1400 and the corresponding scale down break size has been modeled in SPACE code. The loop seal reforming has been occurred at all 4 loops. But the PCT shows no significant behaviors.
Luis Gonzaga Baca Ruiz
2016-08-01
Full Text Available This paper addresses the problem of energy consumption prediction using neural networks over a set of public buildings. Since energy consumption in the public sector comprises a substantial share of overall consumption, the prediction of such consumption represents a decisive issue in the achievement of energy savings. In our experiments, we use the data provided by an energy consumption monitoring system in a compound of faculties and research centers at the University of Granada, and provide a methodology to predict future energy consumption using nonlinear autoregressive (NAR and the nonlinear autoregressive neural network with exogenous inputs (NARX, respectively. Results reveal that NAR and NARX neural networks are both suitable for performing energy consumption prediction, but also that exogenous data may help to improve the accuracy of predictions.
vanderWall, Berend G.; Lim, Joon W.; Smith, Marilyn J.; Jung, Sung N.; Bailly, Joelle; Baeder, James D.; Boyd, D. Douglas, Jr.
2012-01-01
Despite significant advancements in computational fluid dynamics and their coupling with computational structural dynamics (= CSD, or comprehensive codes) for rotorcraft applications, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this paper, the capabilities of such codes are evaluated using the HART II Inter- national Workshop data base, focusing on a typical descent operating condition which includes strong blade-vortex interactions. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics - especially for the cases with HHC - and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.
vanderWall, Berend G.; Lim, Joon W.; Smith, Marilyn J.; Jung, Sung N.; Bailly, Joelle; Baeder, James D.; Boyd, D. Douglas, Jr.
2013-01-01
Significant advancements in computational fluid dynamics (CFD) and their coupling with computational structural dynamics (CSD, or comprehensive codes) for rotorcraft applications have been achieved recently. Despite this, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this article, the capabilities of such codes are evaluated using the HART II International Workshop database, focusing on a typical descent operating condition which includes strong blade-vortex interactions. A companion article addresses the CFD/CSD coupled approach. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics-especially for the cases with HHC-and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.
High-performance small-scale solvers for linear Model Predictive Control
Frison, Gianluca; Sørensen, Hans Henrik Brandenborg; Dammann, Bernd
2014-01-01
, with the two main research areas of explicit MPC and tailored on-line MPC. State-of-the-art solvers in this second class can outperform optimized linear-algebra libraries (BLAS) only for very small problems, and do not explicitly exploit the hardware capabilities, relying on compilers for that. This approach...
Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...
Chapman, Robin S.; Hesketh, Linda J.; Kistler, Doris J.
2002-01-01
Longitudinal change in syntax comprehension and production skill, measured over six years, was modeled in 31 individuals (ages 5-20) with Down syndrome. The best fitting Hierarchical Linear Modeling model of comprehension uses age and visual and auditory short-term memory as predictors of initial status, and age for growth trajectory. (Contains…
Eric J. Gustafson; L. Jay Roberts; Larry A. Leefers
2006-01-01
Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (...
Toric Varieties and Codes, Error-correcting Codes, Quantum Codes, Secret Sharing and Decoding
Hansen, Johan Peder
We present toric varieties and associated toric codes and their decoding. Toric codes are applied to construct Linear Secret Sharing Schemes (LSSS) with strong multiplication by the Massey construction. Asymmetric Quantum Codes are obtained from toric codes by the A.R. Calderbank P.W. Shor and A.......M. Steane construction of stabilizer codes (CSS) from linear codes containing their dual codes....
Rohde, Palle Duun; Demontis, Ditte; Børglum, Anders
is enriched for causal variants. Here we apply the GFBLUP model to a small schizophrenia case-control study to test the promise of this model on psychiatric disorders, and hypothesize that the performance will be increased when applying the model to a larger ADHD case-control study if the genomic feature...... contains the causal variants. Materials and Methods: The schizophrenia study consisted of 882 controls and 888 schizophrenia cases genotyped for 520,000 SNPs. The ADHD study contained 25,954 controls and 16,663 ADHD cases with 8,4 million imputed genotypes. Results: The predictive ability for schizophrenia.......6% for the null model). Conclusion: The improvement in predictive ability for schizophrenia was marginal, however, greater improvement is expected for the larger ADHD data....
Analytical prediction of CHF by FIDAS code based on three-fluid and film-dryout model
Sugawara, Satoru
1990-01-01
Analytical prediction model of critical heat flux (CHF) has been developed on the basis of film dryout criterion due to droplets deposition and entrainment in annular mist flow. Critical heat flux in round tubes were analyzed by the Film Dryout Analysis Code in Subchannels (FIDAS) which is based on the three-fluid, three-field and newly developed film dryout model. Predictions by FIDAS were compared with the world-wide experimental data on CHF obtained in water and Freon for uniformly and non-uniformly heated tubes under vertical upward flow condition. Furthermore, CHF prediction capability of FIDAS was compared with those of other film dryout models for annular flow and Katto's CHF correlation. The predictions of FIDAS are in sufficient agreement with the experimental CHF data, and indicate better agreement than the other film dryout models and empirical correlation of Katto. (author)
Atamewoue Surdive
2017-12-01
Full Text Available In this paper, we define linear codes and cyclic codes over a finite Krasner hyperfield and we characterize these codes by their generator matrices and parity check matrices. We also demonstrate that codes over finite Krasner hyperfields are more interesting for code theory than codes over classical finite fields.
A linear regression model for predicting PNW estuarine temperatures in a changing climate
Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...
2017-10-01
ENGINEERING CENTER GRAIN EVALUATION SOFTWARE TO NUMERICALLY PREDICT LINEAR BURN REGRESSION FOR SOLID PROPELLANT GRAIN GEOMETRIES Brian...distribution is unlimited. AD U.S. ARMY ARMAMENT RESEARCH, DEVELOPMENT AND ENGINEERING CENTER Munitions Engineering Technology Center Picatinny...U.S. ARMY ARMAMENT RESEARCH, DEVELOPMENT AND ENGINEERING CENTER GRAIN EVALUATION SOFTWARE TO NUMERICALLY PREDICT LINEAR BURN REGRESSION FOR SOLID
Code requirements document: MODFLOW 2.1: A program for predicting moderator flow patterns
Peterson, P.F.
1992-03-01
Sudden changes in the temperature of flowing liquids can result in transient buoyancy forces which strongly impact the flow hydrodynamics via flow stratification. These effects have been studied for the case of potential flow of stratified liquids to line sinks, but not for moderator flow in SRS reactors. Standard codes, such as TRAC and COMMIX, do not have the capability to capture the stratification effect, due to strong numerical diffusion which smears away the hot/cold fluid interface. A related problem with standard codes is the inability to track plumes injected into the liquid flow, again due to numerical diffusion. The combined effects of buoyant stratification and plume dispersion have been identified as being important in operation of the Supplementary Safety System which injects neutron-poison ink into SRS reactors to provide safe shutdown in the event of safety rod failure. The MODFLOW code discussed here provides transient moderator flow pattern information with stratification effects, and tracks the location of ink plumes in the reactor. The code, written in Fortran, is compiled for Macintosh II computers, and includes subroutines for interactive control and graphical output. Removing the graphics capabilities, the code can also be compiled on other computers. With graphics, in addition to the capability to perform safety related computations, MODFLOW also provides an easy tool for becoming familiar with flow distributions in SRS reactors
Bogachev, Mikhail I.; Bunde, Armin
2011-06-01
We study the predictability of extreme events in records with linear and nonlinear long-range memory in the presence of additive white noise using two different approaches: (i) the precursory pattern recognition technique (PRT) that exploits solely the information about short-term precursors, and (ii) the return interval approach (RIA) that exploits long-range memory incorporated in the elapsed time after the last extreme event. We find that the PRT always performs better when only linear memory is present. In the presence of nonlinear memory, both methods demonstrate comparable efficiency in the absence of white noise. When additional white noise is present in the record (which is the case in most observational records), the efficiency of the PRT decreases monotonously with increasing noise level. In contrast, the RIA shows an abrupt transition between a phase of low level noise where the prediction is as good as in the absence of noise, and a phase of high level noise where the prediction becomes poor. In the phase of low and intermediate noise the RIA predicts considerably better than the PRT, which explains our recent findings in physiological and financial records.
On the Use of Linearized Euler Equations in the Prediction of Jet Noise
Mankbadi, Reda R.; Hixon, R.; Shih, S.-H.; Povinelli, L. A.
1995-01-01
Linearized Euler equations are used to simulate supersonic jet noise generation and propagation. Special attention is given to boundary treatment. The resulting solution is stable and nearly free from boundary reflections without the need for artificial dissipation, filtering, or a sponge layer. The computed solution is in good agreement with theory and observation and is much less CPU-intensive as compared to large-eddy simulations.
Erosion corrosion in power plant piping systems - Calculation code for predicting wall thinning
Kastner, W.; Erve, M.; Henzel, N.; Stellwag, B.
1990-01-01
Extensive experimental and theoretical investigations have been performed to develop a calculation code for wall thinning due to erosion corrosion in power plant piping systems. The so-called WATHEC code can be applied to single-phase water flow as well as to two-phase water/steam flow. Only input data which are available to the operator of the plant are taken into consideration. Together with a continuously updated erosion corrosion data base the calculation code forms one element of a weak point analysis for power plant piping systems which can be applied to minimize material loss due to erosion corrosion, reduce non-destructive testing and curtail monitoring programs for piping systems, recommend life-extending measures. (author). 12 refs, 17 figs
A computer code PACTOLE to predict activation and transport of corrosion products in a PWR
Beslu, P.; Frejaville, G.; Lalet, A.
1978-01-01
Theoretical studies on activation and transport of corrosion products in a PWR primary circuit have been concentrated, at CEA on the development of a computer code : PACTOLE. This code takes into account the major phenomena which govern corrosion products transport: 1. Ion solubility is obtained by usual thermodynamics laws in function of water chemistry: pH at operating temperature is calculated by the code. 2. Release rates of base metals, dissolution rates of deposits, precipitation rates of soluble products are derived from solubility variations. 3. Deposition of solid particles is treated by a model taking into account particle size, brownian and turbulent diffusion and inertial effect. Erosion of deposits is accounted for by a semi-empirical model. After a review of calculational models, an application of PACTOLE is presented in view of analyzing the distribution of in core. (author)
Lorenzen, J.
1990-01-01
A new Fuel rod Performance Simulator code FRPS has been developed, tested and benchmarked and is now available in different versions. The user may choose between the batch version INTERPIN producing results in form of listings or beforehand defined plots, or the interactive simulator code SIMSIM which is stepping through a power history under the control of user. Both versions are presently running on minicomputers and PC:s using EGA-Graphics. A third version is the implementation in a Studsvik Compact Simulator with FRPS being one of its various modules receiving the dynamic inputs from the simulator
Le Thanh Xuan; Nguyen Thi Cam Thu; Tran Van Nghia; Truong Thi Hong Loan; Vo Thanh Nhon
2015-01-01
The dose distribution calculation is one of the major steps in radiotherapy. In this paper the Monte Carlo code MCNP5 has been applied for simulation 15 MV photon beams emitted from linear accelerator in a case of lung cancer of the General Hospital of Kien Giang. The settings for beam directions, field sizes and isocenter position used in MCNP5 must be the same as those in treatment plan at the hospital to ensure the results from MCNP5 are accurate. We also built a program CODIM by using MATLAB® programming software. This program was used to construct patient model from lung CT images obtained from cancer treatment cases at the General Hospital of Kien Giang and then MCNP5 code was used to simulate the delivered dose in the patient. The results from MCNP5 show that there is a difference of 5% in comparison with Prowess Panther program - a semi-empirical simulation program which is being used for treatment planning in the General Hospital of Kien Giang. The success of the work will help the planners to verify the patient dose distribution calculated from the treatment planning program being used at the hospital. (author)
Wang, Ming; Li, Zheng; Lee, Eun Young; Lewis, Mechelle M; Zhang, Lijun; Sterling, Nicholas W; Wagner, Daymond; Eslinger, Paul; Du, Guangwei; Huang, Xuemei
2017-09-25
It is challenging for current statistical models to predict clinical progression of Parkinson's disease (PD) because of the involvement of multi-domains and longitudinal data. Past univariate longitudinal or multivariate analyses from cross-sectional trials have limited power to predict individual outcomes or a single moment. The multivariate generalized linear mixed-effect model (GLMM) under the Bayesian framework was proposed to study multi-domain longitudinal outcomes obtained at baseline, 18-, and 36-month. The outcomes included motor, non-motor, and postural instability scores from the MDS-UPDRS, and demographic and standardized clinical data were utilized as covariates. The dynamic prediction was performed for both internal and external subjects using the samples from the posterior distributions of the parameter estimates and random effects, and also the predictive accuracy was evaluated based on the root of mean square error (RMSE), absolute bias (AB) and the area under the receiver operating characteristic (ROC) curve. First, our prediction model identified clinical data that were differentially associated with motor, non-motor, and postural stability scores. Second, the predictive accuracy of our model for the training data was assessed, and improved prediction was gained in particularly for non-motor (RMSE and AB: 2.89 and 2.20) compared to univariate analysis (RMSE and AB: 3.04 and 2.35). Third, the individual-level predictions of longitudinal trajectories for the testing data were performed, with ~80% observed values falling within the 95% credible intervals. Multivariate general mixed models hold promise to predict clinical progression of individual outcomes in PD. The data was obtained from Dr. Xuemei Huang's NIH grant R01 NS060722 , part of NINDS PD Biomarker Program (PDBP). All data was entered within 24 h of collection to the Data Management Repository (DMR), which is publically available ( https://pdbp.ninds.nih.gov/data-management ).
Multi input single output model predictive control of non-linear bio-polymerization process
Arumugasamy, Senthil Kumar; Ahmad, Z. [School of Chemical Engineering, Univerisiti Sains Malaysia, Engineering Campus, Seri Ampangan,14300 Nibong Tebal, Seberang Perai Selatan, Pulau Pinang (Malaysia)
2015-05-15
This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.
Zhou, L; Lund, M S; Wang, Y; Su, G
2014-08-01
This study investigated genomic predictions across Nordic Holstein and Nordic Red using various genomic relationship matrices. Different sources of information, such as consistencies of linkage disequilibrium (LD) phase and marker effects, were used to construct the genomic relationship matrices (G-matrices) across these two breeds. Single-trait genomic best linear unbiased prediction (GBLUP) model and two-trait GBLUP model were used for single-breed and two-breed genomic predictions. The data included 5215 Nordic Holstein bulls and 4361 Nordic Red bulls, which was composed of three populations: Danish Red, Swedish Red and Finnish Ayrshire. The bulls were genotyped with 50 000 SNP chip. Using the two-breed predictions with a joint Nordic Holstein and Nordic Red reference population, accuracies increased slightly for all traits in Nordic Red, but only for some traits in Nordic Holstein. Among the three subpopulations of Nordic Red, accuracies increased more for Danish Red than for Swedish Red and Finnish Ayrshire. This is because closer genetic relationships exist between Danish Red and Nordic Holstein. Among Danish Red, individuals with higher genomic relationship coefficients with Nordic Holstein showed more increased accuracies in the two-breed predictions. Weighting the two-breed G-matrices by LD phase consistencies, marker effects or both did not further improve accuracies of the two-breed predictions. © 2014 Blackwell Verlag GmbH.
Albajes-Eizagirre, Anton; Romero, Laia; Soria-Frisch, Aureli; Vanhellemont, Quinten
2011-11-01
Impact of jellyfish in human activities has been increasingly reported worldwide in recent years. Segments such as tourism, water sports and leisure, fisheries and aquaculture are commonly damaged when facing blooms of gelatinous zooplankton. Hence the prediction of the appearance and disappearance of jellyfish in our coasts, which is not fully understood from its biological point of view, has been approached as a pattern recognition problem in the paper presented herein, where a set of potential ecological cues was selected to test their usefulness for prediction. Remote sensing data was used to describe environmental conditions that could support the occurrence of jellyfish blooms with the aim of capturing physical-biological interactions: forcing, coastal morphology, food availability, and water mass characteristics are some of the variables that seem to exert an effect on jellyfish accumulation on the shoreline, under specific spatial and temporal windows. A data-driven model based on computational intelligence techniques has been designed and implemented to predict jellyfish events on the beach area as a function of environmental conditions. Data from 2009 over the NW Mediterranean continental shelf have been used to train and test this prediction protocol. Standard level 2 products are used from MODIS (NASA OceanColor) and MERIS (ESA - FRS data). The procedure for designing the analysis system can be described as following. The aforementioned satellite data has been used as feature set for the performance evaluation. Ground truth has been extracted from visual observations by human agents on different beach sites along the Catalan area. After collecting the evaluation data set, the performance between different computational intelligence approaches have been compared. The outperforming one in terms of its generalization capability has been selected for prediction recall. Different tests have been conducted in order to assess the prediction capability of the
Abe, Hitoshi; Nishio; Gunji; Naito, Yoshitaka
1993-11-01
The accident analysis code TRANS-ACE was developed to evaluate the safety of a ventilation system in a reprocessing plant in the event of fire and explosion accidents. TRANS-ACE can evaluate not only the integrity of a ventilation system containing HEPA filters but also the source term of radioactive materials for release out of a plant. It calculates the temperature, pressure, flow rate, transport of combustion materials and confinement of radioactive materials in the network of a ventilation system that might experience a fire or explosion accident. TRANS-ACE is based on the one-dimensional compressible thermo-fluid analysis code EVENT developed by Los Alamos National Laboratory (LANL). Calculational functions are added for the radioactive source term, heat transfer and radiation to cell and duct walls and HEPA filter integrity. For the second edition in the report, TRANS-ACE has been improved incorporating functions for the initial steady-state calculation to determine the flow rates, pressure drops and temperature in the network before an accident mode analysis. It is also improved to include flow resistance calculations of the filters and blowers in the network and to have an easy to use code by simplifying the input formats. This report is to prepare an explanation of the mathematical model for TRANS-ACE code and to be the user's manual. (author)
Kiteley, J.C.; Carver, M.B.; Zhou, Q.N.
1993-01-01
The ASSERT code has been developed to address the three-dimensional computation of flow and phase distribution and fuel element surface temperatures within the horizontal subchannels of CANDU PHWR fuel channels, and to provide a detailed prediction of critical heat flux distribution throughout the bundle. The ASSERT subchannel code has been validated extensively against a wide repertoire of experiments; its combination of three-dimensional prediction of local flow conditions with a comprehensive method of predicting critical heat flux (CHF) at these local conditions makes it a unique tool for predicting CHF for situations outside the existing experimental data base. In particular, ASSERT is the only tool available to systematically investigate CHF under conditions of local geometric variations, such as pressure tube creep and fuel element strain. This paper discusses the numerical methodology used in ASSERT, the constitutive relationships incorporated, and the CHF assessment methodology. The evolutionary validation plan is discussed, and early validation exercises are summarized. The paper concentrates, however, on more recent validation exercises in standard and non-standard geometries. 28 refs., 12 figs
Carver, M.B.; Kiteley, J.C.; Zhou, R.Q.N.; Junop, S.V.; Rowe, D.S.
1995-01-01
The ASSERT code has been developed to address the three-dimensional computation of flow and phase distribution and fuel element surface temperatures within the horizontal subchannels of Canada uranium deuterium (CANDU) pressurized heavy water reactor fuel channels and to provide a detailed prediction of critical heat flux (CHF) distribution throughout the bundle. The ASSERT subchannel code has been validated extensively against a wide repertoire of experiments; its combination of three-dimensional prediction of local flow conditions with a comprehensive method of predicting CHF at these local conditions makes it a unique tool for predicting CHF for situations outside the existing experimental database. In particular, ASSERT is an appropriate tool to systematically investigate CHF under conditions of local geometric variations, such as pressure tube creep and fuel element strain. The numerical methodology used in ASSERT, the constitutive relationships incorporated, and the CHF assessment methodology are discussed. The evolutionary validation plan is also discussed and early validation exercises are summarized. More recent validation exercises in standard and nonstandard geometries are emphasized
Keshavarz, Mohammad Hossein; Gharagheizi, Farhad; Shokrolahi, Arash; Zakinejad, Sajjad
2012-01-01
Highlights: ► A novel method is introduced for desk calculation of toxicity of benzoic acid derivatives. ► There is no need to use QSAR and QSTR methods, which are based on computer codes. ► The predicted results of 58 compounds are more reliable than those predicted by QSTR method. ► The present method gives good predictions for further 324 benzoic acid compounds. - Abstract: Most of benzoic acid derivatives are toxic, which may cause serious public health and environmental problems. Two novel simple and reliable models are introduced for desk calculations of the toxicity of benzoic acid compounds in mice via oral LD 50 with more reliance on their answers as one could attach to the more complex outputs. They require only elemental composition and molecular fragments without using any computer codes. The first model is based on only the number of carbon and hydrogen atoms, which can be improved by several molecular fragments in the second model. For 57 benzoic compounds, where the computed results of quantitative structure–toxicity relationship (QSTR) were recently reported, the predicted results of two simple models of present method are more reliable than QSTR computations. The present simple method is also tested with further 324 benzoic acid compounds including complex molecular structures, which confirm good forecasting ability of the second model.
Three dimensional force prediction in a model linear brushless dc motor
Moghani, J.S.; Eastham, J.F.; Akmese, R.; Hill-Cottingham, R.J. (Univ. of Bath (United Kingdom). School of Electronic and Electric Engineering)
1994-11-01
Practical results are presented for the three axes forces produced on the primary of a linear brushless dc machine which is supplied from a three-phase delta-modulated inverter. Conditions of both lateral alignment and lateral displacement are considered. Finite element analysis using both two and three dimensional modeling is compared with the practical results. It is shown that a modified two dimensional model is adequate, where it can be used, in the aligned position and that the full three dimensional method gives good results when the machine is axially misaligned.
Drzewiecki Wojciech
2016-12-01
Full Text Available In this work nine non-linear regression models were compared for sub-pixel impervious surface area mapping from Landsat images. The comparison was done in three study areas both for accuracy of imperviousness coverage evaluation in individual points in time and accuracy of imperviousness change assessment. The performance of individual machine learning algorithms (Cubist, Random Forest, stochastic gradient boosting of regression trees, k-nearest neighbors regression, random k-nearest neighbors regression, Multivariate Adaptive Regression Splines, averaged neural networks, and support vector machines with polynomial and radial kernels was also compared with the performance of heterogeneous model ensembles constructed from the best models trained using particular techniques.
Karahan, Aydin, E-mail: karahan@mit.ed [Center for Advanced Nuclear Energy Systems, Nuclear Science and Engineering Department, Massachusetts Institute of Technology (United States); Buongiorno, Jacopo [Center for Advanced Nuclear Energy Systems, Nuclear Science and Engineering Department, Massachusetts Institute of Technology (United States)
2010-01-31
An engineering code to predict the irradiation behavior of U-Zr and U-Pu-Zr metallic alloy fuel pins and UO{sub 2}-PuO{sub 2} mixed oxide fuel pins in sodium-cooled fast reactors was developed. The code was named Fuel Engineering and Structural analysis Tool (FEAST). FEAST has several modules working in coupled form with an explicit numerical algorithm. These modules describe fission gas release and fuel swelling, fuel chemistry and restructuring, temperature distribution, fuel-clad chemical interaction, and fuel and clad mechanical analysis including transient creep-fracture for the clad. Given the fuel pin geometry, composition and irradiation history, FEAST can analyze fuel and clad thermo-mechanical behavior at both steady-state and design-basis (non-disruptive) transient scenarios. FEAST was written in FORTRAN-90 and has a simple input file similar to that of the LWR fuel code FRAPCON. The metal-fuel version is called FEAST-METAL, and is described in this paper. The oxide-fuel version, FEAST-OXIDE is described in a companion paper. With respect to the old Argonne National Laboratory code LIFE-METAL and other same-generation codes, FEAST-METAL emphasizes more mechanistic, less empirical models, whenever available. Specifically, fission gas release and swelling are modeled with the GRSIS algorithm, which is based on detailed tracking of fission gas bubbles within the metal fuel. Migration of the fuel constituents is modeled by means of thermo-transport theory. Fuel-clad chemical interaction models based on precipitation kinetics were developed for steady-state operation and transients. Finally, a transient intergranular creep-fracture model for the clad, which tracks the nucleation and growth of the cavities at the grain boundaries, was developed for and implemented in the code. Reducing the empiricism in the constitutive models should make it more acceptable to extrapolate FEAST-METAL to new fuel compositions and higher burnup, as envisioned in advanced sodium
Karahan, Aydin; Buongiorno, Jacopo
2010-01-01
An engineering code to predict the irradiation behavior of U-Zr and U-Pu-Zr metallic alloy fuel pins and UO 2 -PuO 2 mixed oxide fuel pins in sodium-cooled fast reactors was developed. The code was named Fuel Engineering and Structural analysis Tool (FEAST). FEAST has several modules working in coupled form with an explicit numerical algorithm. These modules describe fission gas release and fuel swelling, fuel chemistry and restructuring, temperature distribution, fuel-clad chemical interaction, and fuel and clad mechanical analysis including transient creep-fracture for the clad. Given the fuel pin geometry, composition and irradiation history, FEAST can analyze fuel and clad thermo-mechanical behavior at both steady-state and design-basis (non-disruptive) transient scenarios. FEAST was written in FORTRAN-90 and has a simple input file similar to that of the LWR fuel code FRAPCON. The metal-fuel version is called FEAST-METAL, and is described in this paper. The oxide-fuel version, FEAST-OXIDE is described in a companion paper. With respect to the old Argonne National Laboratory code LIFE-METAL and other same-generation codes, FEAST-METAL emphasizes more mechanistic, less empirical models, whenever available. Specifically, fission gas release and swelling are modeled with the GRSIS algorithm, which is based on detailed tracking of fission gas bubbles within the metal fuel. Migration of the fuel constituents is modeled by means of thermo-transport theory. Fuel-clad chemical interaction models based on precipitation kinetics were developed for steady-state operation and transients. Finally, a transient intergranular creep-fracture model for the clad, which tracks the nucleation and growth of the cavities at the grain boundaries, was developed for and implemented in the code. Reducing the empiricism in the constitutive models should make it more acceptable to extrapolate FEAST-METAL to new fuel compositions and higher burnup, as envisioned in advanced sodium reactors
Ren, Y Y; Zhou, L C; Yang, L; Liu, P Y; Zhao, B W; Liu, H X
2016-09-01
The paper highlights the use of the logistic regression (LR) method in the construction of acceptable statistically significant, robust and predictive models for the classification of chemicals according to their aquatic toxic modes of action. Essentials accounting for a reliable model were all considered carefully. The model predictors were selected by stepwise forward discriminant analysis (LDA) from a combined pool of experimental data and chemical structure-based descriptors calculated by the CODESSA and DRAGON software packages. Model predictive ability was validated both internally and externally. The applicability domain was checked by the leverage approach to verify prediction reliability. The obtained models are simple and easy to interpret. In general, LR performs much better than LDA and seems to be more attractive for the prediction of the more toxic compounds, i.e. compounds that exhibit excess toxicity versus non-polar narcotic compounds and more reactive compounds versus less reactive compounds. In addition, model fit and regression diagnostics was done through the influence plot which reflects the hat-values, studentized residuals, and Cook's distance statistics of each sample. Overdispersion was also checked for the LR model. The relationships between the descriptors and the aquatic toxic behaviour of compounds are also discussed.
Amano, Hikaru; Uchida, Shigeo; Matsuoka, Syungo; Ikeda, Hiroshi; Hayashi, Hiroko; Kurosawa, Naohiro
2003-01-01
A Code MOGRA (Migration Of GRound Additions) is a migration prediction code for toxic ground additions including radioactive materials in a terrestrial environment, which consists of computational codes that are applicable to various evaluation target systems, and can be used on personal computers. The computational code has the dynamic compartment analysis block at its core, the graphical user interface (GUI) for model formation, computation parameter settings, and results displays. The compartments are obtained by classifying various natural environments into groups that exhibit similar properties. The functionality of MOGRA is being verified by applying it in the analyses of the migration rates of radioactive substances from the atmosphere to soils and plants and flow rates into the rivers. In this report, a hypothetical combination of land usage was supposed to check the function of MOGRA. The land usage was consisted from cultivated lands, forests, uncultivated lands, urban area, river, and lake. Each land usage has its own inside model which is basic module. Also supposed was homogeneous contamination of the surface land from atmospheric deposition of 137 Cs(1.0Bq/m 2 ). The system analyzed the dynamic changes of 137 Cs concentrations in each compartment, fluxes from one compartment to another compartment. (author)
Predictions of Critical Heat Flux Using the ASSERT-PV Subchannel Code for a CANFLEX Variant Bundle
Onder, Ebru Nihan; Leung, Laurence; Kim, Hung; Rao, Yanfei
2009-01-01
The ASSERT-PV subchannel code developed by AECL has been applied as a design-assist tool to the advanced CANDU 1 reactor fuel bundle. Based primarily on the CANFLEX 2 fuel bundle, several geometry changes (such as element sizes and pitchcircle diameters of various element rings) were examined to optimize the dryout power and pressure-drop performances of the new fuel bundle. An experiment was performed to obtain dryout power measurements for verification of the ASSERT-PV code predictions. It was carried out using an electrically heated, Refrigerant-134a cooled, fuel bundle string simulator. The axial power profile of the simulator was uniform, while the radial power profile of the element rings was varied simulating profiles in bundles with various fuel compositions and burn-ups. Dryout power measurements are predicted closely using the ASSERT-PV code, particularly at low flows and low pressures, but are overpredicted at high flows and high pressures. The majority of data shows that dryout powers are underpredicted at low inlet-fluid temperatures but overpredicted at high inlet-fluid temperatures
Darazi, R.; Gouze, A.; Macq, B.
2009-01-01
Reproducing a natural and real scene as we see in the real world everyday is becoming more and more popular. Stereoscopic and multi-view techniques are used for this end. However due to the fact that more information are displayed requires supporting technologies such as digital compression to ensure the storage and transmission of the sequences. In this paper, a new scheme for stereo image coding is proposed. The original left and right images are jointly coded. The main idea is to optimally exploit the existing correlation between the two images. This is done by the design of an efficient transform that reduces the existing redundancy in the stereo image pair. This approach was inspired by Lifting Scheme (LS). The novelty in our work is that the prediction step is been replaced by an hybrid step that consists in disparity compensation followed by luminance correction and an optimized prediction step. The proposed scheme can be used for lossless and for lossy coding. Experimental results show improvement in terms of performance and complexity compared to recently proposed methods.
Lee, C.B.
2002-01-01
CRUDTRAN code is to predict transport of the corrosion products and their radio-activated nuclides such as cobalt-58 and cobalt-60 in the PWR primary coolant system. In CRUDTRAN code the PWR primary circuit is divided into three principal sections such as the core, the coolant and the steam generator. The main driving force for corrosion product transport in the PWR primary coolant comes from coolant temperature change throughout the system and a subsequent change in corrosion product solubility. As the coolant temperature changes around the PWR primary circuit, saturation status of the corrosion products in the coolant also changes such that under-saturation in steam generator and super-saturation in the core. CRUDTRAN code was evaluated by comparison with the results of the in-reactor loop tests simulating the PWR primary coolant system and PWR plant data. It showed that CRUDTRAN could predict variations of cobalt-58 and cobalt-60 radioactivity with time, plant cycle and coolant chemistry in the PWR plant. (author)
Tye, P [Ecole Polytechnique, Montreal, PQ (Canada)
1994-12-31
In this paper, effects of that the constitutive relations used to represent some of the intersubchannel transfer mechanisms have on the predictions of the ASSERT-4 subchannel code for horizontal flows are examined. In particular the choices made in the representation of the gravity driven phase separation phenomena, which is unique to the horizontal fuel channel arrangement seen in CANDU reactors, are analyzed. This is done by comparing the predictions of the ASSERT-4 subchannel code with experimental data on void fraction, mass flow rate, and pressure drop obtained for two horizontal interconnected subchannels. ASSERT-4, the subchannel code used by the Canadian nuclear industry, uses an advanced drift flux model which permits departure from both thermal and mechanical equilibrium between the phases to be accurately modeled. In particular ASSERT-4 contains models for the buoyancy effects which cause phase separation between adjacent subchannels in horizontal flows. This feature, which is of great importance in the subchannel analysis of CANDU reactors, is implemented in the constitutive relationship for the relative velocity required by the conservation equations. In order to, as much as is physically possible, isolate different inter-subchannel transfer mechanisms, three different subchannel orientations are analyzed. These are: the two subchannels at the same elevation, the high void subchannel below the low void subchannel, and the high void subchannel above the low void subchannel. It is observed that for all three subchannel orientations ASSERT-4 does a reasonably good job of predicting the experimental trends. However, certain modifications to the representation of the gravitational phase separation effects which seem to improve the overall predictions are suggested. (author). 12 refs., 12 figs.
Schuecker, Clara; Davila, Carlos G.; Rose, Cheryl A.
2010-01-01
Five models for matrix damage in fiber reinforced laminates are evaluated for matrix-dominated loading conditions under plane stress and are compared both qualitatively and quantitatively. The emphasis of this study is on a comparison of the response of embedded plies subjected to a homogeneous stress state. Three of the models are specifically designed for modeling the non-linear response due to distributed matrix cracking under homogeneous loading, and also account for non-linear (shear) behavior prior to the onset of cracking. The remaining two models are localized damage models intended for predicting local failure at stress concentrations. The modeling approaches of distributed vs. localized cracking as well as the different formulations of damage initiation and damage progression are compared and discussed.
Christiansen, Bo
2015-04-01
Linear regression methods are without doubt the most used approaches to describe and predict data in the physical sciences. They are often good first order approximations and they are in general easier to apply and interpret than more advanced methods. However, even the properties of univariate regression can lead to debate over the appropriateness of various models as witnessed by the recent discussion about climate reconstruction methods. Before linear regression is applied important choices have to be made regarding the origins of the noise terms and regarding which of the two variables under consideration that should be treated as the independent variable. These decisions are often not easy to make but they may have a considerable impact on the results. We seek to give a unified probabilistic - Bayesian with flat priors - treatment of univariate linear regression and prediction by taking, as starting point, the general errors-in-variables model (Christiansen, J. Clim., 27, 2014-2031, 2014). Other versions of linear regression can be obtained as limits of this model. We derive the likelihood of the model parameters and predictands of the general errors-in-variables model by marginalizing over the nuisance parameters. The resulting likelihood is relatively simple and easy to analyze and calculate. The well known unidentifiability of the errors-in-variables model is manifested as the absence of a well-defined maximum in the likelihood. However, this does not mean that probabilistic inference can not be made; the marginal likelihoods of model parameters and the predictands have, in general, well-defined maxima. We also include a probabilistic version of classical calibration and show how it is related to the errors-in-variables model. The results are illustrated by an example from the coupling between the lower stratosphere and the troposphere in the Northern Hemisphere winter.
Sharad Shandilya
Full Text Available The timing of defibrillation is mostly at arbitrary intervals during cardio-pulmonary resuscitation (CPR, rather than during intervals when the out-of-hospital cardiac arrest (OOH-CA patient is physiologically primed for successful countershock. Interruptions to CPR may negatively impact defibrillation success. Multiple defibrillations can be associated with decreased post-resuscitation myocardial function. We hypothesize that a more complete picture of the cardiovascular system can be gained through non-linear dynamics and integration of multiple physiologic measures from biomedical signals.Retrospective analysis of 153 anonymized OOH-CA patients who received at least one defibrillation for ventricular fibrillation (VF was undertaken. A machine learning model, termed Multiple Domain Integrative (MDI model, was developed to predict defibrillation success. We explore the rationale for non-linear dynamics and statistically validate heuristics involved in feature extraction for model development. Performance of MDI is then compared to the amplitude spectrum area (AMSA technique.358 defibrillations were evaluated (218 unsuccessful and 140 successful. Non-linear properties (Lyapunov exponent > 0 of the ECG signals indicate a chaotic nature and validate the use of novel non-linear dynamic methods for feature extraction. Classification using MDI yielded ROC-AUC of 83.2% and accuracy of 78.8%, for the model built with ECG data only. Utilizing 10-fold cross-validation, at 80% specificity level, MDI (74% sensitivity outperformed AMSA (53.6% sensitivity. At 90% specificity level, MDI had 68.4% sensitivity while AMSA had 43.3% sensitivity. Integrating available end-tidal carbon dioxide features into MDI, for the available 48 defibrillations, boosted ROC-AUC to 93.8% and accuracy to 83.3% at 80% sensitivity.At clinically relevant sensitivity thresholds, the MDI provides improved performance as compared to AMSA, yielding fewer unsuccessful defibrillations
Katharina Schmack
2015-06-01
Conclusion: Our results indicate an association between a weakened effect of sensory predictions in perceptual inference and delusions in schizophrenia. We suggest that attenuated predictive signaling during perceptual inference in schizophrenia may yield the experience of aberrant salience, thereby providing the starting point for the formation of delusions.
Predictive coding of visual-auditory and motor-auditory events: An electrophysiological study.
Stekelenburg, Jeroen J; Vroomen, Jean
2015-11-11
The amplitude of auditory components of the event-related potential (ERP) is attenuated when sounds are self-generated compared to externally generated sounds. This effect has been ascribed to internal forward modals predicting the sensory consequences of one's own motor actions. Auditory potentials are also attenuated when a sound is accompanied by a video of anticipatory visual motion that reliably predicts the sound. Here, we investigated whether the neural underpinnings of prediction of upcoming auditory stimuli are similar for motor-auditory (MA) and visual-auditory (VA) events using a stimulus omission paradigm. In the MA condition, a finger tap triggered the sound of a handclap whereas in the VA condition the same sound was accompanied by a video showing the handclap. In both conditions, the auditory stimulus was omitted in either 50% or 12% of the trials. These auditory omissions induced early and mid-latency ERP components (oN1 and oN2, presumably reflecting prediction and prediction error), and subsequent higher-order error evaluation processes. The oN1 and oN2 of MA and VA were alike in amplitude, topography, and neural sources despite that the origin of the prediction stems from different brain areas (motor versus visual cortex). This suggests that MA and VA predictions activate a sensory template of the sound in auditory cortex. This article is part of a Special Issue entitled SI: Prediction and Attention. Copyright © 2015 Elsevier B.V. All rights reserved.
Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna
2017-01-01
The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard…
Pčolka, M.; Žáčeková, E.; Robinett, R.; Čelikovský, Sergej; Šebek, M.
2016-01-01
Roč. 53, č. 1 (2016), s. 124-138 ISSN 0967-0661 R&D Projects: GA ČR GA13-20433S Institutional support: RVO:67985556 Keywords : Model predictive control * Identification for control * Building climatecontrol Subject RIV: BC - Control Systems Theory Impact factor: 2.602, year: 2016 http://library.utia.cas.cz/separaty/2016/TR/celikovsky-0460306.pdf
Prediction of high airway pressure using a non-linear autoregressive model of pulmonary mechanics.
Langdon, Ruby; Docherty, Paul D; Schranz, Christoph; Chase, J Geoffrey
2017-11-02
For mechanically ventilated patients with acute respiratory distress syndrome (ARDS), suboptimal PEEP levels can cause ventilator induced lung injury (VILI). In particular, high PEEP and high peak inspiratory pressures (PIP) can cause over distension of alveoli that is associated with VILI. However, PEEP must also be sufficient to maintain recruitment in ARDS lungs. A lung model that accurately and precisely predicts the outcome of an increase in PEEP may allow dangerous high PIP to be avoided, and reduce the incidence of VILI. Sixteen pressure-flow data sets were collected from nine mechanically ventilated ARDs patients that underwent one or more recruitment manoeuvres. A nonlinear autoregressive (NARX) model was identified on one or more adjacent PEEP steps, and extrapolated to predict PIP at 2, 4, and 6 cmH 2 O PEEP horizons. The analysis considered whether the predicted and measured PIP exceeded a threshold of 40 cmH 2 O. A direct comparison of the method was made using the first order model of pulmonary mechanics (FOM(I)). Additionally, a further, more clinically appropriate method for the FOM was tested, in which the FOM was trained on a single PEEP prior to prediction (FOM(II)). The NARX model exhibited very high sensitivity (> 0.96) in all cases, and a high specificity (> 0.88). While both FOM methods had a high specificity (> 0.96), the sensitivity was much lower, with a mean of 0.68 for FOM(I), and 0.82 for FOM(II). Clinically, false negatives are more harmful than false positives, as a high PIP may result in distension and VILI. Thus, the NARX model may be more effective than the FOM in allowing clinicians to reduce the risk of applying a PEEP that results in dangerously high airway pressures.
Abad, Cesar C C; Barros, Ronaldo V; Bertuzzi, Romulo; Gagliardi, João F L; Lima-Silva, Adriano E; Lambert, Mike I; Pires, Flavio O
2016-06-01
The aim of this study was to verify the power of VO 2max , peak treadmill running velocity (PTV), and running economy (RE), unadjusted or allometrically adjusted, in predicting 10 km running performance. Eighteen male endurance runners performed: 1) an incremental test to exhaustion to determine VO 2max and PTV; 2) a constant submaximal run at 12 km·h -1 on an outdoor track for RE determination; and 3) a 10 km running race. Unadjusted (VO 2max , PTV and RE) and adjusted variables (VO 2max 0.72 , PTV 0.72 and RE 0.60 ) were investigated through independent multiple regression models to predict 10 km running race time. There were no significant correlations between 10 km running time and either the adjusted or unadjusted VO 2max . Significant correlations (p 0.84 and power > 0.88. The allometrically adjusted predictive model was composed of PTV 0.72 and RE 0.60 and explained 83% of the variance in 10 km running time with a standard error of the estimate (SEE) of 1.5 min. The unadjusted model composed of a single PVT accounted for 72% of the variance in 10 km running time (SEE of 1.9 min). Both regression models provided powerful estimates of 10 km running time; however, the unadjusted PTV may provide an uncomplicated estimation.
Zhang, Jie; Stonnington, Cynthia; Li, Qingyang; Shi, Jie; Bauer, Robert J; Gutman, Boris A; Chen, Kewei; Reiman, Eric M; Thompson, Paul M; Ye, Jieping; Wang, Yalin
2016-04-01
Alzheimer's disease (AD) is a progressive brain disease. Accurate diagnosis of AD and its prodromal stage, mild cognitive impairment, is crucial for clinical trial design. There is also growing interests in identifying brain imaging biomarkers that help evaluate AD risk presymptomatically. Here, we applied a recently developed multivariate tensor-based morphometry (mTBM) method to extract features from hippocampal surfaces, derived from anatomical brain MRI. For such surface-based features, the feature dimension is usually much larger than the number of subjects. We used dictionary learning and sparse coding to effectively reduce the feature dimensions. With the new features, an Adaboost classifier was employed for binary group classification. In tests on publicly available data from the Alzheimers Disease Neuroimaging Initiative, the new framework outperformed several standard imaging measures in classifying different stages of AD. The new approach combines the efficiency of sparse coding with the sensitivity of surface mTBM, and boosts classification performance.
Predicting tritium movement and inventory in fusion reactor subsystems using the TMAP code
Jones, J.L.; Merrill, B.J.; Holland, D.F.
1986-01-01
The Fusion Safety Program of EGandG idaho, Inc. at the Idaho National Engineering Laboratory (INEL) is developing a safety analysis code called TMAP (Tritium Migration Analysis Program) to analyze tritium loss from fusion systems during normal and off-normal conditions. TMAP is a one-dimensional code that calculates tritium movement and inventories in a system of interconnected enclosures and wall structures. These wall structures can include composite materials with bulk trapping of the permeating tritium on impurities or radiation induced dislocations within the material. The thermal response of a structure can be modeled to provide temperature information required for tritium movement calculations. Chemical reactions and hydrogen isotope movement can also be included in the calculations. TMAP was used to analyze the movement of tritium implanted into a proposed limiter/first wall structure design
Huo, Pengfei; Miller, Thomas F. III; Coker, David F.
2013-01-01
A partial linearized path integral approach is used to calculate the condensed phase electron transfer (ET) rate by directly evaluating the flux-flux/flux-side quantum time correlation functions. We demonstrate for a simple ET model that this approach can reliably capture the transition between non-adiabatic and adiabatic regimes as the electronic coupling is varied, while other commonly used semi-classical methods are less accurate over the broad range of electronic couplings considered. Further, we show that the approach reliably recovers the Marcus turnover as a function of thermodynamic driving force, giving highly accurate rates over four orders of magnitude from the normal to the inverted regimes. We also demonstrate that the approach yields accurate rate estimates over five orders of magnitude of inverse temperature. Finally, the approach outlined here accurately captures the electronic coherence in the flux-flux correlation function that is responsible for the decreased rate in the inverted regime
Sharma, P.; Khare, M.
2000-01-01
Historical data of the time-series of carbon monoxide (CO) concentration was analysed using Box-Jenkins modelling approach. Univariate Linear Stochastic Models (ULSMs) were developed to examine the degree of prediction possible for situations where only a limited data set, restricted only to the past record of pollutant data are available. The developed models can be used to provide short-term, real-time forecast of extreme CO concentrations for an Air Quality Control Region (AQCR), comprising a major traffic intersection in a Central Business District of Delhi City, India. (author)
Taleyarkhan, R.P.; McFarlane, A.F.; Lahey, R.T. Jr.; Podowski, M.Z.
1994-01-01
The ppercase nufreq - ppercase np (G.C. Park et al. NUREG/CR-3375, 1983; S.J. Peng et al. NUREG/CR-4116, 1984; S.J. Peng et al. Nucl. Sci. Eng. 88 (1988) 404-411) code was modified and set up at Westinghouse, USA, for mixed fuel type multichannel core-wide stability analysis. The resulting code, ppercase nufreq - ppercase npw , allows for variable axial power profiles between channel groups and can handle mixed fuel types.Various models incorporated into ppercase nurfreq - ppercase npw were systematically compared against the Westinghouse channel stability analysis code ppercase mazda -ppercase nf (R. Taleyarkhan et al. J. Heat Transfer 107 (February 1985) 175-181; NUREG/CR2972, 1983), for which the mathematical model was developed in an entirely different manner. Excellent agreement was obtained which verified the thermal-hydraulic modeling and coding aspects. Detailed comparisons were also performed against nuclear-coupled reactor core stability data. All 13 Peach Bottom-2 EOC-2/3 low flow stability tests (L.A. Carmichael and R.O. Neimi, EPRI NP-564, Project 1020-1, 1978; F.B. Woffinden and R.O. Neimi, EPRI, NP 0972, Project 1020-2, 1981) were simulated. A key aspect for code qualification involved the development of a physically based empirical algorithm to correct for the effect of core inlet flow development on subcooled boiling. Various other modeling assumptions were tested and sensitivity studies performed. Good agreement was obtained between ppercase nufreq-npw predictions and data. ((orig.))
Carver, M.B.; Kiteley, J.C.; Zhou, R.Q.N.; Junop, S.V.; Rowe, D.S.
1993-01-01
The ASSERT code has been developed to address the three-dimensional computation of flow and phase distribution and fuel element surface temperatures within the horizontal subchannels of CANDU PHWR fuel channels, and to provide a detailed prediction of critical heat flux (CHF) distribution throughout the bundle. The ASSERT subchannel code has been validated extensively against a wide repertoire of experiments; its combination of three-dimensional prediction of local flow conditions with a comprehensive method of prediting CHF at these local conditions, makes it a unique tool for predicting CHF for situations outside the existing experimental data base. In particular, ASSERT is an appropriate tool to systematically investigate CHF under conditions of local geometric variations, such as pressure tube creep and fuel element strain. This paper discusses the numerical methodology used in ASSERT, the constitutive relationships incorporated, and the CHF assessment methodology. The evolutionary validation plan is discussed, and early validation exercises are summarized. The paper concentrates, however, on more recent validation exercises in standard and non-standard geometries
Møldrup, Per; Chamindu, T. K. K. Deepagoda; Hamamoto, S.
2013-01-01
The soil-gas diffusion is a primary driver of transport, reactions, emissions, and uptake of vadose zone gases, including oxygen, greenhouse gases, fumigants, and spilled volatile organics. The soil-gas diffusion coefficient, Dp, depends not only on soil moisture content, texture, and compaction...... but also on the local-scale variability of these. Different predictive models have been developed to estimate Dp in intact and repacked soil, but clear guidelines for model choice at a given soil state are lacking. In this study, the water-induced linear reduction (WLR) model for repacked soil is made...... air) in repacked soils containing between 0 and 54% clay. With Cm = 2.1, the SWLR model on average gave excellent predictions for 290 intact soils, performing well across soil depths, textures, and compactions (dry bulk densities). The SWLR model generally outperformed similar, simple Dp/Do models...
A Family of High-Performance Solvers for Linear Model Predictive Control
Frison, Gianluca; Sokoler, Leo Emil; Jørgensen, John Bagterp
2014-01-01
In Model Predictive Control (MPC), an optimization problem has to be solved at each sampling time, and this has traditionally limited the use of MPC to systems with slow dynamic. In this paper, we propose an e_cient solution strategy for the unconstrained sub-problems that give the search......-direction in Interior-Point (IP) methods for MPC, and that usually are the computational bottle-neck. This strategy combines a Riccati-like solver with the use of high-performance computing techniques: in particular, in this paper we explore the performance boost given by the use of single precision computation...
Wang, Jim Jing-Yan; Gao, Xin
2014-01-01
Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled. By using the manifold structure spanned by the data set of both labeled and unlabeled samples and the constraints provided by the labels of the labeled samples, we learn the variable class labels for all the samples. Furthermore, to improve the discriminative ability of the learned sparse codes, we assume that the class labels could be predicted from the sparse codes directly using a linear classifier. By solving the codebook, sparse codes, class labels and classifier parameters simultaneously in a unified objective function, we develop a semi-supervised sparse coding algorithm. Experiments on two real-world pattern recognition problems demonstrate the advantage of the proposed methods over supervised sparse coding methods on partially labeled data sets.
Wang, Jim Jing-Yan
2014-07-06
Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a semi-supervised manner, where only a few training samples are labeled. By using the manifold structure spanned by the data set of both labeled and unlabeled samples and the constraints provided by the labels of the labeled samples, we learn the variable class labels for all the samples. Furthermore, to improve the discriminative ability of the learned sparse codes, we assume that the class labels could be predicted from the sparse codes directly using a linear classifier. By solving the codebook, sparse codes, class labels and classifier parameters simultaneously in a unified objective function, we develop a semi-supervised sparse coding algorithm. Experiments on two real-world pattern recognition problems demonstrate the advantage of the proposed methods over supervised sparse coding methods on partially labeled data sets.
Aragones, J.M.; Ahnert, C.
1995-01-01
New computational methods have been developed in our 3-D PWR core dynamics SIMTRAN code for online surveillance and prediction. They improve the accuracy and efficiency of the coupled neutronic-thermalhydraulic solution and extend its scope to provide, mainly, the calculation of: the fission reaction rates at the incore mini-detectors; the responses at the excore detectors (power range); the temperatures at the thermocouple locations; and the in-vessel distribution of the loop cold-leg inlet coolant conditions in the reflector and core channels, and to the hot-leg outlets per loop. The functional capabilities implemented in the extended SIMTRAN code for online utilization include: online surveillance, incore-excore calibration, evaluation of peak power factors and thermal margins, nominal update and cycle follow, prediction of maneuvers and diagnosis of fast transients and oscillations. The new code has been installed at the Vandellos-II PWR unit in Spain, since the startup of its cycle 7 in mid-June, 1994. The computational implementation has been performed on HP-700 workstations under the HP-UX Unix system, including the machine-man interfaces for online acquisition of measured data and interactive graphical utilization, in C and X11. The agreement of the simulated results with the measured data, during the startup tests and first months of actual operation, is well within the accuracy requirements. The performance and usefulness shown during the testing and demo phase, to be extended along this cycle, has proved that SIMTRAN and the man-machine graphic user interface have the qualities for a fast, accurate, user friendly, reliable, detailed and comprehensive online core surveillance and prediction